Recommendations for Modeling Disaster Responses in Public Health and Medicine: A Position Paper of The Society for Medical Decision Making

PubMed Central

Brandeau, Margaret L.; McCoy, Jessica H.; Hupert, Nathaniel; Holty, Jon-Erik; Bravata, Dena M.

2013-01-01

Purpose Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. We examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models. Methods We reviewed a spectrum of published disaster response models addressing public health or healthcare delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. We developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making. Results We propose six recommendations for model construction and reporting, inspired by the most exemplary models: Health sector disaster response models should address real-world problems; be designed for maximum usability by response planners; strike the appropriate balance between simplicity and complexity; include appropriate outcomes, which extend beyond those considered in traditional cost-effectiveness analyses; and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models. Conclusions Quantitative models are critical tools for planning effective health sector responses to disasters. The recommendations we propose can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response. PMID:19605887

Recommendations for modeling disaster responses in public health and medicine: a position paper of the society for medical decision making.

PubMed

Brandeau, Margaret L; McCoy, Jessica H; Hupert, Nathaniel; Holty, Jon-Erik; Bravata, Dena M

2009-01-01

Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. The authors examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models. . The authors reviewed a spectrum of published disaster response models addressing public health or health care delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. They developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making. . The authors propose 6 recommendations for model construction and reporting, inspired by the most exemplary models: health sector disaster response models should address real-world problems, be designed for maximum usability by response planners, strike the appropriate balance between simplicity and complexity, include appropriate outcomes that extend beyond those considered in traditional cost-effectiveness analyses, and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models. . Quantitative models are critical tools for planning effective health sector responses to disasters. The proposed recommendations can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response.

Response Mixture Modeling: Accounting for Heterogeneity in Item Characteristics across Response Times.

PubMed

Molenaar, Dylan; de Boeck, Paul

2018-06-01

In item response theory modeling of responses and response times, it is commonly assumed that the item responses have the same characteristics across the response times. However, heterogeneity might arise in the data if subjects resort to different response processes when solving the test items. These differences may be within-subject effects, that is, a subject might use a certain process on some of the items and a different process with different item characteristics on the other items. If the probability of using one process over the other process depends on the subject's response time, within-subject heterogeneity of the item characteristics across the response times arises. In this paper, the method of response mixture modeling is presented to account for such heterogeneity. Contrary to traditional mixture modeling where the full response vectors are classified, response mixture modeling involves classification of the individual elements in the response vector. In a simulation study, the response mixture model is shown to be viable in terms of parameter recovery. In addition, the response mixture model is applied to a real dataset to illustrate its use in investigating within-subject heterogeneity in the item characteristics across response times.

A Two-Decision Model for Responses to Likert-Type Items

ERIC Educational Resources Information Center

Thissen-Roe, Anne; Thissen, David

2013-01-01

Extreme response set, the tendency to prefer the lowest or highest response option when confronted with a Likert-type response scale, can lead to misfit of item response models such as the generalized partial credit model. Recently, a series of intrinsically multidimensional item response models have been hypothesized, wherein tendency toward…

Modeling Rabbit Responses to Single and Multiple Aerosol ...

EPA Pesticide Factsheets

Journal Article Survival models are developed here to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple dose dataset to predict the probability of death through specifying dose-response functions and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) has an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed employ different underlying dose-response functions and use the assumption that, in a multiple dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this paper. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high-dose rabbit datasets. More accurate survival models depend upon future development of dose-response datasets specifically designed to assess potential multiple dose effects on response and time-to-response. The process used in this paper to dev

A Measurement Model for Likert Responses that Incorporates Response Time

ERIC Educational Resources Information Center

Ferrando, Pere J.; Lorenzo-Seva, Urbano

2007-01-01

This article describes a model for response times that is proposed as a supplement to the usual factor-analytic model for responses to graded or more continuous typical-response items. The use of the proposed model together with the factor model provides additional information about the respondent and can potentially increase the accuracy of the…

A Flexible Latent Trait Model for Response Times in Tests

ERIC Educational Resources Information Center

Ranger, Jochen; Kuhn, Jorg-Tobias

2012-01-01

Latent trait models for response times in tests have become popular recently. One challenge for response time modeling is the fact that the distribution of response times can differ considerably even in similar tests. In order to reduce the need for tailor-made models, a model is proposed that unifies two popular approaches to response time…

Using Data Augmentation and Markov Chain Monte Carlo for the Estimation of Unfolding Response Models

ERIC Educational Resources Information Center

Johnson, Matthew S.; Junker, Brian W.

2003-01-01

Unfolding response models, a class of item response theory (IRT) models that assume a unimodal item response function (IRF), are often used for the measurement of attitudes. Verhelst and Verstralen (1993)and Andrich and Luo (1993) independently developed unfolding response models by relating the observed responses to a more common monotone IRT…

A Primer on the 2- and 3-Parameter Item Response Theory Models.

ERIC Educational Resources Information Center

Thornton, Artist

Item response theory (IRT) is a useful and effective tool for item response measurement if used in the proper context. This paper discusses the sets of assumptions under which responses can be modeled while exploring the framework of the IRT models relative to response testing. The one parameter model, or one parameter logistic model, is perhaps…

Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses

NASA Astrophysics Data System (ADS)

Rowland, L.; Harper, A.; Christoffersen, B. O.; Galbraith, D. R.; Imbuzeiro, H. M. A.; Powell, T. L.; Doughty, C.; Levine, N. M.; Malhi, Y.; Saleska, S. R.; Moorcroft, P. R.; Meir, P.; Williams, M.

2014-11-01

Accurately predicting the response of Amazonia to climate change is important for predicting changes across the globe. However, changes in multiple climatic factors simultaneously may result in complex non-linear responses, which are difficult to predict using vegetation models. Using leaf and canopy scale observations, this study evaluated the capability of five vegetation models (CLM3.5, ED2, JULES, SiB3, and SPA) to simulate the responses of canopy and leaf scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation. There was greater model-data consistency in the response of net ecosystem exchange to changes in temperature, than in the response to temperature of leaf area index (LAI), net photosynthesis (An) and stomatal conductance (gs). Modelled canopy scale fluxes are calculated by scaling leaf scale fluxes to LAI, and therefore in this study similarities in modelled ecosystem scale responses to drought and temperature were the result of inconsistent leaf scale and LAI responses among models. Across the models, the response of An to temperature was more closely linked to stomatal behaviour than biochemical processes. Consequently all the models predicted that GPP would be higher if tropical forests were 5 °C colder, closer to the model optima for gs. There was however no model consistency in the response of the An-gs relationship when temperature changes and drought were introduced simultaneously. The inconsistencies in the An-gs relationships amongst models were caused by to non-linear model responses induced by simultaneous drought and temperature change. To improve the reliability of simulations of the response of Amazonian rainforest to climate change the mechanistic underpinnings of vegetation models need more complete validation to improve accuracy and consistency in the scaling of processes from leaf to canopy.

Response moderation models for conditional dependence between response time and response accuracy.

PubMed

Bolsinova, Maria; Tijmstra, Jesper; Molenaar, Dylan

2017-05-01

It is becoming more feasible and common to register response times in the application of psychometric tests. Researchers thus have the opportunity to jointly model response accuracy and response time, which provides users with more relevant information. The most common choice is to use the hierarchical model (van der Linden, 2007, Psychometrika, 72, 287), which assumes conditional independence between response time and accuracy, given a person's speed and ability. However, this assumption may be violated in practice if, for example, persons vary their speed or differ in their response strategies, leading to conditional dependence between response time and accuracy and confounding measurement. We propose six nested hierarchical models for response time and accuracy that allow for conditional dependence, and discuss their relationship to existing models. Unlike existing approaches, the proposed hierarchical models allow for various forms of conditional dependence in the model and allow the effect of continuous residual response time on response accuracy to be item-specific, person-specific, or both. Estimation procedures for the models are proposed, as well as two information criteria that can be used for model selection. Parameter recovery and usefulness of the information criteria are investigated using simulation, indicating that the procedure works well and is likely to select the appropriate model. Two empirical applications are discussed to illustrate the different types of conditional dependence that may occur in practice and how these can be captured using the proposed hierarchical models. © 2016 The British Psychological Society.

Modelling Mathematics Problem Solving Item Responses Using a Multidimensional IRT Model

ERIC Educational Resources Information Center

Wu, Margaret; Adams, Raymond

2006-01-01

This research examined students' responses to mathematics problem-solving tasks and applied a general multidimensional IRT model at the response category level. In doing so, cognitive processes were identified and modelled through item response modelling to extract more information than would be provided using conventional practices in scoring…

A heteroscedastic generalized linear model with a non-normal speed factor for responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria

2017-05-01

In generalized linear modelling of responses and response times, the observed response time variables are commonly transformed to make their distribution approximately normal. A normal distribution for the transformed response times is desirable as it justifies the linearity and homoscedasticity assumptions in the underlying linear model. Past research has, however, shown that the transformed response times are not always normal. Models have been developed to accommodate this violation. In the present study, we propose a modelling approach for responses and response times to test and model non-normality in the transformed response times. Most importantly, we distinguish between non-normality due to heteroscedastic residual variances, and non-normality due to a skewed speed factor. In a simulation study, we establish parameter recovery and the power to separate both effects. In addition, we apply the model to a real data set. © 2017 The Authors. British Journal of Mathematical and Statistical Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

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.

Effects of prompting and reinforcement of one response pattern upon imitation of a different modeled pattern

PubMed Central

Bondy, Andrew S.

1982-01-01

Twelve preschool children participated in a study of the effects of explicit training on the imitation of modeled behavior. The responses trained involved a marble-dropping pattern that differed from the modeled pattern. Training consisted of physical prompts and verbal praise during a single session. No prompts or praise were used during test periods. After operant levels of the experimental responses were measured, training either preceded or was interposed within a series of exposures to modeled behavior that differed from the trained behavior. Children who were initially exposed to a modeling session immediately imitated, whereas those children who were initially trained immediately performed the appropriate response. Children initially trained on one pattern generally continued to exhibit that pattern even after many modeling sessions. Children who first viewed the modeled response and then were exposed to explicit training of a different response reversed their response pattern from the trained response to the modeled response within a few sessions. The results suggest that under certain conditions explicit training will exert greater control over responding than immediate modeling stimuli. PMID:16812260

Hidden Markov Item Response Theory Models for Responses and Response Times.

PubMed

Molenaar, Dylan; Oberski, Daniel; Vermunt, Jeroen; De Boeck, Paul

2016-01-01

Current approaches to model responses and response times to psychometric tests solely focus on between-subject differences in speed and ability. Within subjects, speed and ability are assumed to be constants. Violations of this assumption are generally absorbed in the residual of the model. As a result, within-subject departures from the between-subject speed and ability level remain undetected. These departures may be of interest to the researcher as they reflect differences in the response processes adopted on the items of a test. In this article, we propose a dynamic approach for responses and response times based on hidden Markov modeling to account for within-subject differences in responses and response times. A simulation study is conducted to demonstrate acceptable parameter recovery and acceptable performance of various fit indices in distinguishing between different models. In addition, both a confirmatory and an exploratory application are presented to demonstrate the practical value of the modeling approach.

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

Women's Endorsement of Models of Sexual Response: Correlates and Predictors.

PubMed

Nowosielski, Krzysztof; Wróbel, Beata; Kowalczyk, Robert

2016-02-01

Few studies have investigated endorsement of female sexual response models, and no single model has been accepted as a normative description of women's sexual response. The aim of the study was to establish how women from a population-based sample endorse current theoretical models of the female sexual response--the linear models and circular model (partial and composite Basson models)--as well as predictors of endorsement. Accordingly, 174 heterosexual women aged 18-55 years were included in a cross-sectional study: 74 women diagnosed with female sexual dysfunction (FSD) based on DSM-5 criteria and 100 non-dysfunctional women. The description of sexual response models was used to divide subjects into four subgroups: linear (Masters-Johnson and Kaplan models), circular (partial Basson model), mixed (linear and circular models in similar proportions, reflective of the composite Basson model), and a different model. Women were asked to choose which of the models best described their pattern of sexual response and how frequently they engaged in each model. Results showed that 28.7% of women endorsed the linear models, 19.5% the partial Basson model, 40.8% the composite Basson model, and 10.9% a different model. Women with FSD endorsed the partial Basson model and a different model more frequently than did non-dysfunctional controls. Individuals who were dissatisfied with a partner as a lover were more likely to endorse a different model. Based on the results, we concluded that the majority of women endorsed a mixed model combining the circular response with the possibility of an innate desire triggering a linear response. Further, relationship difficulties, not FSD, predicted model endorsement.

A Unidimensional Item Response Model for Unfolding Responses from a Graded Disagree-Agree Response Scale.

ERIC Educational Resources Information Center

Roberts, James S.; Laughlin, James E.

1996-01-01

A parametric item response theory model for unfolding binary or graded responses is developed. The graded unfolding model (GUM) is a generalization of the hyperbolic cosine model for binary data of D. Andrich and G. Luo (1993). Applicability of the GUM to attitude testing is illustrated with real data. (SLD)

Theoretical and Empirical Comparisons between Two Models for Continuous Item Responses.

ERIC Educational Resources Information Center

Ferrando, Pere J.

2002-01-01

Analyzed the relations between two continuous response models intended for typical response items: the linear congeneric model and Samejima's continuous response model (CRM). Illustrated the relations described using an empirical example and assessed the relations through a simulation study. (SLD)

Graded Response Model Based on the Logistic Positive Exponent Family of Models for Dichotomous Responses

ERIC Educational Resources Information Center

Samejima, Fumiko

2008-01-01

Samejima ("Psychometrika "65:319--335, 2000) proposed the logistic positive exponent family of models (LPEF) for dichotomous responses in the unidimensional latent space. The objective of the present paper is to propose and discuss a graded response model that is expanded from the LPEF, in the context of item response theory (IRT). This…

Forced-Choice Assessment of Work-Related Maladaptive Personality Traits: Preliminary Evidence From an Application of Thurstonian Item Response Modeling.

PubMed

Guenole, Nigel; Brown, Anna A; Cooper, Andrew J

2018-06-01

This article describes an investigation of whether Thurstonian item response modeling is a viable method for assessment of maladaptive traits. Forced-choice responses from 420 working adults to a broad-range personality inventory assessing six maladaptive traits were considered. The Thurstonian item response model's fit to the forced-choice data was adequate, while the fit of a counterpart item response model to responses to the same items but arranged in a single-stimulus design was poor. Monotrait heteromethod correlations indicated corresponding traits in the two formats overlapped substantially, although they did not measure equivalent constructs. A better goodness of fit and higher factor loadings for the Thurstonian item response model, coupled with a clearer conceptual alignment to the theoretical trait definitions, suggested that the single-stimulus item responses were influenced by biases that the independent clusters measurement model did not account for. Researchers may wish to consider forced-choice designs and appropriate item response modeling techniques such as Thurstonian item response modeling for personality questionnaire applications in industrial psychology, especially when assessing maladaptive traits. We recommend further investigation of this approach in actual selection situations and with different assessment instruments.

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.

A note on monotonicity of item response functions for ordered polytomous item response theory models.

PubMed

Kang, Hyeon-Ah; Su, Ya-Hui; Chang, Hua-Hua

2018-03-08

A monotone relationship between a true score (τ) and a latent trait level (θ) has been a key assumption for many psychometric applications. The monotonicity property in dichotomous response models is evident as a result of a transformation via a test characteristic curve. Monotonicity in polytomous models, in contrast, is not immediately obvious because item response functions are determined by a set of response category curves, which are conceivably non-monotonic in θ. The purpose of the present note is to demonstrate strict monotonicity in ordered polytomous item response models. Five models that are widely used in operational assessments are considered for proof: the generalized partial credit model (Muraki, 1992, Applied Psychological Measurement, 16, 159), the nominal model (Bock, 1972, Psychometrika, 37, 29), the partial credit model (Masters, 1982, Psychometrika, 47, 147), the rating scale model (Andrich, 1978, Psychometrika, 43, 561), and the graded response model (Samejima, 1972, A general model for free-response data (Psychometric Monograph no. 18). Psychometric Society, Richmond). The study asserts that the item response functions in these models strictly increase in θ and thus there exists strict monotonicity between τ and θ under certain specified conditions. This conclusion validates the practice of customarily using τ in place of θ in applied settings and provides theoretical grounds for one-to-one transformations between the two scales. © 2018 The British Psychological Society.

Estimating multivariate response surface model with data outliers, case study in enhancing surface layer properties of an aircraft aluminium alloy

NASA Astrophysics Data System (ADS)

Widodo, Edy; Kariyam

2017-03-01

To determine the input variable settings that create the optimal compromise in response variable used Response Surface Methodology (RSM). There are three primary steps in the RSM problem, namely data collection, modelling, and optimization. In this study focused on the establishment of response surface models, using the assumption that the data produced is correct. Usually the response surface model parameters are estimated by OLS. However, this method is highly sensitive to outliers. Outliers can generate substantial residual and often affect the estimator models. Estimator models produced can be biased and could lead to errors in the determination of the optimal point of fact, that the main purpose of RSM is not reached. Meanwhile, in real life, the collected data often contain some response variable and a set of independent variables. Treat each response separately and apply a single response procedures can result in the wrong interpretation. So we need a development model for the multi-response case. Therefore, it takes a multivariate model of the response surface that is resistant to outliers. As an alternative, in this study discussed on M-estimation as a parameter estimator in multivariate response surface models containing outliers. As an illustration presented a case study on the experimental results to the enhancement of the surface layer of aluminium alloy air by shot peening.

Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods

ERIC Educational Resources Information Center

Rabe-Hesketh, Sophia; Skrondal, Anders

2007-01-01

Composite links and exploded likelihoods are powerful yet simple tools for specifying a wide range of latent variable models. Applications considered include survival or duration models, models for rankings, small area estimation with census information, models for ordinal responses, item response models with guessing, randomized response models,…

A Box-Cox normal model for response times.

PubMed

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

2009-11-01

The log-transform has been a convenient choice in response time modelling on test items. However, motivated by a dataset of the Medical College Admission Test where the lognormal model violated the normality assumption, the possibilities of the broader class of Box-Cox transformations for response time modelling are investigated. After an introduction and an outline of a broader framework for analysing responses and response times simultaneously, the performance of a Box-Cox normal model for describing response times is investigated using simulation studies and a real data example. A transformation-invariant implementation of the deviance information criterium (DIC) is developed that allows for comparing model fit between models with different transformation parameters. Showing an enhanced description of the shape of the response time distributions, its application in an educational measurement context is discussed at length.

On the effect of acoustic coupling on random and harmonic plate vibrations

NASA Technical Reports Server (NTRS)

Frendi, A.; Robinson, J. H.

1993-01-01

The effect of acoustic coupling on random and harmonic plate vibrations is studied using two numerical models. In the coupled model, the plate response is obtained by integration of the nonlinear plate equation coupled with the nonlinear Euler equations for the surrounding acoustic fluid. In the uncoupled model, the nonlinear plate equation with an equivalent linear viscous damping term is integrated to obtain the response of the plate subject to the same excitation field. For a low-level, narrow-band excitation, the two models predict the same plate response spectra. As the excitation level is increased, the response power spectrum predicted by the uncoupled model becomes broader and more shifted towards the high frequencies than that obtained by the coupled model. In addition, the difference in response between the coupled and uncoupled models at high frequencies becomes larger. When a high intensity harmonic excitation is used, causing a nonlinear plate response, both models predict the same frequency content of the response. However, the level of the harmonics and subharmonics are higher for the uncoupled model. Comparisons to earlier experimental and numerical results show that acoustic coupling has a significant effect on the plate response at high excitation levels. Its absence in previous models may explain the discrepancy between predicted and measured responses.

Some Statistics for Assessing Person-Fit Based on Continuous-Response Models

ERIC Educational Resources Information Center

Ferrando, Pere Joan

2010-01-01

This article proposes several statistics for assessing individual fit based on two unidimensional models for continuous responses: linear factor analysis and Samejima's continuous response model. Both models are approached using a common framework based on underlying response variables and are formulated at the individual level as fixed regression…

Stochastic Approximation Methods for Latent Regression Item Response Models

ERIC Educational Resources Information Center

von Davier, Matthias; Sinharay, Sandip

2010-01-01

This article presents an application of a stochastic approximation expectation maximization (EM) algorithm using a Metropolis-Hastings (MH) sampler to estimate the parameters of an item response latent regression model. Latent regression item response models are extensions of item response theory (IRT) to a latent variable model with covariates…

Influence of tyre-road contact model on vehicle vibration response

NASA Astrophysics Data System (ADS)

Múčka, Peter; Gagnon, Louis

2015-09-01

The influence of the tyre-road contact model on the simulated vertical vibration response was analysed. Three contact models were compared: tyre-road point contact model, moving averaged profile and tyre-enveloping model. In total, 1600 real asphalt concrete and Portland cement concrete longitudinal road profiles were processed. The linear planar model of automobile with 12 degrees of freedom (DOF) was used. Five vibration responses as the measures of ride comfort, ride safety and dynamic load of cargo were investigated. The results were calculated as a function of vibration response, vehicle velocity, road quality and road surface type. The marked differences in the dynamic tyre forces and the negligible differences in the ride comfort quantities were observed among the tyre-road contact models. The seat acceleration response for three contact models and 331 DOF multibody model of the truck semi-trailer was compared with the measured response for a known profile of test section.

COBRA ATD multispectral camera response model

NASA Astrophysics Data System (ADS)

Holmes, V. Todd; Kenton, Arthur C.; Hilton, Russell J.; Witherspoon, Ned H.; Holloway, John H., Jr.

2000-08-01

A new multispectral camera response model has been developed in support of the US Marine Corps (USMC) Coastal Battlefield Reconnaissance and Analysis (COBRA) Advanced Technology Demonstration (ATD) Program. This analytical model accurately estimates response form five Xybion intensified IMC 201 multispectral cameras used for COBRA ATD airborne minefield detection. The camera model design is based on a series of camera response curves which were generated through optical laboratory test performed by the Naval Surface Warfare Center, Dahlgren Division, Coastal Systems Station (CSS). Data fitting techniques were applied to these measured response curves to obtain nonlinear expressions which estimates digitized camera output as a function of irradiance, intensifier gain, and exposure. This COBRA Camera Response Model was proven to be very accurate, stable over a wide range of parameters, analytically invertible, and relatively simple. This practical camera model was subsequently incorporated into the COBRA sensor performance evaluation and computational tools for research analysis modeling toolbox in order to enhance COBRA modeling and simulation capabilities. Details of the camera model design and comparisons of modeled response to measured experimental data are presented.

Comparison of Response Surface and Kriging Models for Multidisciplinary Design Optimization

NASA Technical Reports Server (NTRS)

Simpson, Timothy W.; Korte, John J.; Mauery, Timothy M.; Mistree, Farrokh

1998-01-01

In this paper, we compare and contrast the use of second-order response surface models and kriging models for approximating non-random, deterministic computer analyses. After reviewing the response surface method for constructing polynomial approximations, kriging is presented as an alternative approximation method for the design and analysis of computer experiments. Both methods are applied to the multidisciplinary design of an aerospike nozzle which consists of a computational fluid dynamics model and a finite-element model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations, and four optimization problems m formulated and solved using both sets of approximation models. The second-order response surface models and kriging models-using a constant underlying global model and a Gaussian correlation function-yield comparable results.

A Riparian Vegetation Ecophysiological Response Model

Treesearch

Jeffrey P. Leighton; Roland J. Risser

1989-01-01

A mathematical model is described that relates mature riparian vegetation ecophysiological response to changes in stream level. This model was developed to estimate the physiological response of riparian vegetation to reductions in streamflow. Field data from two sites on the North Fork of the Kings River were used in the model development. The physiological response...

A Linear Variable-[theta] Model for Measuring Individual Differences in Response Precision

ERIC Educational Resources Information Center

Ferrando, Pere J.

2011-01-01

Models for measuring individual response precision have been proposed for binary and graded responses. However, more continuous formats are quite common in personality measurement and are usually analyzed with the linear factor analysis model. This study extends the general Gaussian person-fluctuation model to the continuous-response case and…

Distinguishing Fast and Slow Processes in Accuracy - Response Time Data.

PubMed

Coomans, Frederik; Hofman, Abe; Brinkhuis, Matthieu; van der Maas, Han L J; Maris, Gunter

2016-01-01

We investigate the relation between speed and accuracy within problem solving in its simplest non-trivial form. We consider tests with only two items and code the item responses in two binary variables: one indicating the response accuracy, and one indicating the response speed. Despite being a very basic setup, it enables us to study item pairs stemming from a broad range of domains such as basic arithmetic, first language learning, intelligence-related problems, and chess, with large numbers of observations for every pair of problems under consideration. We carry out a survey over a large number of such item pairs and compare three types of psychometric accuracy-response time models present in the literature: two 'one-process' models, the first of which models accuracy and response time as conditionally independent and the second of which models accuracy and response time as conditionally dependent, and a 'two-process' model which models accuracy contingent on response time. We find that the data clearly violates the restrictions imposed by both one-process models and requires additional complexity which is parsimoniously provided by the two-process model. We supplement our survey with an analysis of the erroneous responses for an example item pair and demonstrate that there are very significant differences between the types of errors in fast and slow responses.

Conceptualization of the Sexual Response Models in Men: Are there Differences Between Sexually Functional and Dysfunctional Men?

PubMed

Connaughton, Catherine; McCabe, Marita; Karantzas, Gery

2016-03-01

Research to validate models of sexual response empirically in men with and without sexual dysfunction (MSD), as currently defined, is limited. To explore the extent to which the traditional linear or the Basson circular model best represents male sexual response for men with MSD and sexually functional men. In total, 573 men completed an online questionnaire to assess sexual function and aspects of the models of sexual response. In total, 42.2% of men (242) were sexually functional, and 57.8% (331) had at least one MSD. Models were built and tested using bootstrapping and structural equation modeling. Fit of models for men with and without MSD. The linear model and the initial circular model were a poor fit for men with and without MSD. A modified version of the circular model demonstrated adequate fit for the two groups and showed important interactions between psychological factors and sexual response for men with and without MSD. Male sexual response was not represented by the linear model for men with or without MSD, excluding possible healthy responsive desire. The circular model provided a better fit for the two groups of men but demonstrated that the relations between psychological factors and phases of sexual response were different for men with and without MSD as currently defined. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Response Surface Methodology Using a Fullest Balanced Model: A Re-Analysis of a Dataset in the Korean Journal for Food Science of Animal Resources.

PubMed

Rheem, Sungsue; Rheem, Insoo; Oh, Sejong

2017-01-01

Response surface methodology (RSM) is a useful set of statistical techniques for modeling and optimizing responses in research studies of food science. In the analysis of response surface data, a second-order polynomial regression model is usually used. However, sometimes we encounter situations where the fit of the second-order model is poor. If the model fitted to the data has a poor fit including a lack of fit, the modeling and optimization results might not be accurate. In such a case, using a fullest balanced model, which has no lack of fit, can fix such problem, enhancing the accuracy of the response surface modeling and optimization. This article presents how to develop and use such a model for the better modeling and optimizing of the response through an illustrative re-analysis of a dataset in Park et al. (2014) published in the Korean Journal for Food Science of Animal Resources .

Modeling Response Signal and Response Time Data

ERIC Educational Resources Information Center

Ratcliff, Roger

2006-01-01

The diffusion model (Ratcliff, 1978) and the leaky competing accumulator model (LCA, Usher & McClelland, 2001) were tested against two-choice data collected from the same subjects with the standard response time procedure and the response signal procedure. In the response signal procedure, a stimulus is presented and then, at one of a number of…

Analysis and test evaluation of the dynamic response and stability of three advanced turboprop models

NASA Technical Reports Server (NTRS)

Bansal, P. N.; Arseneaux, P. J.; Smith, A. F.; Turnberg, J. E.; Brooks, B. M.

1985-01-01

Results of dynamic response and stability wind tunnel tests of three 62.2 cm (24.5 in) diameter models of the Prop-Fan, advanced turboprop, are presented. Measurements of dynamic response were made with the rotors mounted on an isolated nacelle, with varying tilt for nonuniform inflow. One model was also tested using a semi-span wing and fuselage configuration for response to realistic aircraft inflow. Stability tests were performed using tunnel turbulence or a nitrogen jet for excitation. Measurements are compared with predictions made using beam analysis methods for the model with straight blades, and finite element analysis methods for the models with swept blades. Correlations between measured and predicted rotating blade natural frequencies for all the models are very good. The IP dynamic response of the straight blade model is reasonably well predicted. The IP response of the swept blades is underpredicted and the wing induced response of the straight blade is overpredicted. Two models did not flutter, as predicted. One swept blade model encountered an instability at a higher RPM than predicted, showing predictions to be conservative.

Regional and Global Climate Response to Anthropogenic SO2 Emissions from China in Three Climate Models

NASA Technical Reports Server (NTRS)

Kasoar, M.; Voulgarakis, Apostolos; Lamarque, Jean-Francois; Shindell, Drew T.; Bellouin, Nicholas; Collins, William J.; Faluvegi, Greg; Tsigaridis, Kostas

2016-01-01

We use the HadGEM3-GA4, CESM1, and GISS ModelE2 climate models to investigate the global and regional aerosol burden, radiative flux, and surface temperature responses to removing anthropogenic sulfur dioxide (SO2) emissions from China. We find that the models differ by up to a factor of 6 in the simulated change in aerosol optical depth (AOD) and shortwave radiative flux over China that results from reduced sulfate aerosol, leading to a large range of magnitudes in the regional and global temperature responses. Two of the three models simulate a near-ubiquitous hemispheric warming due to the regional SO2 removal, with similarities in the local and remote pattern of response, but overall with a substantially different magnitude. The third model simulates almost no significant temperature response. We attribute the discrepancies in the response to a combination of substantial differences in the chemical conversion of SO2 to sulfate, translation of sulfate mass into AOD, cloud radiative interactions, and differences in the radiative forcing efficiency of sulfate aerosol in the models. The model with the strongest response (HadGEM3-GA4) compares best with observations of AOD regionally, however the other two models compare similarly (albeit poorly) and still disagree substantially in their simulated climate response, indicating that total AOD observations are far from sufficient to determine which model response is more plausible. Our results highlight that there remains a large uncertainty in the representation of both aerosol chemistry as well as direct and indirect aerosol radiative effects in current climate models, and reinforces that caution must be applied when interpreting the results of modelling studies of aerosol influences on climate. Model studies that implicate aerosols in climate responses should ideally explore a range of radiative forcing strengths representative of this uncertainty, in addition to thoroughly evaluating the models used against observations.

Ramsay-Curve Item Response Theory for the Three-Parameter Logistic Item Response Model

ERIC Educational Resources Information Center

Woods, Carol M.

2008-01-01

In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters of a unidimensional item response model using marginal maximum likelihood estimation. This study evaluates RC-IRT for the three-parameter logistic (3PL) model with comparisons to the normal model and to the empirical…

Using Response Times for Item Selection in Adaptive Testing

ERIC Educational Resources Information Center

van der Linden, Wim J.

2008-01-01

Response times on items can be used to improve item selection in adaptive testing provided that a probabilistic model for their distribution is available. In this research, the author used a hierarchical modeling framework with separate first-level models for the responses and response times and a second-level model for the distribution of the…

Comparison of Response Surface and Kriging Models in the Multidisciplinary Design of an Aerospike Nozzle

NASA Technical Reports Server (NTRS)

Simpson, Timothy W.

1998-01-01

The use of response surface models and kriging models are compared for approximating non-random, deterministic computer analyses. After discussing the traditional response surface approach for constructing polynomial models for approximation, kriging is presented as an alternative statistical-based approximation method for the design and analysis of computer experiments. Both approximation methods are applied to the multidisciplinary design and analysis of an aerospike nozzle which consists of a computational fluid dynamics model and a finite element analysis model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations. Four optimization problems are formulated and solved using both approximation models. While neither approximation technique consistently outperforms the other in this example, the kriging models using only a constant for the underlying global model and a Gaussian correlation function perform as well as the second order polynomial response surface models.

The Model Averaging for Dichotomous Response Benchmark Dose (MADr-BMD) Tool

EPA Pesticide Factsheets

Providing quantal response models, which are also used in the U.S. EPA benchmark dose software suite, and generates a model-averaged dose response model to generate benchmark dose and benchmark dose lower bound estimates.

Application for managing model-based material properties for simulation-based engineering

DOEpatents

Hoffman, Edward L [Alameda, CA

2009-03-03

An application for generating a property set associated with a constitutive model of a material includes a first program module adapted to receive test data associated with the material and to extract loading conditions from the test data. A material model driver is adapted to receive the loading conditions and a property set and operable in response to the loading conditions and the property set to generate a model response for the material. A numerical optimization module is adapted to receive the test data and the model response and operable in response to the test data and the model response to generate the property set.

A Mixed Effects Randomized Item Response Model

ERIC Educational Resources Information Center

Fox, J.-P.; Wyrick, Cheryl

2008-01-01

The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called randomized item responses are observed. A relationship is specified between randomized item response data and true item response data. True item response data are modeled with a (non)linear…

Nested Logit Models for Multiple-Choice Item Response Data

ERIC Educational Resources Information Center

Suh, Youngsuk; Bolt, Daniel M.

2010-01-01

Nested logit item response models for multiple-choice data are presented. Relative to previous models, the new models are suggested to provide a better approximation to multiple-choice items where the application of a solution strategy precedes consideration of response options. In practice, the models also accommodate collapsibility across all…

Discrete Latent Markov Models for Normally Distributed Response Data

ERIC Educational Resources Information Center

Schmittmann, Verena D.; Dolan, Conor V.; van der Maas, Han L. J.; Neale, Michael C.

2005-01-01

Van de Pol and Langeheine (1990) presented a general framework for Markov modeling of repeatedly measured discrete data. We discuss analogical single indicator models for normally distributed responses. In contrast to discrete models, which have been studied extensively, analogical continuous response models have hardly been considered. These…

Distinguishing Fast and Slow Processes in Accuracy - Response Time Data

PubMed Central

Coomans, Frederik; Hofman, Abe; Brinkhuis, Matthieu; van der Maas, Han L. J.; Maris, Gunter

2016-01-01

We investigate the relation between speed and accuracy within problem solving in its simplest non-trivial form. We consider tests with only two items and code the item responses in two binary variables: one indicating the response accuracy, and one indicating the response speed. Despite being a very basic setup, it enables us to study item pairs stemming from a broad range of domains such as basic arithmetic, first language learning, intelligence-related problems, and chess, with large numbers of observations for every pair of problems under consideration. We carry out a survey over a large number of such item pairs and compare three types of psychometric accuracy-response time models present in the literature: two ‘one-process’ models, the first of which models accuracy and response time as conditionally independent and the second of which models accuracy and response time as conditionally dependent, and a ‘two-process’ model which models accuracy contingent on response time. We find that the data clearly violates the restrictions imposed by both one-process models and requires additional complexity which is parsimoniously provided by the two-process model. We supplement our survey with an analysis of the erroneous responses for an example item pair and demonstrate that there are very significant differences between the types of errors in fast and slow responses. PMID:27167518

Cognitive psychology meets psychometric theory: on the relation between process models for decision making and latent variable models for individual differences.

PubMed

van der Maas, Han L J; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A; Borsboom, Denny

2011-04-01

This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line of reasoning, we discuss the appropriateness of IRT for measuring abilities and bipolar traits, such as pro versus contra attitudes. Surprisingly, if a diffusion model underlies the response processes, IRT models are appropriate for bipolar traits but not for ability tests. A reconsideration of the concept of ability that is appropriate for such situations leads to a new item response model for accuracy and speed based on the idea that ability has a natural zero point. The model implies fundamentally new ways to think about guessing, response speed, and person fit in IRT. We discuss the relation between this model and existing models as well as implications for psychology and psychometrics. 2011 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

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.

A Comparison of Graded Response and Rasch Partial Credit Models with Subjective Well-Being.

ERIC Educational Resources Information Center

Baker, John G.; Rounds, James B.; Zevon, Michael A.

2000-01-01

Compared two multiple category item response theory models using a data set of 52 mood terms with 713 undergraduate psychology students. Comparative model fit for the Samejima (F. Samejima, 1966) logistic model for graded responses and the Masters (G. Masters, 1982) partial credit model favored the former model for this data set. (SLD)

Modeling winter wheat phenological responses to water deficits in the Unified Plant Growth Model (UPGM) component of the spatially distributed Agricultural Ecosystem Services (AgES) model

USDA-ARS?s Scientific Manuscript database

Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...

Bayesian Analysis of Multidimensional Item Response Theory Models: A Discussion and Illustration of Three Response Style Models

ERIC Educational Resources Information Center

Leventhal, Brian C.; Stone, Clement A.

2018-01-01

Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

Sample Invariance of the Structural Equation Model and the Item Response Model: A Case Study.

ERIC Educational Resources Information Center

Breithaupt, Krista; Zumbo, Bruno D.

2002-01-01

Evaluated the sample invariance of item discrimination statistics in a case study using real data, responses of 10 random samples of 500 people to a depression scale. Results lend some support to the hypothesized superiority of a two-parameter item response model over the common form of structural equation modeling, at least when responses are…

Evaluating a Computational Model of Social Causality and Responsibility

DTIC Science & Technology

2006-01-01

Evaluating a Computational Model of Social Causality and Responsibility Wenji Mao University of Southern California Institute for Creative...empirically evaluate a computa- tional model of social causality and responsibility against human social judgments. Results from our experimental...developed a general computational model of social cau- sality and responsibility [10, 11] that formalizes the factors people use in reasoning about

Modelling the isometric force response to multiple pulse stimuli in locust skeletal muscle.

PubMed

Wilson, Emma; Rustighi, Emiliano; Mace, Brian R; Newland, Philip L

2011-02-01

An improved model of locust skeletal muscle will inform on the general behaviour of invertebrate and mammalian muscle with the eventual aim of improving biomedical models of human muscles, embracing prosthetic construction and muscle therapy. In this article, the isometric response of the locust hind leg extensor muscle to input pulse trains is investigated. Experimental data was collected by stimulating the muscle directly and measuring the force at the tibia. The responses to constant frequency stimulus trains of various frequencies and number of pulses were decomposed into the response to each individual stimulus. Each individual pulse response was then fitted to a model, it being assumed that the response to each pulse could be approximated as an impulse response and was linear, no assumption were made about the model order. When the interpulse frequency (IPF) was low and the number of pulses in the train small, a second-order model provided a good fit to each pulse. For moderate IPF or for long pulse trains a linear third-order model provided a better fit to the response to each pulse. The fit using a second-order model deteriorated with increasing IPF. When the input comprised higher IPFs with a large number of pulses the assumptions that the response was linear could not be confirmed. A generalised model is also presented. This model is second-order, and contains two nonlinear terms. The model is able to capture the force response to a range of inputs. This includes cases where the input comprised of higher frequency pulse trains and the assumption of quasi-linear behaviour could not be confirmed.

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

PubMed

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

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.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

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.

On the Relationship Between Classical Test Theory and Item Response Theory: From One to the Other and Back.

PubMed

Raykov, Tenko; Marcoulides, George A

2016-04-01

The frequently neglected and often misunderstood relationship between classical test theory and item response theory is discussed for the unidimensional case with binary measures and no guessing. It is pointed out that popular item response models can be directly obtained from classical test theory-based models by accounting for the discrete nature of the observed items. Two distinct observational equivalence approaches are outlined that render the item response models from corresponding classical test theory-based models, and can each be used to obtain the former from the latter models. Similarly, classical test theory models can be furnished using the reverse application of either of those approaches from corresponding item response models.

Item response theory - A first approach

NASA Astrophysics Data System (ADS)

Nunes, Sandra; Oliveira, Teresa; Oliveira, Amílcar

2017-07-01

The Item Response Theory (IRT) has become one of the most popular scoring frameworks for measurement data, frequently used in computerized adaptive testing, cognitively diagnostic assessment and test equating. According to Andrade et al. (2000), IRT can be defined as a set of mathematical models (Item Response Models - IRM) constructed to represent the probability of an individual giving the right answer to an item of a particular test. The number of Item Responsible Models available to measurement analysis has increased considerably in the last fifteen years due to increasing computer power and due to a demand for accuracy and more meaningful inferences grounded in complex data. The developments in modeling with Item Response Theory were related with developments in estimation theory, most remarkably Bayesian estimation with Markov chain Monte Carlo algorithms (Patz & Junker, 1999). The popularity of Item Response Theory has also implied numerous overviews in books and journals, and many connections between IRT and other statistical estimation procedures, such as factor analysis and structural equation modeling, have been made repeatedly (Van der Lindem & Hambleton, 1997). As stated before the Item Response Theory covers a variety of measurement models, ranging from basic one-dimensional models for dichotomously and polytomously scored items and their multidimensional analogues to models that incorporate information about cognitive sub-processes which influence the overall item response process. The aim of this work is to introduce the main concepts associated with one-dimensional models of Item Response Theory, to specify the logistic models with one, two and three parameters, to discuss some properties of these models and to present the main estimation procedures.

Extreme Response Style: Which Model Is Best?

ERIC Educational Resources Information Center

Leventhal, Brian

2017-01-01

More robust and rigorous psychometric models, such as multidimensional Item Response Theory models, have been advocated for survey applications. However, item responses may be influenced by construct-irrelevant variance factors such as preferences for extreme response options. Through empirical and simulation methods, this study evaluates the use…

Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve.

PubMed

Li, Yi; Chen, Yuren

2016-12-30

To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers' perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers' vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers' perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers' perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers' perception-response time.

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…

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.

Pain and the defense response: structural equation modeling reveals a coordinated psychophysiological response to increasing painful stimulation.

PubMed

Donaldson, Gary W; Chapman, C Richard; Nakamura, Yoshi; Bradshaw, David H; Jacobson, Robert C; Chapman, Christopher N

2003-03-01

The defense response theory implies that individuals should respond to increasing levels of painful stimulation with correlated increases in affectively mediated psychophysiological responses. This paper employs structural equation modeling to infer the latent processes responsible for correlated growth in the pain report, evoked potential amplitudes, pupil dilation, and skin conductance of 92 normal volunteers who experienced 144 trials of three levels of increasingly painful electrical stimulation. The analysis assumed a two-level model of latent growth as a function of stimulus level. The first level of analysis formulated a nonlinear growth model for each response measure, and allowed intercorrelations among the parameters of these models across individuals. The second level of analysis posited latent process factors to account for these intercorrelations. The best-fitting parsimonious model suggests that two latent processes account for the correlations. One of these latent factors, the activation threshold, determines the initial threshold response, while the other, the response gradient, indicates the magnitude of the coherent increase in response with stimulus level. Collectively, these two second-order factors define the defense response, a broad construct comprising both subjective pain evaluation and physiological mechanisms.

A mathematical function for the description of nutrient-response curve

PubMed Central

Ahmadi, Hamed

2017-01-01

Several mathematical equations have been proposed to modeling nutrient-response curve for animal and human justified on the goodness of fit and/or on the biological mechanism. In this paper, a functional form of a generalized quantitative model based on Rayleigh distribution principle for description of nutrient-response phenomena is derived. The three parameters governing the curve a) has biological interpretation, b) may be used to calculate reliable estimates of nutrient response relationships, and c) provide the basis for deriving relationships between nutrient and physiological responses. The new function was successfully applied to fit the nutritional data obtained from 6 experiments including a wide range of nutrients and responses. An evaluation and comparison were also done based simulated data sets to check the suitability of new model and four-parameter logistic model for describing nutrient responses. This study indicates the usefulness and wide applicability of the new introduced, simple and flexible model when applied as a quantitative approach to characterizing nutrient-response curve. This new mathematical way to describe nutritional-response data, with some useful biological interpretations, has potential to be used as an alternative approach in modeling nutritional responses curve to estimate nutrient efficiency and requirements. PMID:29161271

A New Model for Acquiescence at the Interface of Psychometrics and Cognitive Psychology.

PubMed

Plieninger, Hansjörg; Heck, Daniel W

2018-05-29

When measuring psychological traits, one has to consider that respondents often show content-unrelated response behavior in answering questionnaires. To disentangle the target trait and two such response styles, extreme responding and midpoint responding, Böckenholt ( 2012a ) developed an item response model based on a latent processing tree structure. We propose a theoretically motivated extension of this model to also measure acquiescence, the tendency to agree with both regular and reversed items. Substantively, our approach builds on multinomial processing tree (MPT) models that are used in cognitive psychology to disentangle qualitatively distinct processes. Accordingly, the new model for response styles assumes a mixture distribution of affirmative responses, which are either determined by the underlying target trait or by acquiescence. In order to estimate the model parameters, we rely on Bayesian hierarchical estimation of MPT models. In simulations, we show that the model provides unbiased estimates of response styles and the target trait, and we compare the new model and Böckenholt's model in a recovery study. An empirical example from personality psychology is used for illustrative purposes.

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.

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.

Generalizability in Item Response Modeling

ERIC Educational Resources Information Center

Briggs, Derek C.; Wilson, Mark

2007-01-01

An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random…

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.

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.

Toward a unified approach to dose-response modeling in ecotoxicology.

PubMed

Ritz, Christian

2010-01-01

This study reviews dose-response models that are used in ecotoxicology. The focus lies on clarification of differences and similarities between models, and as a side effect, their different guises in ecotoxicology are unravelled. A look at frequently used dose-response models reveals major discrepancies, among other things in naming conventions. Therefore, there is a need for a unified view on dose-response modeling in order to improve the understanding of it and to facilitate communication and comparison of findings across studies, thus realizing its full potential. This study attempts to establish a general framework that encompasses most dose-response models that are of interest to ecotoxicologists in practice. The framework includes commonly used models such as the log-logistic and Weibull models, but also features entire suites of models as found in various guidance documents. An outline on how the proposed framework can be implemented in statistical software systems is also provided.

Simple nonlinear modelling of earthquake response in torsionally coupled R/C structures: A preliminary study

NASA Astrophysics Data System (ADS)

Saiidi, M.

1982-07-01

The equivalent of a single degree of freedom (SDOF) nonlinear model, the Q-model-13, was examined. The study intended to: (1) determine the seismic response of a torsionally coupled building based on the multidegree of freedom (MDOF) and (SDOF) nonlinear models; and (2) develop a simple SDOF nonlinear model to calculate displacement history of structures with eccentric centers of mass and stiffness. It is shown that planar models are able to yield qualitative estimates of the response of the building. The model is used to estimate the response of a hypothetical six-story frame wall reinforced concrete building with torsional coupling, using two different earthquake intensities. It is shown that the Q-Model-13 can lead to a satisfactory estimate of the response of the structure in both cases.

Can a Mathematical Model Predict an Individual’s Trait-like Response to Both Total and Partial Sleep Loss?

DTIC Science & Technology

2015-01-01

Can a mathematical model predict an individual’s trait-like response to both total and partial sleep loss? SR IDHAR RAMAKR I SHNAN 1 , WE I LU 1 , SR...biomathematical model, psychomotor vigilance task, sleep -loss phenotype, trait preservation, two-process model Correspondence Jaques Reifman, PhD...trait-like response to sleep loss. However, it is not known whether this trait-like response can be captured by a mathemat- ical model from only one

A Bifactor Multidimensional Item Response Theory Model for Differential Item Functioning Analysis on Testlet-Based Items

ERIC Educational Resources Information Center

Fukuhara, Hirotaka; Kamata, Akihito

2011-01-01

A differential item functioning (DIF) detection method for testlet-based data was proposed and evaluated in this study. The proposed DIF model is an extension of a bifactor multidimensional item response theory (MIRT) model for testlets. Unlike traditional item response theory (IRT) DIF models, the proposed model takes testlet effects into…

Estimating the Nominal Response Model under Nonnormal Conditions

ERIC Educational Resources Information Center

Preston, Kathleen Suzanne Johnson; Reise, Steven Paul

2014-01-01

The nominal response model (NRM), a much understudied polytomous item response theory (IRT) model, provides researchers the unique opportunity to evaluate within-item category distinctions. Polytomous IRT models, such as the NRM, are frequently applied to psychological assessments representing constructs that are unlikely to be normally…

The Development of a Model of Culturally Responsive Science and Mathematics Teaching

ERIC Educational Resources Information Center

Hernandez, Cecilia M.; Morales, Amanda R.; Shroyer, M. Gail

2013-01-01

This qualitative theoretical study was conducted in response to the current need for an inclusive and comprehensive model to guide the preparation and assessment of teacher candidates for culturally responsive teaching. The process of developing a model of culturally responsive teaching involved three steps: a comprehensive review of the…

Randomized Item Response Theory Models

ERIC Educational Resources Information Center

Fox, Jean-Paul

2005-01-01

The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…

Descriptive Linear modeling of steady-state visual evoked response

NASA Technical Reports Server (NTRS)

Levison, W. H.; Junker, A. M.; Kenner, K.

1986-01-01

A study is being conducted to explore use of the steady state visual-evoke electrocortical response as an indicator of cognitive task loading. Application of linear descriptive modeling to steady state Visual Evoked Response (VER) data is summarized. Two aspects of linear modeling are reviewed: (1) unwrapping the phase-shift portion of the frequency response, and (2) parsimonious characterization of task-loading effects in terms of changes in model parameters. Model-based phase unwrapping appears to be most reliable in applications, such as manual control, where theoretical models are available. Linear descriptive modeling of the VER has not yet been shown to provide consistent and readily interpretable results.

An evidence accumulation model for conflict detection performance in a simulated air traffic control task.

PubMed

Neal, Andrew; Kwantes, Peter J

2009-04-01

The aim of this article is to develop a formal model of conflict detection performance. Our model assumes that participants iteratively sample evidence regarding the state of the world and accumulate it over time. A decision is made when the evidence reaches a threshold that changes over time in response to the increasing urgency of the task. Two experiments were conducted to examine the effects of conflict geometry and timing on response proportions and response time. The model is able to predict the observed pattern of response times, including a nonmonotonic relationship between distance at point of closest approach and response time, as well as effects of angle of approach and relative velocity. The results demonstrate that evidence accumulation models provide a good account of performance on a conflict detection task. Evidence accumulation models are a form of dynamic signal detection theory, allowing for the analysis of response times as well as response proportions, and can be used for simulating human performance on dynamic decision tasks.

Handbook of Polytomous Item Response Theory Models

ERIC Educational Resources Information Center

Nering, Michael L., Ed.; Ostini, Remo, Ed.

2010-01-01

This comprehensive "Handbook" focuses on the most used polytomous item response theory (IRT) models. These models help us understand the interaction between examinees and test questions where the questions have various response categories. The book reviews all of the major models and includes discussions about how and where the models…

The Gradual Increase of Responsibility Model: Coaching for Teacher Change

ERIC Educational Resources Information Center

Collet, Vicki S.

2012-01-01

This study examines the gradual increase of responsibility (GIR) model for teacher coaching (Collet, 2008), an adaptation of Pearson and Gallagher's (1983) Gradual Release of Responsibility model. In GIR, instructional coaches model, make recommendations, ask probing questions, affirm teachers' appropriate decisions, and praise in order to provide…

Design considerations and analysis planning of a phase 2a proof of concept study in rheumatoid arthritis in the presence of possible non-monotonicity.

PubMed

Liu, Feng; Walters, Stephen J; Julious, Steven A

2017-10-02

It is important to quantify the dose response for a drug in phase 2a clinical trials so the optimal doses can then be selected for subsequent late phase trials. In a phase 2a clinical trial of new lead drug being developed for the treatment of rheumatoid arthritis (RA), a U-shaped dose response curve was observed. In the light of this result further research was undertaken to design an efficient phase 2a proof of concept (PoC) trial for a follow-on compound using the lessons learnt from the lead compound. The planned analysis for the Phase 2a trial for GSK123456 was a Bayesian Emax model which assumes the dose-response relationship follows a monotonic sigmoid "S" shaped curve. This model was found to be suboptimal to model the U-shaped dose response observed in the data from this trial and alternatives approaches were needed to be considered for the next compound for which a Normal dynamic linear model (NDLM) is proposed. This paper compares the statistical properties of the Bayesian Emax model and NDLM model and both models are evaluated using simulation in the context of adaptive Phase 2a PoC design under a variety of assumed dose response curves: linear, Emax model, U-shaped model, and flat response. It is shown that the NDLM method is flexible and can handle a wide variety of dose-responses, including monotonic and non-monotonic relationships. In comparison to the NDLM model the Emax model excelled with higher probability of selecting ED90 and smaller average sample size, when the true dose response followed Emax like curve. In addition, the type I error, probability of incorrectly concluding a drug may work when it does not, is inflated with the Bayesian NDLM model in all scenarios which would represent a development risk to pharmaceutical company. The bias, which is the difference between the estimated effect from the Emax and NDLM models and the simulated value, is comparable if the true dose response follows a placebo like curve, an Emax like curve, or log linear shape curve under fixed dose allocation, no adaptive allocation, half adaptive and adaptive scenarios. The bias though is significantly increased for the Emax model if the true dose response follows a U-shaped curve. In most cases the Bayesian Emax model works effectively and efficiently, with low bias and good probability of success in case of monotonic dose response. However, if there is a belief that the dose response could be non-monotonic then the NDLM is the superior model to assess the dose response.

Mathematical modeling of human cardiovascular system for simulation of orthostatic response

NASA Technical Reports Server (NTRS)

Melchior, F. M.; Srinivasan, R. S.; Charles, J. B.

1992-01-01

This paper deals with the short-term response of the human cardiovascular system to orthostatic stresses in the context of developing a mathematical model of the overall system. It discusses the physiological issues involved and how these issues have been handled in published cardiovascular models for simulation of orthostatic response. Most of the models are stimulus specific with no demonstrated capability for simulating the responses to orthostatic stimuli of different types. A comprehensive model incorporating all known phenomena related to cardiovascular regulation would greatly help to interpret the various orthostatic responses of the system in a consistent manner and to understand the interactions among its elements. This paper provides a framework for future efforts in mathematical modeling of the entire cardiovascular system.

On the deterministic and stochastic use of hydrologic models

USGS Publications Warehouse

Farmer, William H.; Vogel, Richard M.

2016-01-01

Environmental simulation models, such as precipitation-runoff watershed models, are increasingly used in a deterministic manner for environmental and water resources design, planning, and management. In operational hydrology, simulated responses are now routinely used to plan, design, and manage a very wide class of water resource systems. However, all such models are calibrated to existing data sets and retain some residual error. This residual, typically unknown in practice, is often ignored, implicitly trusting simulated responses as if they are deterministic quantities. In general, ignoring the residuals will result in simulated responses with distributional properties that do not mimic those of the observed responses. This discrepancy has major implications for the operational use of environmental simulation models as is shown here. Both a simple linear model and a distributed-parameter precipitation-runoff model are used to document the expected bias in the distributional properties of simulated responses when the residuals are ignored. The systematic reintroduction of residuals into simulated responses in a manner that produces stochastic output is shown to improve the distributional properties of the simulated responses. Every effort should be made to understand the distributional behavior of simulation residuals and to use environmental simulation models in a stochastic manner.

Fast and Slow Precipitation Responses to Individual Climate Forcers: A PDRMIP Multimodel Study

NASA Technical Reports Server (NTRS)

Samset, B. H.; Myhre, G.; Forster, P.M.; Hodnebrog, O.; Andrews, T.; Faluvegi, G.; Flaschner, D.; Kasoar, M.; Kharin, V.; Kirkevag, A.;

Limits on Log Cross-Product Ratios for Item Response Models. Research Report. ETS RR-06-10

ERIC Educational Resources Information Center

Haberman, Shelby J.; Holland, Paul W.; Sinharay, Sandip

2006-01-01

Bounds are established for log cross-product ratios (log odds ratios) involving pairs of items for item response models. First, expressions for bounds on log cross-product ratios are provided for unidimensional item response models in general. Then, explicit bounds are obtained for the Rasch model and the two-parameter logistic (2PL) model.…

Fitting a Mixture Item Response Theory Model to Personality Questionnaire Data: Characterizing Latent Classes and Investigating Possibilities for Improving Prediction

ERIC Educational Resources Information Center

Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk

2008-01-01

Mixture item response theory (IRT) models aid the interpretation of response behavior on personality tests and may provide possibilities for improving prediction. Heterogeneity in the population is modeled by identifying homogeneous subgroups that conform to different measurement models. In this study, mixture IRT models were applied to the…

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…

Linking an ecosystem model and a landscape model to study forest species response to climate warming

Treesearch

Hong S. He; David J. Mladenoff; Thomas R. Crow

1999-01-01

No single model can address forest change from single tree to regional scales. We discuss a framework linking an ecosystem process model {LINKAGES) with a spatial landscape model (LANDIS) to examine forest species responses to climate warming for a large, heterogeneous landscape in northern Wisconsin, USA. Individual species response at the ecosystem scale was...

Modeling Answer Change Behavior: An Application of a Generalized Item Response Tree Model

ERIC Educational Resources Information Center

Jeon, Minjeong; De Boeck, Paul; van der Linden, Wim

2017-01-01

We present a novel application of a generalized item response tree model to investigate test takers' answer change behavior. The model allows us to simultaneously model the observed patterns of the initial and final responses after an answer change as a function of a set of latent traits and item parameters. The proposed application is illustrated…

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.

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

PubMed

Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

2018-05-10

Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

Humanitarian response: improving logistics to save lives.

PubMed

McCoy, Jessica

2008-01-01

Each year, millions of people worldwide are affected by disasters, underscoring the importance of effective relief efforts. Many highly visible disaster responses have been inefficient and ineffective. Humanitarian agencies typically play a key role in disaster response (eg, procuring and distributing relief items to an affected population, assisting with evacuation, providing healthcare, assisting in the development of long-term shelter), and thus their efficiency is critical for a successful disaster response. The field of disaster and emergency response modeling is well established, but the application of such techniques to humanitarian logistics is relatively recent. This article surveys models of humanitarian response logistics and identifies promising opportunities for future work. Existing models analyze a variety of preparation and response decisions (eg, warehouse location and the distribution of relief supplies), consider both natural and manmade disasters, and typically seek to minimize cost or unmet demand. Opportunities to enhance the logistics of humanitarian response include the adaptation of models developed for general disaster response; the use of existing models, techniques, and insights from the literature on commercial supply chain management; the development of working partnerships between humanitarian aid organizations and private companies with expertise in logistics; and the consideration of behavioral factors relevant to a response. Implementable, realistic models that support the logistics of humanitarian relief can improve the preparation for and the response to disasters, which in turn can save lives.

Population activity statistics dissect subthreshold and spiking variability in V1.

PubMed

Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

2017-07-01

Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of variability. Our work shows that stimulus-dependent changes in pairwise but not in single-cell statistics can differentiate between two widely used models of neuronal variability. Contrasting model predictions with neuronal data provides hints on the noise sources in spiking and provides constraints on statistical models of population activity. Copyright © 2017 the American Physiological Society.

The development of a model of culturally responsive science and mathematics teaching

NASA Astrophysics Data System (ADS)

Hernandez, Cecilia M.; Morales, Amanda R.; Shroyer, M. Gail

2013-12-01

This qualitative theoretical study was conducted in response to the current need for an inclusive and comprehensive model to guide the preparation and assessment of teacher candidates for culturally responsive teaching. The process of developing a model of culturally responsive teaching involved three steps: a comprehensive review of the literature; a synthesis of the literature into thematic categories to capture the dispositions and behaviors of culturally responsive teaching; and the piloting of these thematic categories with teacher candidates to validate the usefulness of the categories and to generate specific exemplars of behavior to represent each category. The model of culturally responsive teaching contains five thematic categories: (1) content integration, (2) facilitating knowledge construction, (3) prejudice reduction, (4) social justice, and (5) academic development. The current model is a promising tool for comprehensively defining culturally responsive teaching in the context of teacher education as well as to guide curriculum and assessment changes aimed to increase candidates' culturally responsive knowledge and skills in science and mathematics teaching.

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.

Prediction of chemo-response in serous ovarian cancer.

PubMed

Gonzalez Bosquet, Jesus; Newtson, Andreea M; Chung, Rebecca K; Thiel, Kristina W; Ginader, Timothy; Goodheart, Michael J; Leslie, Kimberly K; Smith, Brian J

2016-10-19

Nearly one-third of serous ovarian cancer (OVCA) patients will not respond to initial treatment with surgery and chemotherapy and die within one year of diagnosis. If patients who are unlikely to respond to current standard therapy can be identified up front, enhanced tumor analyses and treatment regimens could potentially be offered. Using the Cancer Genome Atlas (TCGA) serous OVCA database, we previously identified a robust molecular signature of 422-genes associated with chemo-response. Our objective was to test whether this signature is an accurate and sensitive predictor of chemo-response in serous OVCA. We first constructed prediction models to predict chemo-response using our previously described 422-gene signature that was associated with response to treatment in serous OVCA. Performance of all prediction models were measured with area under the curves (AUCs, a measure of the model's accuracy) and their respective confidence intervals (CIs). To optimize the prediction process, we determined which elements of the signature most contributed to chemo-response prediction. All prediction models were replicated and validated using six publicly available independent gene expression datasets. The 422-gene signature prediction models predicted chemo-response with AUCs of ~70 %. Optimization of prediction models identified the 34 most important genes in chemo-response prediction. These 34-gene models had improved performance, with AUCs approaching 80 %. Both 422-gene and 34-gene prediction models were replicated and validated in six independent datasets. These prediction models serve as the foundation for the future development and implementation of a diagnostic tool to predict response to chemotherapy for serous OVCA patients.

Optimal plant nitrogen use improves model representation of vegetation response to elevated CO2

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Kern, Melanie; Engel, Jan; Zaehle, Sönke

2017-04-01

Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.

Incorporating Response Times in Item Response Theory Models of Reading Comprehension Fluency

ERIC Educational Resources Information Center

Su, Shiyang

2017-01-01

With the online assessment becoming mainstream and the recording of response times becoming straightforward, the importance of response times as a measure of psychological constructs has been recognized and the literature of modeling times has been growing during the last few decades. Previous studies have tried to formulate models and theories to…

Quantifying Local, Response Dependence between Two Polytomous Items Using the Rasch Model

ERIC Educational Resources Information Center

Andrich, David; Humphry, Stephen M.; Marais, Ida

2012-01-01

Models of modern test theory imply statistical independence among responses, generally referred to as "local independence." One violation of local independence occurs when the response to one item governs the response to a subsequent item. Expanding on a formulation of this kind of violation as a process in the dichotomous Rasch model,…

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…

Speed-Accuracy Response Models: Scoring Rules Based on Response Time and Accuracy

ERIC Educational Resources Information Center

Maris, Gunter; van der Maas, Han

2012-01-01

Starting from an explicit scoring rule for time limit tasks incorporating both response time and accuracy, and a definite trade-off between speed and accuracy, a response model is derived. Since the scoring rule is interpreted as a sufficient statistic, the model belongs to the exponential family. The various marginal and conditional distributions…

Evaluating Social Causality and Responsibility Models: An Initial Report

DTIC Science & Technology

2005-01-01

ICT Technical Report ICT-TR-03-2005 Evaluating Social Causality and Responsibility ... social intelligent agents. In this report, we present a general computational model of social causality and responsibility , and empirical results of...2005 to 00-00-2005 4. TITLE AND SUBTITLE Evaluating Social Causality and Responsibility Models: An Initial Report 5a. CONTRACT NUMBER 5b. GRANT

Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications.

PubMed

Liu, Xuejin; Persson, Mats; Bornefalk, Hans; Karlsson, Staffan; Xu, Cheng; Danielsson, Mats; Huber, Ben

2015-07-01

Variations among detector channels in computed tomography can lead to ring artifacts in the reconstructed images and biased estimates in projection-based material decomposition. Typically, the ring artifacts are corrected by compensation methods based on flat fielding, where transmission measurements are required for a number of material-thickness combinations. Phantoms used in these methods can be rather complex and require an extensive number of transmission measurements. Moreover, material decomposition needs knowledge of the individual response of each detector channel to account for the detector inhomogeneities. For this purpose, we have developed a spectral response model that binwise predicts the response of a multibin photon-counting detector individually for each detector channel. The spectral response model is performed in two steps. The first step employs a forward model to predict the expected numbers of photon counts, taking into account parameters such as the incident x-ray spectrum, absorption efficiency, and energy response of the detector. The second step utilizes a limited number of transmission measurements with a set of flat slabs of two absorber materials to fine-tune the model predictions, resulting in a good correspondence with the physical measurements. To verify the response model, we apply the model in two cases. First, the model is used in combination with a compensation method which requires an extensive number of transmission measurements to determine the necessary parameters. Our spectral response model successfully replaces these measurements by simulations, saving a significant amount of measurement time. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. The contrast agent concentrations are reconstructed with more than 94% accuracy.

Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications

PubMed Central

Liu, Xuejin; Persson, Mats; Bornefalk, Hans; Karlsson, Staffan; Xu, Cheng; Danielsson, Mats; Huber, Ben

2015-01-01

Abstract. Variations among detector channels in computed tomography can lead to ring artifacts in the reconstructed images and biased estimates in projection-based material decomposition. Typically, the ring artifacts are corrected by compensation methods based on flat fielding, where transmission measurements are required for a number of material-thickness combinations. Phantoms used in these methods can be rather complex and require an extensive number of transmission measurements. Moreover, material decomposition needs knowledge of the individual response of each detector channel to account for the detector inhomogeneities. For this purpose, we have developed a spectral response model that binwise predicts the response of a multibin photon-counting detector individually for each detector channel. The spectral response model is performed in two steps. The first step employs a forward model to predict the expected numbers of photon counts, taking into account parameters such as the incident x-ray spectrum, absorption efficiency, and energy response of the detector. The second step utilizes a limited number of transmission measurements with a set of flat slabs of two absorber materials to fine-tune the model predictions, resulting in a good correspondence with the physical measurements. To verify the response model, we apply the model in two cases. First, the model is used in combination with a compensation method which requires an extensive number of transmission measurements to determine the necessary parameters. Our spectral response model successfully replaces these measurements by simulations, saving a significant amount of measurement time. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. The contrast agent concentrations are reconstructed with more than 94% accuracy. PMID:26839904

SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model

NASA Astrophysics Data System (ADS)

Grelle, Gerardo; Bonito, Laura; Lampasi, Alessandro; Revellino, Paola; Guerriero, Luigi; Sappa, Giuseppe; Guadagno, Francesco Maria

2016-04-01

The SiSeRHMap (simulator for mapped seismic response using a hybrid model) is a computerized methodology capable of elaborating prediction maps of seismic response in terms of acceleration spectra. It was realized on the basis of a hybrid model which combines different approaches and models in a new and non-conventional way. These approaches and models are organized in a code architecture composed of five interdependent modules. A GIS (geographic information system) cubic model (GCM), which is a layered computational structure based on the concept of lithodynamic units and zones, aims at reproducing a parameterized layered subsoil model. A meta-modelling process confers a hybrid nature to the methodology. In this process, the one-dimensional (1-D) linear equivalent analysis produces acceleration response spectra for a specified number of site profiles using one or more input motions. The shear wave velocity-thickness profiles, defined as trainers, are randomly selected in each zone. Subsequently, a numerical adaptive simulation model (Emul-spectra) is optimized on the above trainer acceleration response spectra by means of a dedicated evolutionary algorithm (EA) and the Levenberg-Marquardt algorithm (LMA) as the final optimizer. In the final step, the GCM maps executor module produces a serial map set of a stratigraphic seismic response at different periods, grid solving the calibrated Emul-spectra model. In addition, the spectra topographic amplification is also computed by means of a 3-D validated numerical prediction model. This model is built to match the results of the numerical simulations related to isolate reliefs using GIS morphometric data. In this way, different sets of seismic response maps are developed on which maps of design acceleration response spectra are also defined by means of an enveloping technique.

The Simplest Complete Model of Choice Response Time: Linear Ballistic Accumulation

ERIC Educational Resources Information Center

Brown, Scott D.; Heathcote, Andrew

2008-01-01

We propose a linear ballistic accumulator (LBA) model of decision making and reaction time. The LBA is simpler than other models of choice response time, with independent accumulators that race towards a common response threshold. Activity in the accumulators increases in a linear and deterministic manner. The simplicity of the model allows…

Hierarchical Diffusion Models for Two-Choice Response Times

ERIC Educational Resources Information Center

Vandekerckhove, Joachim; Tuerlinckx, Francis; Lee, Michael D.

2011-01-01

Two-choice response times are a common type of data, and much research has been devoted to the development of process models for such data. However, the practical application of these models is notoriously complicated, and flexible methods are largely nonexistent. We combine a popular model for choice response times--the Wiener diffusion…

Applying the age-shift approach to model responses to midrotation fertilization

Treesearch

Colleen A. Carlson; Thomas R. Fox; H. Lee Allen; Timothy J. Albaugh

2010-01-01

Growth and yield models used to evaluate midrotation fertilization economics require adjustments to account for the typically observed responses. This study investigated the use of age-shift models to predict midrotation fertilizer responses. Age-shift prediction models were constructed from a regional study consisting of 43 installations of a nitrogen (N) by...

The Impact of Truth Surrogate Variance on Quality Assessment/Assurance in Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2016-01-01

Minimum data volume requirements for wind tunnel testing are reviewed and shown to depend on error tolerance, response model complexity, random error variance in the measurement environment, and maximum acceptable levels of inference error risk. Distinctions are made between such related concepts as quality assurance and quality assessment in response surface modeling, as well as between precision and accuracy. Earlier research on the scaling of wind tunnel tests is extended to account for variance in the truth surrogates used at confirmation sites in the design space to validate proposed response models. A model adequacy metric is presented that represents the fraction of the design space within which model predictions can be expected to satisfy prescribed quality specifications. The impact of inference error on the assessment of response model residuals is reviewed. The number of sites where reasonably well-fitted response models actually predict inadequately is shown to be considerably less than the number of sites where residuals are out of tolerance. The significance of such inference error effects on common response model assessment strategies is examined.

Model-experiment synthesis at two FACE sites in the southeastern US. Forest ecosystem responses to elevated CO[2]. (Invited)

NASA Astrophysics Data System (ADS)

Walker, A. P.; Zaehle, S.; De Kauwe, M. G.; Medlyn, B. E.; Dietze, M.; Hickler, T.; Iversen, C. M.; Jain, A. K.; Luo, Y.; McCarthy, H. R.; Parton, W. J.; Prentice, C.; Thornton, P. E.; Wang, S.; Wang, Y.; Warlind, D.; Warren, J.; Weng, E.; Hanson, P. J.; Oren, R.; Norby, R. J.

2013-12-01

Ecosystem observations from two long-term Free-Air CO[2] Enrichment (FACE) experiments (Duke forest and Oak Ridge forest) were used to evaluate the assumptions of 11 terrestrial ecosystem models and the consequences of those assumptions for the responses of ecosystem water, carbon (C) and nitrogen (N) fluxes to elevated CO[2] (eCO[2]). Nitrogen dynamics were the main constraint on simulated productivity responses to eCO[2]. At Oak Ridge some models reproduced the declining response of C and N fluxes, while at Duke none of the models were able to maintain the observed sustained responses. C and N cycles are coupled through a number of complex interactions, which causes uncertainty in model simulations in multiple ways. Nonetheless, the major difference between models and experiments was a larger than observed increase in N-use efficiency and lower than observed response of N uptake. The results indicate that at Duke there were mechanisms by which trees accessed additional N in response to eCO[2] that were not represented in the ecosystem models, and which did not operate with the same efficiency at Oak Ridge. Sequestration of the additional productivity under eCO[2] into forest biomass depended largely on C allocation. Allocation assumptions were classified into three main categories--fixed partitioning coefficients, functional relationships and a partial (leaf allocation only) optimisation. The assumption which best constrained model results was a functional relationship between leaf area and sapwood area (pipe-model) and increased root allocation when nitrogen or water were limiting. Both, productivity and allocation responses to eCO[2] determined the ecosystem-level response of LAI, which together with the response of stomatal conductance (and hence water-use efficiency; WUE) determined the ecosystem response of transpiration. Differences in the WUE response across models were related to the representation of the relationship of stomatal conductance to CO[2] and the relative importance of the combined boundary and aerodynamic resistances in the total resistance to leaf-atmosphere water transport.

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).

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.

Item response theory and structural equation modelling for ordinal data: Describing the relationship between KIDSCREEN and Life-H.

PubMed

Titman, Andrew C; Lancaster, Gillian A; Colver, Allan F

2016-10-01

Both item response theory and structural equation models are useful in the analysis of ordered categorical responses from health assessment questionnaires. We highlight the advantages and disadvantages of the item response theory and structural equation modelling approaches to modelling ordinal data, from within a community health setting. Using data from the SPARCLE project focussing on children with cerebral palsy, this paper investigates the relationship between two ordinal rating scales, the KIDSCREEN, which measures quality-of-life, and Life-H, which measures participation. Practical issues relating to fitting models, such as non-positive definite observed or fitted correlation matrices, and approaches to assessing model fit are discussed. item response theory models allow properties such as the conditional independence of particular domains of a measurement instrument to be assessed. When, as with the SPARCLE data, the latent traits are multidimensional, structural equation models generally provide a much more convenient modelling framework. © The Author(s) 2013.

Modeled responses of terrestrial ecosystems to elevated atmospheric CO2: a comparison of simulations by the biogeochemistry models of the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP).

PubMed

Pan, Yude; Melillo, Jerry M; McGuire, A David; Kicklighter, David W; Pitelka, Louis F; Hibbard, Kathy; Pierce, Lars L; Running, Steven W; Ojima, Dennis S; Parton, William J; Schimel, David S

1998-04-01

Although there is a great deal of information concerning responses to increases in atmospheric CO 2 at the tissue and plant levels, there are substantially fewer studies that have investigated ecosystem-level responses in the context of integrated carbon, water, and nutrient cycles. Because our understanding of ecosystem responses to elevated CO 2 is incomplete, modeling is a tool that can be used to investigate the role of plant and soil interactions in the response of terrestrial ecosystems to elevated CO 2 . In this study, we analyze the responses of net primary production (NPP) to doubled CO 2 from 355 to 710 ppmv among three biogeochemistry models in the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP): BIOME-BGC (BioGeochemical Cycles), Century, and the Terrestrial Ecosystem Model (TEM). For the conterminous United States, doubled atmospheric CO 2 causes NPP to increase by 5% in Century, 8% in TEM, and 11% in BIOME-BGC. Multiple regression analyses between the NPP response to doubled CO 2 and the mean annual temperature and annual precipitation of biomes or grid cells indicate that there are negative relationships between precipitation and the response of NPP to doubled CO 2 for all three models. In contrast, there are different relationships between temperature and the response of NPP to doubled CO 2 for the three models: there is a negative relationship in the responses of BIOME-BGC, no relationship in the responses of Century, and a positive relationship in the responses of TEM. In BIOME-BGC, the NPP response to doubled CO 2 is controlled by the change in transpiration associated with reduced leaf conductance to water vapor. This change affects soil water, then leaf area development and, finally, NPP. In Century, the response of NPP to doubled CO 2 is controlled by changes in decomposition rates associated with increased soil moisture that results from reduced evapotranspiration. This change affects nitrogen availability for plants, which influences NPP. In TEM, the NPP response to doubled CO 2 is controlled by increased carboxylation which is modified by canopy conductance and the degree to which nitrogen constraints cause down-regulation of photosynthesis. The implementation of these different mechanisms has consequences for the spatial pattern of NPP responses, and represents, in part, conceptual uncertainty about controls over NPP responses. Progress in reducing these uncertainties requires research focused at the ecosystem level to understand how interactions between the carbon, nitrogen, and water cycles influence the response of NPP to elevated atmospheric CO 2 .

Modeled responses of terrestrial ecosystems to elevated atmospheric CO2: A comparison of simulations by the biogeochemistry models of the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP)

USGS Publications Warehouse

Pan, Y.; Melillo, J.M.; McGuire, A.D.; Kicklighter, D.W.; Pitelka, Louis F.; Hibbard, K.; Pierce, L.L.; Running, S.W.; Ojima, D.S.; Parton, W.J.; Schimel, D.S.; Borchers, J.; Neilson, R.; Fisher, H.H.; Kittel, T.G.F.; Rossenbloom, N.A.; Fox, S.; Haxeltine, A.; Prentice, I.C.; Sitch, S.; Janetos, A.; McKeown, R.; Nemani, R.; Painter, T.; Rizzo, B.; Smith, T.; Woodward, F.I.

1998-01-01

Although there is a great deal of information concerning responses to increases in atmospheric CO2 at the tissue and plant levels, there are substantially fewer studies that have investigated ecosystem-level responses in the context of integrated carbon, water, and nutrient cycles. Because our understanding of ecosystem responses to elevated CO2 is incomplete, modeling is a tool that can be used to investigate the role of plant and soil interactions in the response of terrestrial ecosystems to elevated CO2. In this study, we analyze the responses of net primary production (NPP) to doubled CO2 from 355 to 710 ppmv among three biogeochemistry models in the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP): BIOME-BGC (BioGeochemical Cycles), Century, and the Terrestrial Ecosystem Model (TEM). For the conterminous United States, doubled atmospheric CO2 causes NPP to increase by 5% in Century, 8% in TEM, and 11% in BIOME-BGC. Multiple regression analyses between the NPP response to doubled CO2 and the mean annual temperature and annual precipitation of biomes or grid cells indicate that there are negative relationships between precipitation and the response of NPP to doubled CO2 for all three models. In contrast, there are different relationships between temperature and the response of NPP to doubled CO2 for the three models: there is a negative relationship in the responses of BIOME-BGC, no relationship in the responses of Century, and a positive relationship in the responses of TEM. In BIOME-BGC, the NPP response to doubled CO2 is controlled by the change in transpiration associated with reduced leaf conductance to water vapor. This change affects soil water, then leaf area development and, finally, NPP. In Century, the response of NPP to doubled CO2 is controlled by changes in decomposition rates associated with increased soil moisture that results from reduced evapotranspiration. This change affects nitrogen availability for plants, which influences NPP. In TEM, the NPP response to doubled CO2 is controlled by increased carboxylation which is modified by canopy conductance and the degree to which nitrogen constraints cause down-regulation of photosynthesis. The implementation of these different mechanisms has consequences for the spatial pattern of NPP responses, and represents, in part, conceptual uncertainty about controls over NPP responses. Progress in reducing these uncertainties requires research focused at the ecosystem level to understand how interactions between the carbon, nitrogen, and water cycles influence the response of NPP to elevated atmospheric CO2.

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.

Bayesian multimodel inference for dose-response studies

USGS Publications Warehouse

Link, W.A.; Albers, P.H.

2007-01-01

Statistical inference in dose?response studies is model-based: The analyst posits a mathematical model of the relation between exposure and response, estimates parameters of the model, and reports conclusions conditional on the model. Such analyses rarely include any accounting for the uncertainties associated with model selection. The Bayesian inferential system provides a convenient framework for model selection and multimodel inference. In this paper we briefly describe the Bayesian paradigm and Bayesian multimodel inference. We then present a family of models for multinomial dose?response data and apply Bayesian multimodel inferential methods to the analysis of data on the reproductive success of American kestrels (Falco sparveriuss) exposed to various sublethal dietary concentrations of methylmercury.

Cognitive Psychology Meets Psychometric Theory: On the Relation between Process Models for Decision Making and Latent Variable Models for Individual Differences

ERIC Educational Resources Information Center

van der Maas, Han L. J.; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A.; Borsboom, Denny

2011-01-01

This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line…

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

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

Thomas, Edward V.; Lewis, John. R.; Anderson-Cook, Christine Michaela

The inverse prediction is important in a variety of scientific and engineering applications, such as to predict properties/characteristics of an object by using multiple measurements obtained from it. Inverse prediction can be accomplished by inverting parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are computational/science based; but often, forward models are empirically based response surface models, obtained by using the results of controlled experimentation. For empirical models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). And while nature dictatesmore » the causal relationships between factors and responses, experimenters can control the complexity, accuracy, and precision of forward models constructed via selection of factors, factor levels, and the set of trials that are performed. Recognition of the uncertainty in the estimated forward models leads to an errors-in-variables approach for inverse prediction. The forward models (estimated by experiments or science based) can also be used to analyze how well candidate responses complement one another for inverse prediction over the range of the factor space of interest. Furthermore, one may find that some responses are complementary, redundant, or noninformative. Simple analysis and examples illustrate how an informative and discriminating subset of responses could be selected among candidates in cases where the number of responses that can be acquired during inverse prediction is limited by difficulty, expense, and/or availability of material.« less

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.

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

DOE PAGES

Thomas, Edward V.; Lewis, John. R.; Anderson-Cook, Christine Michaela; ...

2017-07-01

The inverse prediction is important in a variety of scientific and engineering applications, such as to predict properties/characteristics of an object by using multiple measurements obtained from it. Inverse prediction can be accomplished by inverting parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are computational/science based; but often, forward models are empirically based response surface models, obtained by using the results of controlled experimentation. For empirical models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). And while nature dictatesmore » the causal relationships between factors and responses, experimenters can control the complexity, accuracy, and precision of forward models constructed via selection of factors, factor levels, and the set of trials that are performed. Recognition of the uncertainty in the estimated forward models leads to an errors-in-variables approach for inverse prediction. The forward models (estimated by experiments or science based) can also be used to analyze how well candidate responses complement one another for inverse prediction over the range of the factor space of interest. Furthermore, one may find that some responses are complementary, redundant, or noninformative. Simple analysis and examples illustrate how an informative and discriminating subset of responses could be selected among candidates in cases where the number of responses that can be acquired during inverse prediction is limited by difficulty, expense, and/or availability of material.« less

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 development of a fully-integrated immune response model (FIRM) simulator of the immune response through integration of multiple subset models

PubMed Central

2013-01-01

Background The complexity and multiscale nature of the mammalian immune response provides an excellent test bed for the potential of mathematical modeling and simulation to facilitate mechanistic understanding. Historically, mathematical models of the immune response focused on subsets of the immune system and/or specific aspects of the response. Mathematical models have been developed for the humoral side of the immune response, or for the cellular side, or for cytokine kinetics, but rarely have they been proposed to encompass the overall system complexity. We propose here a framework for integration of subset models, based on a system biology approach. Results A dynamic simulator, the Fully-integrated Immune Response Model (FIRM), was built in a stepwise fashion by integrating published subset models and adding novel features. The approach used to build the model includes the formulation of the network of interacting species and the subsequent introduction of rate laws to describe each biological process. The resulting model represents a multi-organ structure, comprised of the target organ where the immune response takes place, circulating blood, lymphoid T, and lymphoid B tissue. The cell types accounted for include macrophages, a few T-cell lineages (cytotoxic, regulatory, helper 1, and helper 2), and B-cell activation to plasma cells. Four different cytokines were accounted for: IFN-γ, IL-4, IL-10 and IL-12. In addition, generic inflammatory signals are used to represent the kinetics of IL-1, IL-2, and TGF-β. Cell recruitment, differentiation, replication, apoptosis and migration are described as appropriate for the different cell types. The model is a hybrid structure containing information from several mammalian species. The structure of the network was built to be physiologically and biochemically consistent. Rate laws for all the cellular fate processes, growth factor production rates and half-lives, together with antibody production rates and half-lives, are provided. The results demonstrate how this framework can be used to integrate mathematical models of the immune response from several published sources and describe qualitative predictions of global immune system response arising from the integrated, hybrid model. In addition, we show how the model can be expanded to include novel biological findings. Case studies were carried out to simulate TB infection, tumor rejection, response to a blood borne pathogen and the consequences of accounting for regulatory T-cells. Conclusions The final result of this work is a postulated and increasingly comprehensive representation of the mammalian immune system, based on physiological knowledge and susceptible to further experimental testing and validation. We believe that the integrated nature of FIRM has the potential to simulate a range of responses under a variety of conditions, from modeling of immune responses after tuberculosis (TB) infection to tumor formation in tissues. FIRM also has the flexibility to be expanded to include both complex and novel immunological response features as our knowledge of the immune system advances. PMID:24074340

Comparison between a typical and a simplified model for blast load-induced structural response

NASA Astrophysics Data System (ADS)

Abd-Elhamed, A.; Mahmoud, S.

2017-02-01

As explosive blasts continue to cause severe damage as well as victims in both civil and military environments. There is a bad need for understanding the behavior of structural elements to such extremely short duration dynamic loads where it is of great concern nowadays. Due to the complexity of the typical blast pressure profile model and in order to reduce the modelling and computational efforts, the simplified triangle model for blast loads profile is used to analyze structural response. This simplified model considers only the positive phase and ignores the suction phase which characterizes the typical one in simulating blast loads. The closed from solution for the equation of motion under blast load as a forcing term modelled either typical or simplified models has been derived. The considered herein two approaches have been compared using the obtained results from simulation response analysis of a building structure under an applied blast load. The computed error in simulating response using the simplified model with respect to the typical one has been computed. In general, both simplified and typical models can perform the dynamic blast-load induced response of building structures. However, the simplified one shows a remarkably different response behavior as compared to the typical one despite its simplicity and the use of only positive phase for simulating the explosive loads. The prediction of the dynamic system responses using the simplified model is not satisfactory due to the obtained larger errors as compared to the system responses obtained using the typical one.

Responses to atmospheric CO2 concentrations in crop simulation models: a review of current simple and semicomplex representations and options for model development.

PubMed

Vanuytrecht, Eline; Thorburn, Peter J

2017-05-01

Elevated atmospheric CO 2 concentrations ([CO 2 ]) cause direct changes in crop physiological processes (e.g. photosynthesis and stomatal conductance). To represent these CO 2 responses, commonly used crop simulation models have been amended, using simple and semicomplex representations of the processes involved. Yet, there is no standard approach to and often poor documentation of these developments. This study used a bottom-up approach (starting with the APSIM framework as case study) to evaluate modelled responses in a consortium of commonly used crop models and illuminate whether variation in responses reflects true uncertainty in our understanding compared to arbitrary choices of model developers. Diversity in simulated CO 2 responses and limited validation were common among models, both within the APSIM framework and more generally. Whereas production responses show some consistency up to moderately high [CO 2 ] (around 700 ppm), transpiration and stomatal responses vary more widely in nature and magnitude (e.g. a decrease in stomatal conductance varying between 35% and 90% among models was found for [CO 2 ] doubling to 700 ppm). Most notably, nitrogen responses were found to be included in few crop models despite being commonly observed and critical for the simulation of photosynthetic acclimation, crop nutritional quality and carbon allocation. We suggest harmonization and consideration of more mechanistic concepts in particular subroutines, for example, for the simulation of N dynamics, as a way to improve our predictive understanding of CO 2 responses and capture secondary processes. Intercomparison studies could assist in this aim, provided that they go beyond simple output comparison and explicitly identify the representations and assumptions that are causal for intermodel differences. Additionally, validation and proper documentation of the representation of CO 2 responses within models should be prioritized. © 2017 John Wiley & Sons Ltd.

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

A Multidimensional Ideal Point Item Response Theory Model for Binary Data

ERIC Educational Resources Information Center

Maydeu-Olivares, Albert; Hernandez, Adolfo; McDonald, Roderick P.

2006-01-01

We introduce a multidimensional item response theory (IRT) model for binary data based on a proximity response mechanism. Under the model, a respondent at the mode of the item response function (IRF) endorses the item with probability one. The mode of the IRF is the ideal point, or in the multidimensional case, an ideal hyperplane. The model…

Analytical approach to calculation of response spectra from seismological models of ground motion

USGS Publications Warehouse

Safak, Erdal

1988-01-01

An analytical approach to calculate response spectra from seismological models of ground motion is presented. Seismological models have three major advantages over empirical models: (1) they help in an understanding of the physics of earthquake mechanisms, (2) they can be used to predict ground motions for future earthquakes and (3) they can be extrapolated to cases where there are no data available. As shown with this study, these models also present a convenient form for the calculation of response spectra, by using the methods of random vibration theory, for a given magnitude and site conditions. The first part of the paper reviews the past models for ground motion description, and introduces the available seismological models. Then, the random vibration equations for the spectral response are presented. The nonstationarity, spectral bandwidth and the correlation of the peaks are considered in the calculation of the peak response.

Development of structural and material clavicle response corridors under axial compression and three point bending loading for clavicle finite element model validation.

PubMed

Zhang, Qi; Kindig, Matthew; Li, Zuoping; Crandall, Jeff R; Kerrigan, Jason R

2014-08-22

Clavicle injuries were frequently observed in automotive side and frontal crashes. Finite element (FE) models have been developed to understand the injury mechanism, although no clavicle loading response corridors yet exist in the literature to ensure the model response biofidelity. Moreover, the typically developed structural level (e.g., force-deflection) response corridors were shown to be insufficient for verifying the injury prediction capacity of FE model, which usually is based on strain related injury criteria. Therefore, the purpose of this study is to develop both the structural (force vs deflection) and material level (strain vs force) clavicle response corridors for validating FE models for injury risk modeling. 20 Clavicles were loaded to failure under loading conditions representative of side and frontal crashes respectively, half of which in axial compression, and the other half in three point bending. Both structural and material response corridors were developed for each loading condition. FE model that can accurately predict structural response and strain level provides a more useful tool in injury risk modeling and prediction. The corridor development method in this study could also be extended to develop corridors for other components of the human body. Copyright © 2014 Elsevier Ltd. All rights reserved.

Solar Signals in CMIP-5 Simulations: The Stratospheric Pathway

NASA Technical Reports Server (NTRS)

Mitchell, D.M.; Misios, S.; Gray, L. J.; Tourpali, K.; Matthes, K.; Hood, L.; Schmidt, H.; Chiodo, G.; Thieblemont, R.; Rozanov, E.;

The Graded Unfolding Model: A Unidimensional Item Response Model for Unfolding Graded Responses.

ERIC Educational Resources Information Center

Roberts, James S.; Laughlin, James E.

Binary or graded disagree-agree responses to attitude items are often collected for the purpose of attitude measurement. Although such data are sometimes analyzed with cumulative measurement models, recent investigations suggest that unfolding models are more appropriate (J. S. Roberts, 1995; W. H. Van Schuur and H. A. L. Kiers, 1994). Advances in…

Stochastic Approximation Methods for Latent Regression Item Response Models. Research Report. ETS RR-09-09

ERIC Educational Resources Information Center

von Davier, Matthias; Sinharay, Sandip

2009-01-01

This paper presents an application of a stochastic approximation EM-algorithm using a Metropolis-Hastings sampler to estimate the parameters of an item response latent regression model. Latent regression models are extensions of item response theory (IRT) to a 2-level latent variable model in which covariates serve as predictors of the…

An Estimation Procedure for the Structural Parameters of the Unified Cognitive/IRT Model.

ERIC Educational Resources Information Center

Jiang, Hai; And Others

L. V. DiBello, W. F. Stout, and L. A. Roussos (1993) have developed a new item response model, the Unified Model, which brings together the discrete, deterministic aspects of cognition favored by cognitive scientists, and the continuous, stochastic aspects of test response behavior that underlie item response theory (IRT). The Unified Model blends…

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

Equilibrium Atmospheric Response to North Atlantic SST Anomalies.

NASA Astrophysics Data System (ADS)

Kushnir, Yochanan; Held, Isaac M.

1996-06-01

The equilibrium general circulation model (GCM) response to sea surface temperature (SST) anomalies in the western North Atlantic region is studied. A coarse resolution GCM, with realistic lower boundary conditions including topography and climatological SST distribution, is integrated in perpetual January and perpetual October modes, distinguished from one another by the strength of the midlatitude westerlies. An SST anomaly with a maximum of 4°C is added to the climatological SST distribution of the model with both positive and negative polarity. These anomaly runs are compared to one another, and to a control integration, to determine the atmospheric response. In all cases warming (cooling) of the midlatitude ocean surface yields a warming (cooling) of the atmosphere over and to the east of the SST anomaly center. The atmospheric temperature change is largest near the surface and decreases upward. Consistent with this simple thermal response, the geopotential height field displays a baroclinic response with a shallow anomalous low somewhat downstream from the warm SST anomaly. The equivalent barotropic, downstream response is weak and not robust. To help interpret the results, the realistic GCM integrations are compared with parallel idealized model runs. The idealized model has full physics and a similar horizontal and vertical resolution, but an all-ocean surface with a single, permanent zonal asymmetry. The idealized and realistic versions of the GCM display compatible response patterns that are qualitatively consistent with stationary, linear, quasigeostrophic theory. However, the idealized model response is stronger and more coherent. The differences between the two model response patterns can be reconciled based on the size of the anomaly, the model treatment of cloud-radiation interaction, and the static stability of the model atmosphere in the vicinity of the SST anomaly. Model results are contrasted with other GCM studies and observations.

Calibration Designs for Non-Monolithic Wind Tunnel Force Balances

NASA Technical Reports Server (NTRS)

Johnson, Thomas H.; Parker, Peter A.; Landman, Drew

2010-01-01

This research paper investigates current experimental designs and regression models for calibrating internal wind tunnel force balances of non-monolithic design. Such calibration methods are necessary for this class of balance because it has an electrical response that is dependent upon the sign of the applied forces and moments. This dependency gives rise to discontinuities in the response surfaces that are not easily modeled using traditional response surface methodologies. An analysis of current recommended calibration models is shown to lead to correlated response model terms. Alternative modeling methods are explored which feature orthogonal or near-orthogonal terms.

Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses

NASA Astrophysics Data System (ADS)

Rowland, L.; Harper, A.; Christoffersen, B. O.; Galbraith, D. R.; Imbuzeiro, H. M. A.; Powell, T. L.; Doughty, C.; Levine, N. M.; Malhi, Y.; Saleska, S. R.; Moorcroft, P. R.; Meir, P.; Williams, M.

2015-04-01

Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model - CLM3.5-DGVM; Ecosystem Demography model version 2 - ED2; the Joint UK Land Environment Simulator version 2.1 - JULES; Simple Biosphere model version 3 - SiB3; and the soil-plant-atmosphere model - SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model-data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in An with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest that even up to fairly extreme temperature increases from ambient levels (+6 °C), simulated photosynthesis becomes increasingly sensitive to gs and remains less sensitive to biochemical changes. To improve the reliability of simulations of the response of Amazonian rainforest to climate change, the mechanistic underpinnings of vegetation models need to be validated at both leaf- and canopy-scales to improve accuracy and consistency in the quantification of processes within and across an ecosystem.

Predictive Ensemble Decoding of Acoustical Features Explains Context-Dependent Receptive Fields.

PubMed

Yildiz, Izzet B; Mesgarani, Nima; Deneve, Sophie

2016-12-07

A primary goal of auditory neuroscience is to identify the sound features extracted and represented by auditory neurons. Linear encoding models, which describe neural responses as a function of the stimulus, have been primarily used for this purpose. Here, we provide theoretical arguments and experimental evidence in support of an alternative approach, based on decoding the stimulus from the neural response. We used a Bayesian normative approach to predict the responses of neurons detecting relevant auditory features, despite ambiguities and noise. We compared the model predictions to recordings from the primary auditory cortex of ferrets and found that: (1) the decoding filters of auditory neurons resemble the filters learned from the statistics of speech sounds; (2) the decoding model captures the dynamics of responses better than a linear encoding model of similar complexity; and (3) the decoding model accounts for the accuracy with which the stimulus is represented in neural activity, whereas linear encoding model performs very poorly. Most importantly, our model predicts that neuronal responses are fundamentally shaped by "explaining away," a divisive competition between alternative interpretations of the auditory scene. Neural responses in the auditory cortex are dynamic, nonlinear, and hard to predict. Traditionally, encoding models have been used to describe neural responses as a function of the stimulus. However, in addition to external stimulation, neural activity is strongly modulated by the responses of other neurons in the network. We hypothesized that auditory neurons aim to collectively decode their stimulus. In particular, a stimulus feature that is decoded (or explained away) by one neuron is not explained by another. We demonstrated that this novel Bayesian decoding model is better at capturing the dynamic responses of cortical neurons in ferrets. Whereas the linear encoding model poorly reflects selectivity of neurons, the decoding model can account for the strong nonlinearities observed in neural data. Copyright © 2016 Yildiz et al.

Robust Estimation of Latent Ability in Item Response Models

ERIC Educational Resources Information Center

Schuster, Christof; Yuan, Ke-Hai

2011-01-01

Because of response disturbances such as guessing, cheating, or carelessness, item response models often can only approximate the "true" individual response probabilities. As a consequence, maximum-likelihood estimates of ability will be biased. Typically, the nature and extent to which response disturbances are present is unknown, and, therefore,…

Optimal Linking Design for Response Model Parameters

ERIC Educational Resources Information Center

Barrett, Michelle D.; van der Linden, Wim J.

2017-01-01

Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…

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.

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.

A linear model fails to predict orientation selectivity of cells in the cat visual cortex.

PubMed Central

Volgushev, M; Vidyasagar, T R; Pei, X

1996-01-01

1. Postsynaptic potentials (PSPs) evoked by visual stimulation in simple cells in the cat visual cortex were recorded using in vivo whole-cell technique. Responses to small spots of light presented at different positions over the receptive field and responses to elongated bars of different orientations centred on the receptive field were recorded. 2. To test whether a linear model can account for orientation selectivity of cortical neurones, responses to elongated bars were compared with responses predicted by a linear model from the receptive field map obtained from flashing spots. 3. The linear model faithfully predicted the preferred orientation, but not the degree of orientation selectivity or the sharpness of orientation tuning. The ratio of optimal to non-optimal responses was always underestimated by the model. 4. Thus non-linear mechanisms, which can include suppression of non-optimal responses and/or amplification of optimal responses, are involved in the generation of orientation selectivity in the primary visual cortex. PMID:8930828

A Generalized QMRA Beta-Poisson Dose-Response Model.

PubMed

Xie, Gang; Roiko, Anne; Stratton, Helen; Lemckert, Charles; Dunn, Peter K; Mengersen, Kerrie

2016-10-01

Quantitative microbial risk assessment (QMRA) is widely accepted for characterizing the microbial risks associated with food, water, and wastewater. Single-hit dose-response models are the most commonly used dose-response models in QMRA. Denoting PI(d) as the probability of infection at a given mean dose d, a three-parameter generalized QMRA beta-Poisson dose-response model, PI(d|α,β,r*), is proposed in which the minimum number of organisms required for causing infection, K min , is not fixed, but a random variable following a geometric distribution with parameter 0

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.

Improved system identification using artificial neural networks and analysis of individual differences in responses of an identified neuron.

PubMed

Costalago Meruelo, Alicia; Simpson, David M; Veres, Sandor M; Newland, Philip L

2016-03-01

Mathematical modelling is used routinely to understand the coding properties and dynamics of responses of neurons and neural networks. Here we analyse the effectiveness of Artificial Neural Networks (ANNs) as a modelling tool for motor neuron responses. We used ANNs to model the synaptic responses of an identified motor neuron, the fast extensor motor neuron, of the desert locust in response to displacement of a sensory organ, the femoral chordotonal organ, which monitors movements of the tibia relative to the femur of the leg. The aim of the study was threefold: first to determine the potential value of ANNs as tools to model and investigate neural networks, second to understand the generalisation properties of ANNs across individuals and to different input signals and third, to understand individual differences in responses of an identified neuron. A metaheuristic algorithm was developed to design the ANN architectures. The performance of the models generated by the ANNs was compared with those generated through previous mathematical models of the same neuron. The results suggest that ANNs are significantly better than LNL and Wiener models in predicting specific neural responses to Gaussian White Noise, but not significantly different when tested with sinusoidal inputs. They are also able to predict responses of the same neuron in different individuals irrespective of which animal was used to develop the model, although notable differences between some individuals were evident. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Development of Web-based Graphical User Interface for Unified Modeling Data with Multi (Correlated) Responses

NASA Astrophysics Data System (ADS)

Made Tirta, I.; Anggraeni, Dian

2018-04-01

Statistical models have been developed rapidly into various directions to accommodate various types of data. Data collected from longitudinal, repeated measured, clustered data (either continuous, binary, count, or ordinal), are more likely to be correlated. Therefore statistical model for independent responses, such as Generalized Linear Model (GLM), Generalized Additive Model (GAM) are not appropriate. There are several models available to apply for correlated responses including GEEs (Generalized Estimating Equations), for marginal model and various mixed effect model such as GLMM (Generalized Linear Mixed Models) and HGLM (Hierarchical Generalized Linear Models) for subject spesific models. These models are available on free open source software R, but they can only be accessed through command line interface (using scrit). On the othe hand, most practical researchers very much rely on menu based or Graphical User Interface (GUI). We develop, using Shiny framework, standard pull down menu Web-GUI that unifies most models for correlated responses. The Web-GUI has accomodated almost all needed features. It enables users to do and compare various modeling for repeated measure data (GEE, GLMM, HGLM, GEE for nominal responses) much more easily trough online menus. This paper discusses the features of the Web-GUI and illustrates the use of them. In General we find that GEE, GLMM, HGLM gave very closed results.

A comparison of item response models for accuracy and speed of item responses with applications to adaptive testing.

PubMed

van Rijn, Peter W; Ali, Usama S

2017-05-01

We compare three modelling frameworks for accuracy and speed of item responses in the context of adaptive testing. The first framework is based on modelling scores that result from a scoring rule that incorporates both accuracy and speed. The second framework is the hierarchical modelling approach developed by van der Linden (2007, Psychometrika, 72, 287) in which a regular item response model is specified for accuracy and a log-normal model for speed. The third framework is the diffusion framework in which the response is assumed to be the result of a Wiener process. Although the three frameworks differ in the relation between accuracy and speed, one commonality is that the marginal model for accuracy can be simplified to the two-parameter logistic model. We discuss both conditional and marginal estimation of model parameters. Models from all three frameworks were fitted to data from a mathematics and spelling test. Furthermore, we applied a linear and adaptive testing mode to the data off-line in order to determine differences between modelling frameworks. It was found that a model from the scoring rule framework outperformed a hierarchical model in terms of model-based reliability, but the results were mixed with respect to correlations with external measures. © 2017 The British Psychological Society.

Climate Change: Modeling the Human Response

NASA Astrophysics Data System (ADS)

Oppenheimer, M.; Hsiang, S. M.; Kopp, R. E.

2012-12-01

Integrated assessment models have historically relied on forward modeling including, where possible, process-based representations to project climate change impacts. Some recent impact studies incorporate the effects of human responses to initial physical impacts, such as adaptation in agricultural systems, migration in response to drought, and climate-related changes in worker productivity. Sometimes the human response ameliorates the initial physical impacts, sometimes it aggravates it, and sometimes it displaces it onto others. In these arenas, understanding of underlying socioeconomic mechanisms is extremely limited. Consequently, for some sectors where sufficient data has accumulated, empirically based statistical models of human responses to past climate variability and change have been used to infer response sensitivities which may apply under certain conditions to future impacts, allowing a broad extension of integrated assessment into the realm of human adaptation. We discuss the insights gained from and limitations of such modeling for benefit-cost analysis of climate change.

System level analysis and control of manufacturing process variation

DOEpatents

Hamada, Michael S.; Martz, Harry F.; Eleswarpu, Jay K.; Preissler, Michael J.

2005-05-31

A computer-implemented method is implemented for determining the variability of a manufacturing system having a plurality of subsystems. Each subsystem of the plurality of subsystems is characterized by signal factors, noise factors, control factors, and an output response, all having mean and variance values. Response models are then fitted to each subsystem to determine unknown coefficients for use in the response models that characterize the relationship between the signal factors, noise factors, control factors, and the corresponding output response having mean and variance values that are related to the signal factors, noise factors, and control factors. The response models for each subsystem are coupled to model the output of the manufacturing system as a whole. The coefficients of the fitted response models are randomly varied to propagate variances through the plurality of subsystems and values of signal factors and control factors are found to optimize the output of the manufacturing system to meet a specified criterion.

The temporal representation of speech in a nonlinear model of the guinea pig cochlea

NASA Astrophysics Data System (ADS)

Holmes, Stephen D.; Sumner, Christian J.; O'Mard, Lowel P.; Meddis, Ray

2004-12-01

The temporal representation of speechlike stimuli in the auditory-nerve output of a guinea pig cochlea model is described. The model consists of a bank of dual resonance nonlinear filters that simulate the vibratory response of the basilar membrane followed by a model of the inner hair cell/auditory nerve complex. The model is evaluated by comparing its output with published physiological auditory nerve data in response to single and double vowels. The evaluation includes analyses of individual fibers, as well as ensemble responses over a wide range of best frequencies. In all cases the model response closely follows the patterns in the physiological data, particularly the tendency for the temporal firing pattern of each fiber to represent the frequency of a nearby formant of the speech sound. In the model this behavior is largely a consequence of filter shapes; nonlinear filtering has only a small contribution at low frequencies. The guinea pig cochlear model produces a useful simulation of the measured physiological response to simple speech sounds and is therefore suitable for use in more advanced applications including attempts to generalize these principles to the response of human auditory system, both normal and impaired. .

Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won't help.

PubMed

Stein, Christopher; Wallis, Lee; Adetunji, Olufemi

2015-09-19

Response time is viewed as a key performance indicator in most emergency medical services (EMS) systems. To determine the effect of increased emergency vehicle numbers on response time performance for priority 1 incidents in an urban EMS system in Cape Town, South Africa, using discrete-event computer simulation. A simulation model was created, based on input data from part of the EMS operations. Two different versions of the model were used, one with primary response vehicles and ambulances and one with only ambulances. In both cases the models were run in seven different scenarios. The first scenario used the actual number of emergency vehicles in the real system, and in each subsequent scenario vehicle numbers were increased by adding the baseline number to the cumulative total. The model using only ambulances had shorter response times and a greater number of responses meeting national response time targets than models using primary response vehicles and ambulances. In both cases an improvement in response times and the number of responses meeting national response time targets was observed with the first incremental addition of vehicles. After this the improvements rapidly diminished and eventually became negligible with each successive increase in vehicle numbers. The national response time target for urban areas was never met, even with a seven-fold increase in vehicle numbers. The addition of emergency vehicles to an urban EMS system improves response times in priority 1 incidents, but alone is not capable of the magnitude of response time improvement needed to meet the national response time targets.

TThe role of nitrogen availability in land-atmosphere interactions: a systematic evaluation of carbon-nitrogen coupling in a global land surface model using plot-level nitrogen fertilization experiments

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Goodale, C. L.; Bonan, G. B.; Mahowald, N. M.; Ricciuto, D. M.; Thornton, P. E.

2010-12-01

Recent research from global land surface models emphasizes the important role of nitrogen cycling on global climate, via its control on the terrestrial carbon balance. Despite the implications of nitrogen cycling on global climate predictions, the research community has not performed a systematic evaluation of nitrogen cycling in global models. Here, we present such an evaluation for one global land model, CLM-CN. In the evaluation we simulated 45 plot-scale nitrogen-fertilization experiments distributed across 33 temperate and boreal forest sites. Model predictions were evaluated against field observations by comparing the vegetation and soil carbon responses to the additional nitrogen. Aggregated across all experiments, the model predicted a larger vegetation carbon response and a smaller soil carbon response than observed; the responses partially offset each other, leading to a slightly larger total ecosystem carbon response than observed. However, the model-observation agreement improved for vegetation carbon when the sites with observed negative carbon responses to nitrogen were excluded, which may be because the model lacks mechanisms whereby nitrogen additions increase tree mortality. Among experiments, younger forests and boreal forests’ vegetation carbon responses were less than predicted and mature forests (> 40 years old) were greater than predicted. Specific to the CLM-CN, this study used a systematic evaluation to identify key areas to focus model development, especially soil carbon- nitrogen interactions and boreal forest nitrogen cycling. Applicable to the modeling community, this study demonstrates a standardized protocol for comparing carbon-nitrogen interactions among global land models.

A review: Development of a microdose model for analysis of adaptive response and bystander dose response behavior.

PubMed

Leonard, Bobby E

2008-02-27

Prior work has provided incremental phases to a microdosimetry modeling program to describe the dose response behavior of the radio-protective adaptive response effect. We have here consolidated these prior works (Leonard 2000, 2005, 2007a, 2007b, 2007c) to provide a composite, comprehensive Microdose Model that is also herein modified to include the bystander effect. The nomenclature for the model is also standardized for the benefit of the experimental cellular radio-biologist. It extends the prior work to explicitly encompass separately the analysis of experimental data that is 1.) only dose dependent and reflecting only adaptive response radio-protection, 2.) both dose and dose-rate dependent data and reflecting only adaptive response radio-protection for spontaneous and challenge dose damage, 3.) only dose dependent data and reflecting both bystander deleterious damage and adaptive response radio-protection (AR-BE model). The Appendix cites the various applications of the model. Here we have used the Microdose Model to analyze the, much more human risk significant, Elmore et al (2006) data for the dose and dose rate influence on the adaptive response radio-protective behavior of HeLa x Skin cells for naturally occurring, spontaneous chromosome damage from a Brachytherapy type (125)I photon radiation source. We have also applied the AR-BE Microdose Model to the Chromosome inversion data of Hooker et al (2004) reflecting both low LET bystander and adaptive response effects. The micro-beam facility data of Miller et al (1999), Nagasawa and Little (1999) and Zhou et al (2003) is also examined. For the Zhou et al (2003) data, we use the AR-BE model to estimate the threshold for adaptive response reduction of the bystander effect. The mammogram and diagnostic X-ray induction of AR and protective BE are observed. We show that bystander damage is reduced in the similar manner as spontaneous and challenge dose damage as shown by the Azzam et al (1996) data. We cite primary unresolved questions regarding adaptive response behavior and bystander behavior. The five features of major significance provided by the Microdose Model so far are 1. Single Specific Energy Hits initiate Adaptive Response. 2. Mammogram and diagnostic X-rays induce a protective Bystander Effect as well as Adaptive Response radio-protection. 3. For mammogram X-rays the Adaptive Response protection is retained at high primer dose levels. 4. The dose range of the AR protection depends on the value of the Specific Energy per Hit, 1 >. 5. Alpha particle induced deleterious Bystander damage is modulated by low LET radiation.

Estimation and Identifiability of Model Parameters in Human Nociceptive Processing Using Yes-No Detection Responses to Electrocutaneous Stimulation.

PubMed

Yang, Huan; Meijer, Hil G E; Buitenweg, Jan R; van Gils, Stephan A

2016-01-01

Healthy or pathological states of nociceptive subsystems determine different stimulus-response relations measured from quantitative sensory testing. In turn, stimulus-response measurements may be used to assess these states. In a recently developed computational model, six model parameters characterize activation of nerve endings and spinal neurons. However, both model nonlinearity and limited information in yes-no detection responses to electrocutaneous stimuli challenge to estimate model parameters. Here, we address the question whether and how one can overcome these difficulties for reliable parameter estimation. First, we fit the computational model to experimental stimulus-response pairs by maximizing the likelihood. To evaluate the balance between model fit and complexity, i.e., the number of model parameters, we evaluate the Bayesian Information Criterion. We find that the computational model is better than a conventional logistic model regarding the balance. Second, our theoretical analysis suggests to vary the pulse width among applied stimuli as a necessary condition to prevent structural non-identifiability. In addition, the numerically implemented profile likelihood approach reveals structural and practical non-identifiability. Our model-based approach with integration of psychophysical measurements can be useful for a reliable assessment of states of the nociceptive system.

An empirical propellant response function for combustion stability predictions

NASA Technical Reports Server (NTRS)

Hessler, R. O.

1980-01-01

An empirical response function model was developed for ammonium perchlorate propellants to supplant T-burner testing at the preliminary design stage. The model was developed by fitting a limited T-burner data base, in terms of oxidizer size and concentration, to an analytical two parameter response function expression. Multiple peaks are predicted, but the primary effect is of a single peak for most formulations, with notable bulges for the various AP size fractions. The model was extended to velocity coupling with the assumption that dynamic response was controlled primarily by the solid phase described by the two parameter model. The magnitude of velocity coupling was then scaled using an erosive burning law. Routine use of the model for stability predictions on a number of propulsion units indicates that the model tends to overpredict propellant response. It is concluded that the model represents a generally conservative prediction tool, suited especially for the preliminary design stage when T-burner data may not be readily available. The model work included development of a rigorous summation technique for pseudopropellant properties and of a concept for modeling ordered packing of particulates.

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America.

PubMed

Rollinson, Christine R; Liu, Yao; Raiho, Ann; Moore, David J P; McLachlan, Jason; Bishop, Daniel A; Dye, Alex; Matthes, Jaclyn H; Hessl, Amy; Hickler, Thomas; Pederson, Neil; Poulter, Benjamin; Quaife, Tristan; Schaefer, Kevin; Steinkamp, Jörg; Dietze, Michael C

2017-07-01

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO 2 at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO 2 in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO 2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm-growing season temperatures, while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO 2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO 2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO 2 , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO 2 in individual models. © 2017 John Wiley & Sons Ltd.

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.

Modeling and Identification for Vector Propulsion of an Unmanned Surface Vehicle: Three Degrees of Freedom Model and Response Model.

PubMed

Mu, Dongdong; Wang, Guofeng; Fan, Yunsheng; Sun, Xiaojie; Qiu, Bingbing

2018-06-08

This paper presents a complete scheme for research on the three degrees of freedom model and response model of the vector propulsion of an unmanned surface vehicle. The object of this paper is “Lanxin”, an unmanned surface vehicle (7.02 m × 2.6 m), which is equipped with a single vector propulsion device. First, the “Lanxin” unmanned surface vehicle and the related field experiments (turning test and zig-zag test) are introduced and experimental data are collected through various sensors. Then, the thrust of the vector thruster is estimated by the empirical formula method. Third, using the hypothesis and simplification, the three degrees of freedom model and the response model of USV are deduced and established, respectively. Fourth, the parameters of the models (three degrees of freedom model, response model and thruster servo model) are obtained by system identification, and we compare the simulated turning test and zig-zag test with the actual data to verify the accuracy of the identification results. Finally, the biggest advantage of this paper is that it combines theory with practice. Based on identified response model, simulation and practical course keeping experiments are carried out to further verify feasibility and correctness of modeling and identification.

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

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.

Adaptation of non-linear mixed amount with zero amount response surface model for analysis of concentration-dependent synergism and safety with midazolam, alfentanil, and propofol sedation.

PubMed

Liou, J-Y; Ting, C-K; Teng, W-N; Mandell, M S; Tsou, M-Y

2018-06-01

The non-linear mixed amount with zero amounts response surface model can be used to describe drug interactions and predict loss of response to noxious stimuli and respiratory depression. We aimed to determine whether this response surface model could be used to model sedation with the triple drug combination of midazolam, alfentanil and propofol. Sedation was monitored in 56 patients undergoing gastrointestinal endoscopy (modelling group) using modified alertness/sedation scores. A total of 227 combinations of effect-site concentrations were derived from pharmacokinetic models. Accuracy and the area under the receiver operating characteristic curve were calculated. Accuracy was defined as an absolute difference <0.5 between the binary patient responses and the predicted probability of loss of responsiveness. Validation was performed with a separate group (validation group) of 47 patients. Effect-site concentration ranged from 0 to 108 ng ml -1 for midazolam, 0-156 ng ml -1 for alfentanil, and 0-2.6 μg ml -1 for propofol in both groups. Synergy was strongest with midazolam and alfentanil (24.3% decrease in U 50 , concentration for half maximal drug effect). Adding propofol, a third drug, offered little additional synergy (25.8% decrease in U 50 ). Two patients (3%) experienced respiratory depression. Model accuracy was 83% and 76%, area under the curve was 0.87 and 0.80 for the modelling and validation group, respectively. The non-linear mixed amount with zero amounts triple interaction response surface model predicts patient sedation responses during endoscopy with combinations of midazolam, alfentanil, or propofol that fall within clinical use. Our model also suggests a safety margin of alfentanil fraction <0.12 that avoids respiratory depression after loss of responsiveness. Copyright © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.

Parametric design and analysis on the landing gear of a planet lander using the response surface method

NASA Astrophysics Data System (ADS)

Zheng, Guang; Nie, Hong; Luo, Min; Chen, Jinbao; Man, Jianfeng; Chen, Chuanzhi; Lee, Heow Pueh

2018-07-01

The purpose of this paper is to obtain the design parameter-landing response relation for designing the configuration of the landing gear in a planet lander quickly. To achieve this, parametric studies on the landing gear are carried out using the response surface method (RSM), based on a single landing gear landing model validated by experimental results. According to the design of experiment (DOE) results of the landing model, the RS (response surface)-functions of the three crucial landing responses are obtained, and the sensitivity analysis (SA) of the corresponding parameters is performed. Also, two multi-objective optimizations designs on the landing gear are carried out. The analysis results show that the RS (response surface)-model performs well for the landing response design process, with a minimum fitting accuracy of 98.99%. The most sensitive parameters for the three landing response are the design size of the buffers, struts friction and the diameter of the bending beam. Moreover, the good agreement between the simulated model and RS-model results are obtained in two optimized designs, which show that the RS-model coupled with the FE (finite element)-method is an efficient method to obtain the design configuration of the landing gear.

COMPUTATIONAL MODELING OF SIGNALING PATHWAYS MEDIATING CELL CYCLE AND APOPTOTIC RESPONSES TO IONIZING RADIATION MEDIATED DNA DAMAGE

EPA Science Inventory

Demonstrated of the use of a computational systems biology approach to model dose response relationships. Also discussed how the biologically motivated dose response models have only limited reference to the underlying molecular level. Discussed the integration of Computational S...

Investigating the LGBTQ Responsive Model for Supervision of Group Work

ERIC Educational Resources Information Center

Luke, Melissa; Goodrich, Kristopher M.

2013-01-01

This article reports an investigation of the LGBTQ Responsive Model for Supervision of Group Work, a trans-theoretical supervisory framework to address the needs of lesbian, gay, bisexual, transgender, and questioning (LGBTQ) persons (Goodrich & Luke, 2011). Findings partially supported applicability of the LGBTQ Responsive Model for Supervision…

Ethical Leaders Resist: A Feminist Response to ACCEL

ERIC Educational Resources Information Center

Brimager, Ashley

2017-01-01

This response to Sternberg's ACCEL (Active Concerned Citizenship and Ethical Leadership) model aims to provide a feminist perspective on the rationale and relevance of the model in mitigating harmful patriarchal gender expectations. Additionally, this response investigates potential barriers to the implementation of ACCEL as a model for gifted…

Projective Item Response Model for Test-Independent Measurement

ERIC Educational Resources Information Center

Ip, Edward Hak-Sing; Chen, Shyh-Huei

2012-01-01

The problem of fitting unidimensional item-response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that contains a major dimension of interest but that may also contain minor nuisance dimensions. Because fitting a unidimensional model to multidimensional data results in…

Climate model diversity in the Northern Hemisphere Polar vortex response to climate change.

NASA Astrophysics Data System (ADS)

Simpson, I.; Seager, R.; Hitchcock, P.; Cohen, N.

2017-12-01

Global climate models vary widely in their predictions of the future of the Northern Hemisphere stratospheric polar vortex, with some showing a significant strengthening of the vortex, some showing a significant weakening and others displaying a response that is not outside of the range expected from internal variability alone. This inter-model spread in stratospheric predictions may account for some inter-model spread in tropospheric predictions with important implications for the storm tracks and regional climate change, particularly for the North Atlantic sector. Here, our current state of understanding of this model spread and its tropospheric impacts will be reviewed. Previous studies have proposed relationships between a models polar vortex response to climate change and its present day vortex climatology while others have demonstrated links between a models polar vortex response and changing wave activity coming up from the troposphere below under a warming climate. The extent to which these mechanisms can account for the spread in polar vortex changes exhibited by the Coupled Model Intercomparison Project, phase 5 models will be assessed. In addition, preliminary results from a series of idealized experiments with the Community Atmosphere Model will be presented. In these experiments, nudging of the stratospheric zonal mean state has been imposed to mimic the inter-model spread in the polar vortex response to climate change so that the downward influence of the spread in zonal mean stratospheric responses on the tropospheric circulation can be assessed within one model.

Model updating strategy for structures with localised nonlinearities using frequency response measurements

NASA Astrophysics Data System (ADS)

Wang, Xing; Hill, Thomas L.; Neild, Simon A.; Shaw, Alexander D.; Haddad Khodaparast, Hamed; Friswell, Michael I.

2018-02-01

This paper proposes a model updating strategy for localised nonlinear structures. It utilises an initial finite-element (FE) model of the structure and primary harmonic response data taken from low and high amplitude excitations. The underlying linear part of the FE model is first updated using low-amplitude test data with established techniques. Then, using this linear FE model, the nonlinear elements are localised, characterised, and quantified with primary harmonic response data measured under stepped-sine or swept-sine excitations. Finally, the resulting model is validated by comparing the analytical predictions with both the measured responses used in the updating and with additional test data. The proposed strategy is applied to a clamped beam with a nonlinear mechanism and good agreements between the analytical predictions and measured responses are achieved. Discussions on issues of damping estimation and dealing with data from amplitude-varying force input in the updating process are also provided.

Carotene Degradation and Isomerization during Thermal Processing: A Review on the Kinetic Aspects.

PubMed

Colle, Ines J P; Lemmens, Lien; Knockaert, Griet; Van Loey, Ann; Hendrickx, Marc

2016-08-17

Kinetic models are important tools for process design and optimization to balance desired and undesired reactions taking place in complex food systems during food processing and preservation. This review covers the state of the art on kinetic models available to describe heat-induced conversion of carotenoids, in particular lycopene and β-carotene. First, relevant properties of these carotenoids are discussed. Second, some general aspects of kinetic modeling are introduced, including both empirical single-response modeling and mechanism-based multi-response modeling. The merits of multi-response modeling to simultaneously describe carotene degradation and isomerization are demonstrated. The future challenge in this research field lies in the extension of the current multi-response models to better approach the real reaction pathway and in the integration of kinetic models with mass transfer models in case of reaction in multi-phase food systems.

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.

Testing simulations of intra- and inter-annual variation in the plant production response to elevated CO(2) against measurements from an 11-year FACE experiment on grazed pasture.

PubMed

Li, Frank Yonghong; Newton, Paul C D; Lieffering, Mark

2014-01-01

Ecosystem models play a crucial role in understanding and evaluating the combined impacts of rising atmospheric CO2 concentration and changing climate on terrestrial ecosystems. However, we are not aware of any studies where the capacity of models to simulate intra- and inter-annual variation in responses to elevated CO2 has been tested against long-term experimental data. Here we tested how well the ecosystem model APSIM/AgPasture was able to simulate the results from a free air carbon dioxide enrichment (FACE) experiment on grazed pasture. At this FACE site, during 11 years of CO2 enrichment, a wide range in annual plant production response to CO2 (-6 to +28%) was observed. As well as running the full model, which includes three plant CO2 response functions (plant photosynthesis, nitrogen (N) demand and stomatal conductance), we also tested the influence of these three functions on model predictions. Model/data comparisons showed that: (i) overall the model over-predicted the mean annual plant production response to CO2 (18.5% cf 13.1%) largely because years with small or negative responses to CO2 were not well simulated; (ii) in general seasonal and inter-annual variation in plant production responses to elevated CO2 were well represented by the model; (iii) the observed CO2 enhancement in overall mean legume content was well simulated but year-to-year variation in legume content was poorly captured by the model; (iv) the best fit of the model to the data required all three CO2 response functions to be invoked; (v) using actual legume content and reduced N fixation rate under elevated CO2 in the model provided the best fit to the experimental data. We conclude that in temperate grasslands the N dynamics (particularly the legume content and N fixation activity) play a critical role in pasture production responses to elevated CO2 , and are processes for model improvement. © 2013 John Wiley & Sons Ltd.

Process-Response Modeling and the Scientific Process.

ERIC Educational Resources Information Center

Fichter, Lynn S.

1988-01-01

Discusses the process-response model (PRM) in its theoretical and practical forms. Describes how geologists attempt to reconstruct the process from the response (the geologic phenomenon) being studied. (TW)

STRESS RESPONSE STUDIES USING ANIMAL MODELS

EPA Science Inventory

This presentation will provide the evidence that ozone exposure in animal models induce neuroendocrine stress response and this stress response modulates lung injury and inflammation through adrenergic and glucocorticoid receptors.

Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

NASA Technical Reports Server (NTRS)

Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco;

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

A multi-agent safety response model in the construction industry.

PubMed

Meliá, José L

2015-01-01

The construction industry is one of the sectors with the highest accident rates and the most serious accidents. A multi-agent safety response approach allows a useful diagnostic tool in order to understand factors affecting risk and accidents. The special features of the construction sector can influence the relationships among safety responses along the model of safety influences. The purpose of this paper is to test a model explaining risk and work-related accidents in the construction industry as a result of the safety responses of the organization, the supervisors, the co-workers and the worker. 374 construction employees belonging to 64 small Spanish construction companies working for two main companies participated in the study. Safety responses were measured using a 45-item Likert-type questionnaire. The structure of the measure was analyzed using factor analysis and the model of effects was tested using a structural equation model. Factor analysis clearly identifies the multi-agent safety dimensions hypothesized. The proposed safety response model of work-related accidents, involving construction specific results, showed a good fit. The multi-agent safety response approach to safety climate is a useful framework for the assessment of organizational and behavioral risks in construction.

Solar irradiance reduction to counteract radiative forcing from a quadrupling of CO2: climate responses simulated by four earth system models

NASA Astrophysics Data System (ADS)

Schmidt, H.; Alterskjær, K.; Karam, D. Bou; Boucher, O.; Jones, A.; Kristjánsson, J. E.; Niemeier, U.; Schulz, M.; Aaheim, A.; Benduhn, F.; Lawrence, M.; Timmreck, C.

2012-06-01

In this study we compare the response of four state-of-the-art Earth system models to climate engineering under scenario G1 of two model intercomparison projects: GeoMIP (Geoengineering Model Intercomparison Project) and IMPLICC (EU project "Implications and risks of engineering solar radiation to limit climate change"). In G1, the radiative forcing from an instantaneous quadrupling of the CO2 concentration, starting from the preindustrial level, is balanced by a reduction of the solar constant. Model responses to the two counteracting forcings in G1 are compared to the preindustrial climate in terms of global means and regional patterns and their robustness. While the global mean surface air temperature in G1 remains almost unchanged compared to the control simulation, the meridional temperature gradient is reduced in all models. Another robust response is the global reduction of precipitation with strong effects in particular over North and South America and northern Eurasia. In comparison to the climate response to a quadrupling of CO2 alone, the temperature responses are small in experiment G1. Precipitation responses are, however, in many regions of comparable magnitude but globally of opposite sign.

Analysis of Mars Pathfinder Entry Data, Aerothermal Heating, and Heat Shield Material Response

NASA Technical Reports Server (NTRS)

Milos, Frank; Chen, Y. K.; Tran, H. K.; Rasky, Daniel J. (Technical Monitor)

1997-01-01

The Mars Pathfinder heatshield contained several thermocouples and resistance thermometers. A description of the experiment, the entry data, and analysis of the entry environment and material response is presented. In particular, the analysis addresses uncertainties of the data and the fluid dynamics and material response models. The calculations use the latest trajectory and atmosphere reconstructions for the Pathfinder entry. A modified version of the GIANTS code is used for CFD (computational fluid dynamics) analyses, and FIAT is used for material response. The material response and flowfield are coupled appropriately. Three different material response models are considered. The analysis of Pathfinder entry data for validation of aerothermal heating and material response models is complicated by model uncertainties and unanticipated data-acquisition and processing problems. We will discuss these issues as well as ramifications of the data and analysis for future Mars missions.

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.

Using item response theory to investigate the structure of anticipated affect: do self-reports about future affective reactions conform to typical or maximal models?

PubMed

Zampetakis, Leonidas A; Lerakis, Manolis; Kafetsios, Konstantinos; Moustakis, Vassilis

2015-01-01

In the present research, we used item response theory (IRT) to examine whether effective predictions (anticipated affect) conforms to a typical (i.e., what people usually do) or a maximal behavior process (i.e., what people can do). The former, correspond to non-monotonic ideal point IRT models, whereas the latter correspond to monotonic dominance IRT models. A convenience, cross-sectional student sample (N = 1624) was used. Participants were asked to report on anticipated positive and negative affect around a hypothetical event (emotions surrounding the start of a new business). We carried out analysis comparing graded response model (GRM), a dominance IRT model, against generalized graded unfolding model, an unfolding IRT model. We found that the GRM provided a better fit to the data. Findings suggest that the self-report responses to anticipated affect conform to dominance response process (i.e., maximal behavior). The paper also discusses implications for a growing literature on anticipated affect.

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.

Using item response theory to investigate the structure of anticipated affect: do self-reports about future affective reactions conform to typical or maximal models?

PubMed Central

Zampetakis, Leonidas A.; Lerakis, Manolis; Kafetsios, Konstantinos; Moustakis, Vassilis

2015-01-01

In the present research, we used item response theory (IRT) to examine whether effective predictions (anticipated affect) conforms to a typical (i.e., what people usually do) or a maximal behavior process (i.e., what people can do). The former, correspond to non-monotonic ideal point IRT models, whereas the latter correspond to monotonic dominance IRT models. A convenience, cross-sectional student sample (N = 1624) was used. Participants were asked to report on anticipated positive and negative affect around a hypothetical event (emotions surrounding the start of a new business). We carried out analysis comparing graded response model (GRM), a dominance IRT model, against generalized graded unfolding model, an unfolding IRT model. We found that the GRM provided a better fit to the data. Findings suggest that the self-report responses to anticipated affect conform to dominance response process (i.e., maximal behavior). The paper also discusses implications for a growing literature on anticipated affect. PMID:26441806

A comparison of models of the isometric force of locust skeletal muscle in response to pulse train inputs.

PubMed

Wilson, Emma; Rustighi, Emiliano; Newland, Philip L; Mace, Brian R

2012-03-01

Muscle models are an important tool in the development of new rehabilitation and diagnostic techniques. Many models have been proposed in the past, but little work has been done on comparing the performance of models. In this paper, seven models that describe the isometric force response to pulse train inputs are investigated. Five of the models are from the literature while two new models are also presented. Models are compared in terms of their ability to fit to isometric force data, using Akaike's and Bayesian information criteria and by examining the ability of each model to describe the underlying behaviour in response to individual pulses. Experimental data were collected by stimulating the locust extensor tibia muscle and measuring the force generated at the tibia. Parameters in each model were estimated by minimising the error between the modelled and actual force response for a set of training data. A separate set of test data, which included physiological kick-type data, was used to assess the models. It was found that a linear model performed the worst whereas a new model was found to perform the best. The parameter sensitivity of this new model was investigated using a one-at-a-time approach, and it found that the force response is not particularly sensitive to changes in any parameter.

A comparison of methods of fitting several models to nutritional response data.

PubMed

Vedenov, D; Pesti, G M

2008-02-01

A variety of models have been proposed to fit nutritional input-output response data. The models are typically nonlinear; therefore, fitting the models usually requires sophisticated statistical software and training to use it. An alternative tool for fitting nutritional response models was developed by using widely available and easier-to-use Microsoft Excel software. The tool, implemented as an Excel workbook (NRM.xls), allows simultaneous fitting and side-by-side comparisons of several popular models. This study compared the results produced by the tool we developed and PROC NLIN of SAS. The models compared were the broken line (ascending linear and quadratic segments), saturation kinetics, 4-parameter logistics, sigmoidal, and exponential models. The NRM.xls workbook provided results nearly identical to those of PROC NLIN. Furthermore, the workbook successfully fit several models that failed to converge in PROC NLIN. Two data sets were used as examples to compare fits by the different models. The results suggest that no particular nonlinear model is necessarily best for all nutritional response data.

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.

Comparing the GPR responses of real experiment and simulation of cavity

NASA Astrophysics Data System (ADS)

Yu, H.; Nam, M. J.; Kim, C.; Lee, D. K.

2017-12-01

Seoul, capital city of South Korea, has been suffering from ground subsidence mainly caused by cavities beneath the road. Urban subsidence usually brings serious social problems such as damages of human life, properties and so on. To prevent ground subsidence, Korea government embark much money in developing techniques to detect cavities in advance. Ground penetrating radar (GPR) is known as the most effective method among geophysical surveys in exploring underground cavitied but shallow ones only. For the study of GPR responses for underground cavities, real scale physical models have been made and GPR surveys are conducted. In simulating cavities with various sizes at various depths, spheres of polystyrene have been used since the electric permittivity of polystyrene has a similar value to that of the air. However, the real scale experiments only used simple shapes of cavities due to its expensive construction cost and further changing in shapes of cavities is limited once they are built. For not only comparison between field responses for the physical model and numerical responses but also for analyzing GPR responses for more various cavity shapes in numerous environments, we conducted numerical simulation of GPR responses using three-dimensional (3D) finite difference time domain (FDTD) GPR modeling algorithm employing staggered grid. We first construct numerical modeling for models similar to the physical models to confirm considering radiation pattern in numerical modeling of GPR responses which is critical to generate similar responses to field GPR data. Further, GPR responses computed for various shapes of cavities in several different environments determine not only additional construction of the physical cavities but also analyze the characteristics of GPR responses.

On the dimension of complex responses in nonlinear structural vibrations

NASA Astrophysics Data System (ADS)

Wiebe, R.; Spottswood, S. M.

2016-07-01

The ability to accurately model engineering systems under extreme dynamic loads would prove a major breakthrough in many aspects of aerospace, mechanical, and civil engineering. Extreme loads frequently induce both nonlinearities and coupling which increase the complexity of the response and the computational cost of finite element models. Dimension reduction has recently gained traction and promises the ability to distill dynamic responses down to a minimal dimension without sacrificing accuracy. In this context, the dimensionality of a response is related to the number of modes needed in a reduced order model to accurately simulate the response. Thus, an important step is characterizing the dimensionality of complex nonlinear responses of structures. In this work, the dimensionality of the nonlinear response of a post-buckled beam is investigated. Significant detail is dedicated to carefully introducing the experiment, the verification of a finite element model, and the dimensionality estimation algorithm as it is hoped that this system may help serve as a benchmark test case. It is shown that with minor modifications, the method of false nearest neighbors can quantitatively distinguish between the response dimension of various snap-through, non-snap-through, random, and deterministic loads. The state-space dimension of the nonlinear system in question increased from 2-to-10 as the system response moved from simple, low-level harmonic to chaotic snap-through. Beyond the problem studied herein, the techniques developed will serve as a prescriptive guide in developing fast and accurate dimensionally reduced models of nonlinear systems, and eventually as a tool for adaptive dimension-reduction in numerical modeling. The results are especially relevant in the aerospace industry for the design of thin structures such as beams, panels, and shells, which are all capable of spatio-temporally complex dynamic responses that are difficult and computationally expensive to model.

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

NASA Technical Reports Server (NTRS)

Frady, Gregory P.; Duvall, Lowery D.; Fulcher, Clay W. G.; Laverde, Bruce T.; Hunt, Ronald A.

2011-01-01

rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for component-loaded curved orthogrid panels typical of launch vehicle skin structures. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was applied to correlate the measured input sound pressures across the energized panel. This application quantifies the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software developed for the RPTF method allows easy replacement of the diffuse acoustic field with other pressure fields such as a turbulent boundary layer (TBL) model suitable for vehicle ascent. Structural responses using a TBL model were demonstrated, and wind tunnel tests have been proposed to anchor the predictions and provide new insight into modeling approaches for this environment. Finally, design load factors were developed from the measured and predicted responses and compared with those derived from traditional techniques such as historical Mass Acceleration Curves and Barrett scaling methods for acreage and component-loaded panels.

General mixture item response models with different item response structures: Exposition with an application to Likert scales.

PubMed

Tijmstra, Jesper; Bolsinova, Maria; Jeon, Minjeong

2018-01-10

This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person's responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category ("neither agree nor disagree") is taken to be qualitatively similar to the other categories, and is taken to provide information about the person's endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person's willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example.

Shift-variant linear system modeling for multispectral scanners

NASA Astrophysics Data System (ADS)

Amini, Abolfazl M.; Ioup, George E.; Ioup, Juliette W.

1995-07-01

Multispectral scanner data are affected both by the spatial impulse response of the sensor and the spectral response of each channel. To achieve a realistic representation for the output data for a given scene spectral input, both of these effects must be incorporated into a forward model. Each channel can have a different spatial response and each has its characteristic spectral response. A forward model is built which includes the shift invariant spatial broadening of the input for the channels and the shift variant spectral response across channels. The model is applied to the calibrated airborne multispectral scanner as well as the airborne terrestrial applications sensor developed at NASA Stennis Space Center.

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 discourse on sensitivity analysis for discretely-modeled structures

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Haftka, Raphael T.

1991-01-01

A descriptive review is presented of the most recent methods for performing sensitivity analysis of the structural behavior of discretely-modeled systems. The methods are generally but not exclusively aimed at finite element modeled structures. Topics included are: selections of finite difference step sizes; special consideration for finite difference sensitivity of iteratively-solved response problems; first and second derivatives of static structural response; sensitivity of stresses; nonlinear static response sensitivity; eigenvalue and eigenvector sensitivities for both distinct and repeated eigenvalues; and sensitivity of transient response for both linear and nonlinear structural response.

User-experience surveys with maternity services: a randomized comparison of two data collection models.

PubMed

Bjertnaes, Oyvind Andresen; Iversen, Hilde Hestad

2012-08-01

To compare two ways of combining postal and electronic data collection for a maternity services user-experience survey. Cross-sectional survey. Maternity services in Norway. All women who gave birth at a university hospital in Norway between 1 June and 27 July 2010. Patients were randomized into the following groups (n= 752): Group A, who were posted questionnaires with both electronic and paper response options for both the initial and reminder postal requests; and Group B, who were posted questionnaires with an electronic response option for the initial request, and both electronic and paper response options for the reminder postal request. Response rate, the amount of difference in background variables between respondents and non-respondents, main study results and estimated cost-effectiveness. The final response rate was significantly higher in Group A (51.9%) than Group B (41.1%). None of the background variables differed significantly between the respondents and non-respondents in Group A, while two variables differed significantly between the respondents and non-respondents in Group B. None of the 11 user-experience scales differed significantly between Groups A and B. The estimated costs per response for the forthcoming national survey was €11.7 for data collection Model A and €9.0 for Model B. The model with electronic-only response option in the first request had lowest response rate. However, this model performed equal to the other model on non-response bias and better on estimated cost-effectiveness, and is the better of the two models in large-scale user experiences surveys with maternity services.

Model Selection Indices for Polytomous Items

ERIC Educational Resources Information Center

Kang, Taehoon; Cohen, Allan S.; Sung, Hyun-Jung

2009-01-01

This study examines the utility of four indices for use in model selection with nested and nonnested polytomous item response theory (IRT) models: a cross-validation index and three information-based indices. Four commonly used polytomous IRT models are considered: the graded response model, the generalized partial credit model, the partial credit…

Development of a multi-body nonlinear model for a seat-occupant system

NASA Astrophysics Data System (ADS)

Azizi, Yousof

A car seat is an important component of today's cars, which directly affects ride comfort experienced by occupants. Currently, the process of ride comfort evaluation is subjective. Alternatively, the ride comfort can be evaluated by a series of objective metrics in the dynamic response of the occupant. From previous studies it is well known that the dynamic behavior of a seat-occupant system is greatly affected by soft nonlinear viscoelastic materials used in the seat cushion. Therefore, in this research, especial attention was given to efficiently modeling the behavior of seat cushion. In the first part of this research, a phenomenological nonlinear viscoelastic foam model was proposed and its ability to capture uniaxial behavior of foam was investigated. The model is based on the assumption that the total stress can be decomposed into the sum of a nonlinear elastic component, modeled by a higher order polynomial of strain, and a nonlinear hereditary type viscoelastic component. System identification procedures were developed to estimate the model parameters using uniaxial cyclic compression data from experiments conducted at different rates on two types of low density polyurethane foams and three types of high density CONFOR foams. The performance of the proposed model was compared to that of other traditional continuum models. For each foam type, it was observed that lower order models are sufficient to describe the uniaxial behavior of the foam compressed at different rates. Although, the estimated model parameters were functions of the input strain rate. Alternatively, higher order comprehensive models, with strain independent parameters, were estimated as well. The estimated comprehensive model predicts foam responses under different compression rates. Also, a methodology was proposed to predict the stress-response of a layered foam system using the estimated models of each foam in the layers. Next, the estimated foam model was incorporated into a single-degree of freedom foam-mass model which is also the simplest model of seat-occupant systems. The steady-state response of the system when it is subjected to harmonic base excitation was studied using the incremental harmonic balance method. The incremental harmonic balance method was used to reduce the time required to generate the steady-state response of the system. The incremental harmonic balance method was used to reduce the time required to generate the steady-state response of the system. Experiments are conducted on a single-degree of freedom foam-mass system subjected to harmonic base excitation. Initially, the simulated response predictions were found to deviate from the experimental results. The foam-mass model was then modified to incorporate rate dependency of foam parameters resulting in response predictions that were in good agreement with experimental results. In the second part of this research, the dynamic response of a seat-occupant system was examined through a more realistic planar multi-body seat-occupant model. A constraint Lagrangian formulation was used to derive the governing equations for the seat-occupant model. First, the governing equations were solved numerically to obtain the occupant transient response, the occupant's H-Point location and the interfacial pressure distribution. Variations in the H-Point location and the seat-occupant pressure distribution with changes in the seat-occupant parameters, including the seat geometry and the occupant's characteristics, were studied. The estimated pressure was also investigated experimentally and was found to match with the results obtained using the seat-occupant model. Next, the incremental harmonic balance method was modified and used to obtain the occupant's steady-state response when the seat-occupant system was subjected to harmonic base excitation at different frequencies. The system frequency response and mode shapes at different frequencies were also obtained and compared to the previously measured experimental frequency responses. Finally, variations in the estimated frequency response with changes in the seat-occupant parameters, including the seat geometry and the occupant characteristics, were studied.

Improved partition equilibrium model for predicting analyte response in electrospray ionization mass spectrometry.

PubMed

Du, Lihong; White, Robert L

2009-02-01

A previously proposed partition equilibrium model for quantitative prediction of analyte response in electrospray ionization mass spectrometry is modified to yield an improved linear relationship. Analyte mass spectrometer response is modeled by a competition mechanism between analyte and background electrolytes that is based on partition equilibrium considerations. The correlation between analyte response and solution composition is described by the linear model over a wide concentration range and the improved model is shown to be valid for a wide range of experimental conditions. The behavior of an analyte in a salt solution, which could not be explained by the original model, is correctly predicted. The ion suppression effects of 16:0 lysophosphatidylcholine (LPC) on analyte signals are attributed to a combination of competition for excess charge and reduction of total charge due to surface tension effects. In contrast to the complicated mathematical forms that comprise the original model, the simplified model described here can more easily be employed to predict analyte mass spectrometer responses for solutions containing multiple components. Copyright (c) 2008 John Wiley & Sons, Ltd.

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

Harnessing the theoretical foundations of the exponential and beta-Poisson dose-response models to quantify parameter uncertainty using Markov Chain Monte Carlo.

PubMed

Schmidt, Philip J; Pintar, Katarina D M; Fazil, Aamir M; Topp, Edward

2013-09-01

Dose-response models are the essential link between exposure assessment and computed risk values in quantitative microbial risk assessment, yet the uncertainty that is inherent to computed risks because the dose-response model parameters are estimated using limited epidemiological data is rarely quantified. Second-order risk characterization approaches incorporating uncertainty in dose-response model parameters can provide more complete information to decisionmakers by separating variability and uncertainty to quantify the uncertainty in computed risks. Therefore, the objective of this work is to develop procedures to sample from posterior distributions describing uncertainty in the parameters of exponential and beta-Poisson dose-response models using Bayes's theorem and Markov Chain Monte Carlo (in OpenBUGS). The theoretical origins of the beta-Poisson dose-response model are used to identify a decomposed version of the model that enables Bayesian analysis without the need to evaluate Kummer confluent hypergeometric functions. Herein, it is also established that the beta distribution in the beta-Poisson dose-response model cannot address variation among individual pathogens, criteria to validate use of the conventional approximation to the beta-Poisson model are proposed, and simple algorithms to evaluate actual beta-Poisson probabilities of infection are investigated. The developed MCMC procedures are applied to analysis of a case study data set, and it is demonstrated that an important region of the posterior distribution of the beta-Poisson dose-response model parameters is attributable to the absence of low-dose data. This region includes beta-Poisson models for which the conventional approximation is especially invalid and in which many beta distributions have an extreme shape with questionable plausibility. © Her Majesty the Queen in Right of Canada 2013. Reproduced with the permission of the Minister of the Public Health Agency of Canada.

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

NASA Astrophysics Data System (ADS)

Wu, Donghai; Ciais, Philippe; Viovy, Nicolas; Knapp, Alan K.; Wilcox, Kevin; Bahn, Michael; Smith, Melinda D.; Vicca, Sara; Fatichi, Simone; Zscheischler, Jakob; He, Yue; Li, Xiangyi; Ito, Akihiko; Arneth, Almut; Harper, Anna; Ukkola, Anna; Paschalis, Athanasios; Poulter, Benjamin; Peng, Changhui; Ricciuto, Daniel; Reinthaler, David; Chen, Guangsheng; Tian, Hanqin; Genet, Hélène; Mao, Jiafu; Ingrisch, Johannes; Nabel, Julia E. S. M.; Pongratz, Julia; Boysen, Lena R.; Kautz, Markus; Schmitt, Michael; Meir, Patrick; Zhu, Qiuan; Hasibeder, Roland; Sippel, Sebastian; Dangal, Shree R. S.; Sitch, Stephen; Shi, Xiaoying; Wang, Yingping; Luo, Yiqi; Liu, Yongwen; Piao, Shilong

2018-06-01

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon-water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

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.

Computerized Adaptive Test (CAT) Applications and Item Response Theory Models for Polytomous Items

ERIC Educational Resources Information Center

Aybek, Eren Can; Demirtasli, R. Nukhet

2017-01-01

This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…

Introduction to Multilevel Item Response Theory Analysis: Descriptive and Explanatory Models

ERIC Educational Resources Information Center

Sulis, Isabella; Toland, Michael D.

2017-01-01

Item response theory (IRT) models are the main psychometric approach for the development, evaluation, and refinement of multi-item instruments and scaling of latent traits, whereas multilevel models are the primary statistical method when considering the dependence between person responses when primary units (e.g., students) are nested within…

The Cognitive-Miser Response Model: Testing for Intuitive and Deliberate Reasoning

ERIC Educational Resources Information Center

Bockenholt, Ulf

2012-01-01

In a number of psychological studies, answers to reasoning vignettes have been shown to result from both intuitive and deliberate response processes. This paper utilizes a psychometric model to separate these two response tendencies. An experimental application shows that the proposed model facilitates the analysis of dual-process item responses…

Stressor-response modeling using the 2D water quality model and regression trees to predict chlorophyll-a in a reservoir system

USDA-ARS?s Scientific Manuscript database

In order to control algal blooms, stressor-response relationships between water quality metrics, environmental variables, and algal growth should be understood and modeled. Machine-learning methods were suggested to express stressor-response relationships found by application of mechanistic water qu...

IRTPRO 2.1 for Windows (Item Response Theory for Patient-Reported Outcomes)

ERIC Educational Resources Information Center

Paek, Insu; Han, Kyung T.

2013-01-01

This article reviews a new item response theory (IRT) model estimation program, IRTPRO 2.1, for Windows that is capable of unidimensional and multidimensional IRT model estimation for existing and user-specified constrained IRT models for dichotomously and polytomously scored item response data. (Contains 1 figure and 2 notes.)

The Role of Assessment in a Response to Intervention Model

ERIC Educational Resources Information Center

Crawford, Lindy

2014-01-01

This article discusses the role of assessment in a response-to-intervention model. Although assessment represents only 1 component in a response-to-intervention model, a well-articulated assessment system is critical in providing teachers with reliable data that are easily interpreted and used to make instructional decisions. Three components of…

KERIS: kaleidoscope of gene responses to inflammation between species

PubMed Central

Li, Peng; Tompkins, Ronald G; Xiao, Wenzhong

2017-01-01

A cornerstone of modern biomedical research is the use of animal models to study disease mechanisms and to develop new therapeutic approaches. In order to help the research community to better explore the similarities and differences of genomic response between human inflammatory diseases and murine models, we developed KERIS: kaleidoscope of gene responses to inflammation between species (available at http://www.igenomed.org/keris/). As of June 2016, KERIS includes comparisons of the genomic response of six human inflammatory diseases (burns, trauma, infection, sepsis, endotoxin and acute respiratory distress syndrome) and matched mouse models, using 2257 curated samples from the Inflammation and the Host Response to Injury Glue Grant studies and other representative studies in Gene Expression Omnibus. A researcher can browse, query, visualize and compare the response patterns of genes, pathways and functional modules across different diseases and corresponding murine models. The database is expected to help biologists choosing models when studying the mechanisms of particular genes and pathways in a disease and prioritizing the translation of findings from disease models into clinical studies. PMID:27789704

Do Responses to Different Anthropogenic Forcings Add Linearly in Climate Models?

NASA Technical Reports Server (NTRS)

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; Bonfils, Celine; LeGrande, Allegra N.; Nazarenko, Larissa; Tsigaridis, Kostas

2015-01-01

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings; however, we demonstrate that there are significant nonlinearities in precipitation responses to di?erent forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to di?erences in ozone forcing arising from interactions between forcing agents. Our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.

Do responses to different anthropogenic forcings add linearly in climate models?

DOE PAGES

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; ...

2015-10-14

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM4) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings. However,more » we demonstrate that there are significant nonlinearities in precipitation responses to different forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to differences in ozone forcing arising from interactions between forcing agents. Lastly, our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.« less

Hierarchical dose response of E. coli O157:H7 from human outbreaks incorporating heterogeneity in exposure.

PubMed

Teunis, P F M; Ogden, I D; Strachan, N J C

2008-06-01

The infectivity of pathogenic microorganisms is a key factor in the transmission of an infectious disease in a susceptible population. Microbial infectivity is generally estimated from dose-response studies in human volunteers. This can only be done with mildly pathogenic organisms. Here a hierarchical Beta-Poisson dose-response model is developed utilizing data from human outbreaks. On the lowest level each outbreak is modelled separately and these are then combined at a second level to produce a group dose-response relation. The distribution of foodborne pathogens often shows strong heterogeneity and this is incorporated by introducing an additional parameter to the dose-response model, accounting for the degree of overdispersion relative to Poisson distribution. It was found that heterogeneity considerably influences the shape of the dose-response relationship and increases uncertainty in predicted risk. This uncertainty is greater than previously reported surrogate and outbreak models using a single level of analysis. Monte Carlo parameter samples (alpha, beta of the Beta-Poisson model) can be readily incorporated in risk assessment models built using tools such as S-plus and @ Risk.

Fitting IRT Models to Dichotomous and Polytomous Data: Assessing the Relative Model-Data Fit of Ideal Point and Dominance Models

ERIC Educational Resources Information Center

Tay, Louis; Ali, Usama S.; Drasgow, Fritz; Williams, Bruce

2011-01-01

This study investigated the relative model-data fit of an ideal point item response theory (IRT) model (the generalized graded unfolding model [GGUM]) and dominance IRT models (e.g., the two-parameter logistic model [2PLM] and Samejima's graded response model [GRM]) to simulated dichotomous and polytomous data generated from each of these models.…

Dose- and time-dependence of the host-mediated response to paclitaxel therapy: a mathematical modeling approach.

PubMed

Benguigui, Madeleine; Alishekevitz, Dror; Timaner, Michael; Shechter, Dvir; Raviv, Ziv; Benzekry, Sebastien; Shaked, Yuval

2018-01-05

It has recently been suggested that pro-tumorigenic host-mediated processes induced in response to chemotherapy counteract the anti-tumor activity of therapy, and thereby decrease net therapeutic outcome. Here we use experimental data to formulate a mathematical model describing the host response to different doses of paclitaxel (PTX) chemotherapy as well as the duration of the response. Three previously described host-mediated effects are used as readouts for the host response to therapy. These include the levels of circulating endothelial progenitor cells in peripheral blood and the effect of plasma derived from PTX-treated mice on migratory and invasive properties of tumor cells in vitro . A first set of mathematical models, based on basic principles of pharmacokinetics/pharmacodynamics, did not appropriately describe the dose-dependence and duration of the host response regarding the effects on invasion. We therefore provide an alternative mathematical model with a dose-dependent threshold, instead of a concentration-dependent one, that describes better the data. This model is integrated into a global model defining all three host-mediated effects. It not only precisely describes the data, but also correctly predicts host-mediated effects at different doses as well as the duration of the host response. This mathematical model may serve as a tool to predict the host response to chemotherapy in cancer patients, and therefore may be used to design chemotherapy regimens with improved therapeutic outcome by minimizing host mediated effects.

Modeling the interactions between pathogenic bacteria, bacteriophage and immune response

NASA Astrophysics Data System (ADS)

Leung, Chung Yin (Joey); Weitz, Joshua S.

The prevalence of antibiotic-resistant strains of pathogenic bacteria has led to renewed interest in the use of bacteriophage (phage), or virus that infects bacteria, as a therapeutic agent against bacterial infections. However, little is known about the theoretical mechanism by which phage therapy may work. In particular, interactions between the bacteria, the phage and the host immune response crucially influences the outcome of the therapy. Few models of phage therapy have incorporated all these three components, and existing models suffer from unrealistic assumptions such as unbounded growth of the immune response. We propose a model of phage therapy with an emphasis on nonlinear feedback arising from interactions with bacteria and the immune response. Our model shows a synergistic effect between the phage and the immune response which underlies a possible mechanism for phage to catalyze the elimination of bacteria even when neither the immune response nor phage could do so alone. We study the significance of this effect for different parameters of infection and immune response, and discuss its implications for phage therapy.

Causal Responsibility and Counterfactuals

PubMed Central

Lagnado, David A; Gerstenberg, Tobias; Zultan, Ro'i

2013-01-01

How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in multiple agent contexts. We draw on the structural model account of actual causation (e.g., Halpern & Pearl, 2005) and its extension to responsibility judgments (Chockler & Halpern, 2004). We review the main theoretical and empirical issues that arise from this literature and propose a novel model of intuitive judgments of responsibility. This model is a function of both pivotality (whether an agent made a difference to the outcome) and criticality (how important the agent is perceived to be for the outcome, before any actions are taken). The model explains empirical results from previous studies and is supported by a new experiment that manipulates both pivotality and criticality. We also discuss possible extensions of this model to deal with a broader range of causal situations. Overall, our approach emphasizes the close interrelations between causality, counterfactuals, and responsibility attributions. PMID:23855451

Assessment of health surveys: fitting a multidimensional graded response model.

PubMed

Depaoli, Sarah; Tiemensma, Jitske; Felt, John M

The multidimensional graded response model, an item response theory (IRT) model, can be used to improve the assessment of surveys, even when sample sizes are restricted. Typically, health-based survey development utilizes classical statistical techniques (e.g. reliability and factor analysis). In a review of four prominent journals within the field of Health Psychology, we found that IRT-based models were used in less than 10% of the studies examining scale development or assessment. However, implementing IRT-based methods can provide more details about individual survey items, which is useful when determining the final item content of surveys. An example using a quality of life survey for Cushing's syndrome (CushingQoL) highlights the main components for implementing the multidimensional graded response model. Patients with Cushing's syndrome (n = 397) completed the CushingQoL. Results from the multidimensional graded response model supported a 2-subscale scoring process for the survey. All items were deemed as worthy contributors to the survey. The graded response model can accommodate unidimensional or multidimensional scales, be used with relatively lower sample sizes, and is implemented in free software (example code provided in online Appendix). Use of this model can help to improve the quality of health-based scales being developed within the Health Sciences.

Chlorine truck attack consequences and mitigation.

PubMed

Barrett, Anthony Michael; Adams, Peter J

2011-08-01

We develop and apply an integrated modeling system to estimate fatalities from intentional release of 17 tons of chlorine from a tank truck in a generic urban area. A public response model specifies locations and actions of the populace. A chemical source term model predicts initial characteristics of the chlorine vapor and aerosol cloud. An atmospheric dispersion model predicts cloud spreading and movement. A building air exchange model simulates movement of chlorine from outdoors into buildings at each location. A dose-response model translates chlorine exposures into predicted fatalities. Important parameters outside defender control include wind speed, atmospheric stability class, amount of chlorine released, and dose-response model parameters. Without fast and effective defense response, with 2.5 m/sec wind and stability class F, we estimate approximately 4,000 (half within ∼10 minutes) to 30,000 fatalities (half within ∼20 minutes), depending on dose-response model. Although we assume 7% of the population was outdoors, they represent 60-90% of fatalities. Changing weather conditions result in approximately 50-90% lower total fatalities. Measures such as sheltering in place, evacuation, and use of security barriers and cryogenic storage can reduce fatalities, sometimes by 50% or more, depending on response speed and other factors. © 2011 Society for Risk Analysis.

Testing of the European Union exposure-response relationships and annoyance equivalents model for annoyance due to transportation noises: The need of revised exposure-response relationships and annoyance equivalents model.

PubMed

Gille, Laure-Anne; Marquis-Favre, Catherine; Morel, Julien

2016-09-01

An in situ survey was performed in 8 French cities in 2012 to study the annoyance due to combined transportation noises. As the European Commission recommends to use the exposure-response relationships suggested by Miedema and Oudshoorn [Environmental Health Perspective, 2001] to predict annoyance due to single transportation noise, these exposure-response relationships were tested using the annoyance due to each transportation noise measured during the French survey. These relationships only enabled a good prediction in terms of the percentages of people highly annoyed by road traffic noise. For the percentages of people annoyed and a little annoyed by road traffic noise, the quality of prediction is weak. For aircraft and railway noises, prediction of annoyance is not satisfactory either. As a consequence, the annoyance equivalents model of Miedema [The Journal of the Acoustical Society of America, 2004], based on these exposure-response relationships did not enable a good prediction of annoyance due to combined transportation noises. Local exposure-response relationships were derived, following the whole computation suggested by Miedema and Oudshoorn [Environmental Health Perspective, 2001]. They led to a better calculation of annoyance due to each transportation noise in the French cities. A new version of the annoyance equivalents model was proposed using these new exposure-response relationships. This model enabled a better prediction of the total annoyance due to the combined transportation noises. These results encourage therefore to improve the annoyance prediction for noise in isolation with local or revised exposure-response relationships, which will also contribute to improve annoyance modeling for combined noises. With this aim in mind, a methodology is proposed to consider noise sensitivity in exposure-response relationships and in the annoyance equivalents model. The results showed that taking into account such variable did not enable to enhance both exposure-response relationships and the annoyance equivalents model. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Models of subjective response to in-flight motion data

NASA Technical Reports Server (NTRS)

Rudrapatna, A. N.; Jacobson, I. D.

1973-01-01

Mathematical relationships between subjective comfort and environmental variables in an air transportation system are investigated. As a first step in model building, only the motion variables are incorporated and sensitivities are obtained using stepwise multiple regression analysis. The data for these models have been collected from commercial passenger flights. Two models are considered. In the first, subjective comfort is assumed to depend on rms values of the six-degrees-of-freedom accelerations. The second assumes a Rustenburg type human response function in obtaining frequency weighted rms accelerations, which are used in a linear model. The form of the human response function is examined and the results yield a human response weighting function for different degrees of freedom.

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.

TRPM8-Dependent Dynamic Response in a Mathematical Model of Cold Thermoreceptor

PubMed Central

Olivares, Erick; Salgado, Simón; Maidana, Jean Paul; Herrera, Gaspar; Campos, Matías; Madrid, Rodolfo; Orio, Patricio

2015-01-01

Cold-sensitive nerve terminals (CSNTs) encode steady temperatures with regular, rhythmic temperature-dependent firing patterns that range from irregular tonic firing to regular bursting (static response). During abrupt temperature changes, CSNTs show a dynamic response, transiently increasing their firing frequency as temperature decreases and silencing when the temperature increases (dynamic response). To date, mathematical models that simulate the static response are based on two depolarizing/repolarizing pairs of membrane ionic conductance (slow and fast kinetics). However, these models fail to reproduce the dynamic response of CSNTs to rapid changes in temperature and notoriously they lack a specific cold-activated conductance such as the TRPM8 channel. We developed a model that includes TRPM8 as a temperature-dependent conductance with a calcium-dependent desensitization. We show by computer simulations that it appropriately reproduces the dynamic response of CSNTs from mouse cornea, while preserving their static response behavior. In this model, the TRPM8 conductance is essential to display a dynamic response. In agreement with experimental results, TRPM8 is also needed for the ongoing activity in the absence of stimulus (i.e. neutral skin temperature). Free parameters of the model were adjusted by an evolutionary optimization algorithm, allowing us to find different solutions. We present a family of possible parameters that reproduce the behavior of CSNTs under different temperature protocols. The detection of temperature gradients is associated to a homeostatic mechanism supported by the calcium-dependent desensitization. PMID:26426259

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.

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

PubMed

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

Simultaneously Coupled Mechanical-Electrochemical-Thermal Simulation of Lithium-Ion Cells

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

Zhang, C.; Santhanagopalan, S.; Sprague, M. A.

2016-07-28

Understanding the combined electrochemical-thermal and mechanical response of a system has a variety of applications, for example, structural failure from electrochemical fatigue and the potential induced changes of material properties. For lithium-ion batteries, there is an added concern over the safety of the system in the event of mechanical failure of the cell components. In this work, we present a generic multi-scale simultaneously coupled mechanical-electrochemical-thermal model to examine the interaction between mechanical failure and electrochemical-thermal responses. We treat the battery cell as a homogeneous material while locally we explicitly solve for the mechanical response of individual components using a homogenizationmore » model and the electrochemical-thermal responses using an electrochemical model for the battery. A benchmark problem is established to demonstrate the proposed modeling framework. The model shows the capability to capture the gradual evolution of cell electrochemical-thermal responses, and predicts the variation of those responses under different short-circuit conditions.« less

Simultaneously Coupled Mechanical-Electrochemical-Thermal Simulation of Lithium-Ion Cells: Preprint

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

Zhang, Chao; Santhanagopalan, Shriram; Sprague, Michael A.

2016-08-01

Understanding the combined electrochemical-thermal and mechanical response of a system has a variety of applications, for example, structural failure from electrochemical fatigue and the potential induced changes of material properties. For lithium-ion batteries, there is an added concern over the safety of the system in the event of mechanical failure of the cell components. In this work, we present a generic multi-scale simultaneously coupled mechanical-electrochemical-thermal model to examine the interaction between mechanical failure and electrochemical-thermal responses. We treat the battery cell as a homogeneous material while locally we explicitly solve for the mechanical response of individual components using a homogenizationmore » model and the electrochemical-thermal responses using an electrochemical model for the battery. A benchmark problem is established to demonstrate the proposed modeling framework. The model shows the capability to capture the gradual evolution of cell electrochemical-thermal responses, and predicts the variation of those responses under different short-circuit conditions.« less

Unification of color postprocessing techniques for 3-dimensional computational mechanics

NASA Technical Reports Server (NTRS)

Bailey, Bruce Charles

1985-01-01

To facilitate the understanding of complex three-dimensional numerical models, advanced interactive color postprocessing techniques are introduced. These techniques are sufficiently flexible so that postprocessing difficulties arising from model size, geometric complexity, response variation, and analysis type can be adequately overcome. Finite element, finite difference, and boundary element models may be evaluated with the prototype postprocessor. Elements may be removed from parent models to be studied as independent subobjects. Discontinuous responses may be contoured including responses which become singular, and nonlinear color scales may be input by the user for the enhancement of the contouring operation. Hit testing can be performed to extract precise geometric, response, mesh, or material information from the database. In addition, stress intensity factors may be contoured along the crack front of a fracture model. Stepwise analyses can be studied, and the user can recontour responses repeatedly, as if he were paging through the response sets. As a system, these tools allow effective interpretation of complex analysis results.

NLTE steady-state response matrix method.

NASA Astrophysics Data System (ADS)

Faussurier, G.; More, R. M.

2000-05-01

A connection between atomic kinetics and non-equilibrium thermodynamics has been recently established by using a collisional-radiative model modified to include line absorption. The calculated net emission can be expressed as a non-local thermodynamic equilibrium (NLTE) symmetric response matrix. In the paper, this connection is extended to both cases of the average-atom model and the Busquet's model (RAdiative-Dependent IOnization Model, RADIOM). The main properties of the response matrix still remain valid. The RADIOM source function found in the literature leads to a diagonal response matrix, stressing the absence of any frequency redistribution among the frequency groups at this order of calculation.

Modeling of biodynamic responses distributed at the fingers and the palm of the human hand-arm system.

PubMed

Dong, Ren G; Dong, Jennie H; Wu, John Z; Rakheja, Subhash

2007-01-01

The objective of this study is to develop analytical models for simulating driving-point biodynamic responses distributed at the fingers and palm of the hand under vibration along the forearm direction (z(h)-axis). Two different clamp-like model structures are formulated to analyze the distributed responses at the fingers-handle and palm-handle interfaces, as opposed to the single driving point invariably considered in the reported models. The parameters of the proposed four- and five degrees-of-freedom models are identified through minimization of an rms error function of the model and measured responses under different hand actions, namely, fingers pull, push only, grip only, and combined push and grip. The results show that the responses predicted from both models agree reasonably well with the measured data in terms of distributed as well total impedance magnitude and phase. The variations in the identified model parameters under different hand actions are further discussed in view of the biological system behavior. The proposed models are considered to serve as useful tools for design and assessment of vibration isolation methods, and for developing a hand-arm simulator for vibration analysis of power tools.

Mutual information and the fidelity of response of gene regulatory models

NASA Astrophysics Data System (ADS)

Tabbaa, Omar P.; Jayaprakash, C.

2014-08-01

We investigate cellular response to extracellular signals by using information theory techniques motivated by recent experiments. We present results for the steady state of the following gene regulatory models found in both prokaryotic and eukaryotic cells: a linear transcription-translation model and a positive or negative auto-regulatory model. We calculate both the information capacity and the mutual information exactly for simple models and approximately for the full model. We find that (1) small changes in mutual information can lead to potentially important changes in cellular response and (2) there are diminishing returns in the fidelity of response as the mutual information increases. We calculate the information capacity using Gillespie simulations of a model for the TNF-α-NF-κ B network and find good agreement with the measured value for an experimental realization of this network. Our results provide a quantitative understanding of the differences in cellular response when comparing experimentally measured mutual information values of different gene regulatory models. Our calculations demonstrate that Gillespie simulations can be used to compute the mutual information of more complex gene regulatory models, providing a potentially useful tool in synthetic biology.

A Review: Development of a Microdose Model for Analysis of Adaptive Response and Bystander Dose Response Behavior

PubMed Central

Leonard, Bobby E.

2008-01-01

Prior work has provided incremental phases to a microdosimetry modeling program to describe the dose response behavior of the radio-protective adaptive response effect. We have here consolidated these prior works (Leonard 2000, 2005, 2007a, 2007b, 2007c) to provide a composite, comprehensive Microdose Model that is also herein modified to include the bystander effect. The nomenclature for the model is also standardized for the benefit of the experimental cellular radio-biologist. It extends the prior work to explicitly encompass separately the analysis of experimental data that is 1.) only dose dependent and reflecting only adaptive response radio-protection, 2.) both dose and dose-rate dependent data and reflecting only adaptive response radio-protection for spontaneous and challenge dose damage, 3.) only dose dependent data and reflecting both bystander deleterious damage and adaptive response radio-protection (AR-BE model). The Appendix cites the various applications of the model. Here we have used the Microdose Model to analyze the, much more human risk significant, Elmore et al (2006) data for the dose and dose rate influence on the adaptive response radio-protective behavior of HeLa x Skin cells for naturally occurring, spontaneous chromosome damage from a Brachytherapy type 125I photon radiation source. We have also applied the AR-BE Microdose Model to the Chromosome inversion data of Hooker et al (2004) reflecting both low LET bystander and adaptive response effects. The micro-beam facility data of Miller et al (1999), Nagasawa and Little (1999) and Zhou et al (2003) is also examined. For the Zhou et al (2003) data, we use the AR-BE model to estimate the threshold for adaptive response reduction of the bystander effect. The mammogram and diagnostic X-ray induction of AR and protective BE are observed. We show that bystander damage is reduced in the similar manner as spontaneous and challenge dose damage as shown by the Azzam et al (1996) data. We cite primary unresolved questions regarding adaptive response behavior and bystander behavior. The five features of major significance provided by the Microdose Model so far are 1.) Single Specific Energy Hits initiate Adaptive Response, 2.) Mammogram and diagnostic X-rays induce a protective Bystander Effect as well as Adaptive Response radio-protection. 3.) For mammogram X-rays the Adaptive Response protection is retained at high primer dose levels. 4.) The dose range of the AR protection depends on the value of the Specific Energy per Hit, . 5.) Alpha particle induced deleterious Bystander damage is modulated by low LET radiation. PMID:18648579

Modeling rate sensitivity of exercise transient responses to limb motion.

PubMed

Yamashiro, Stanley M; Kato, Takahide

2014-10-01

Transient responses of ventilation (V̇e) to limb motion can exhibit predictive characteristics. In response to a change in limb motion, a rapid change in V̇e is commonly observed with characteristics different than during a change in workload. This rapid change has been attributed to a feed-forward or adaptive response. Rate sensitivity was explored as a specific hypothesis to explain predictive V̇e responses to limb motion. A simple model assuming an additive feed-forward summation of V̇e proportional to the rate of change of limb motion was studied. This model was able to successfully account for the adaptive phase correction observed during human sinusoidal changes in limb motion. Adaptation of rate sensitivity might also explain the reduction of the fast component of V̇e responses previously reported following sudden exercise termination. Adaptation of the fast component of V̇e response could occur by reduction of rate sensitivity. Rate sensitivity of limb motion was predicted by the model to reduce the phase delay between limb motion and V̇e response without changing the steady-state response to exercise load. In this way, V̇e can respond more quickly to an exercise change without interfering with overall feedback control. The asymmetry between responses to an incremental and decremental ramp change in exercise can also be accounted for by the proposed model. Rate sensitivity leads to predicted behavior, which resembles responses observed in exercise tied to expiratory reserve volume. Copyright © 2014 the American Physiological Society.

Climate Change Effects on Agriculture: Economic Responses to Biophysical Shocks

NASA Technical Reports Server (NTRS)

Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlik, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina

2014-01-01

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(sup 2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Climate change effects on agriculture: Economic responses to biophysical shocks

PubMed Central

Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d’Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-01-01

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. PMID:24344285

Climate change effects on agriculture: economic responses to biophysical shocks.

PubMed

Nelson, Gerald C; Valin, Hugo; Sands, Ronald D; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d'Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-03-04

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

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.…

The Social Responsibility Performance Outcomes Model: Building Socially Responsible Companies through Performance Improvement Outcomes.

ERIC Educational Resources Information Center

Hatcher, Tim

2000-01-01

Considers the role of performance improvement professionals and human resources development professionals in helping organizations realize the ethical and financial power of corporate social responsibility. Explains the social responsibility performance outcomes model, which incorporates the concepts of societal needs and outcomes. (LRW)

Bayesian Estimation of Multi-Unidimensional Graded Response IRT Models

ERIC Educational Resources Information Center

Kuo, Tzu-Chun

2015-01-01

Item response theory (IRT) has gained an increasing popularity in large-scale educational and psychological testing situations because of its theoretical advantages over classical test theory. Unidimensional graded response models (GRMs) are useful when polytomous response items are designed to measure a unified latent trait. They are limited in…

SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model

NASA Astrophysics Data System (ADS)

Grelle, G.; Bonito, L.; Lampasi, A.; Revellino, P.; Guerriero, L.; Sappa, G.; Guadagno, F. M.

2015-06-01

SiSeRHMap is a computerized methodology capable of drawing up prediction maps of seismic response. It was realized on the basis of a hybrid model which combines different approaches and models in a new and non-conventional way. These approaches and models are organized in a code-architecture composed of five interdependent modules. A GIS (Geographic Information System) Cubic Model (GCM), which is a layered computational structure based on the concept of lithodynamic units and zones, aims at reproducing a parameterized layered subsoil model. A metamodeling process confers a hybrid nature to the methodology. In this process, the one-dimensional linear equivalent analysis produces acceleration response spectra of shear wave velocity-thickness profiles, defined as trainers, which are randomly selected in each zone. Subsequently, a numerical adaptive simulation model (Spectra) is optimized on the above trainer acceleration response spectra by means of a dedicated Evolutionary Algorithm (EA) and the Levenberg-Marquardt Algorithm (LMA) as the final optimizer. In the final step, the GCM Maps Executor module produces a serial map-set of a stratigraphic seismic response at different periods, grid-solving the calibrated Spectra model. In addition, the spectra topographic amplification is also computed by means of a numerical prediction model. This latter is built to match the results of the numerical simulations related to isolate reliefs using GIS topographic attributes. In this way, different sets of seismic response maps are developed, on which, also maps of seismic design response spectra are defined by means of an enveloping technique.

An Evaluation of Three Approximate Item Response Theory Models for Equating Test Scores.

ERIC Educational Resources Information Center

Marco, Gary L.; And Others

Three item response models were evaluated for estimating item parameters and equating test scores. The models, which approximated the traditional three-parameter model, included: (1) the Rasch one-parameter model, operationalized in the BICAL computer program; (2) an approximate three-parameter logistic model based on coarse group data divided…

Dynamic response tests of inertial and optical wind-tunnel model attitude measurement devices

NASA Technical Reports Server (NTRS)

Buehrle, R. D.; Young, C. P., Jr.; Burner, A. W.; Tripp, J. S.; Tcheng, P.; Finley, T. D.; Popernack, T. G., Jr.

1995-01-01

Results are presented for an experimental study of the response of inertial and optical wind-tunnel model attitude measurement systems in a wind-off simulated dynamic environment. This study is part of an ongoing activity at the NASA Langley Research Center to develop high accuracy, advanced model attitude measurement systems that can be used in a dynamic wind-tunnel environment. This activity was prompted by the inertial model attitude sensor response observed during high levels of model vibration which results in a model attitude measurement bias error. Significant bias errors in model attitude measurement were found for the measurement using the inertial device during wind-off dynamic testing of a model system. The amount of bias present during wind-tunnel tests will depend on the amplitudes of the model dynamic response and the modal characteristics of the model system. Correction models are presented that predict the vibration-induced bias errors to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment. The optical system results were uncorrupted by model vibration in the laboratory setup.

Frequency Response of Synthetic Vocal Fold Models with Linear and Nonlinear Material Properties

PubMed Central

Shaw, Stephanie M.; Thomson, Scott L.; Dromey, Christopher; Smith, Simeon

2014-01-01

Purpose The purpose of this study was to create synthetic vocal fold models with nonlinear stress-strain properties and to investigate the effect of linear versus nonlinear material properties on fundamental frequency during anterior-posterior stretching. Method Three materially linear and three materially nonlinear models were created and stretched up to 10 mm in 1 mm increments. Phonation onset pressure (Pon) and fundamental frequency (F0) at Pon were recorded for each length. Measurements were repeated as the models were relaxed in 1 mm increments back to their resting lengths, and tensile tests were conducted to determine the stress-strain responses of linear versus nonlinear models. Results Nonlinear models demonstrated a more substantial frequency response than did linear models and a more predictable pattern of F0 increase with respect to increasing length (although range was inconsistent across models). Pon generally increased with increasing vocal fold length for nonlinear models, whereas for linear models, Pon decreased with increasing length. Conclusions Nonlinear synthetic models appear to more accurately represent the human vocal folds than linear models, especially with respect to F0 response. PMID:22271874

Frequency response of synthetic vocal fold models with linear and nonlinear material properties.

PubMed

Shaw, Stephanie M; Thomson, Scott L; Dromey, Christopher; Smith, Simeon

2012-10-01

The purpose of this study was to create synthetic vocal fold models with nonlinear stress-strain properties and to investigate the effect of linear versus nonlinear material properties on fundamental frequency (F0) during anterior-posterior stretching. Three materially linear and 3 materially nonlinear models were created and stretched up to 10 mm in 1-mm increments. Phonation onset pressure (Pon) and F0 at Pon were recorded for each length. Measurements were repeated as the models were relaxed in 1-mm increments back to their resting lengths, and tensile tests were conducted to determine the stress-strain responses of linear versus nonlinear models. Nonlinear models demonstrated a more substantial frequency response than did linear models and a more predictable pattern of F0 increase with respect to increasing length (although range was inconsistent across models). Pon generally increased with increasing vocal fold length for nonlinear models, whereas for linear models, Pon decreased with increasing length. Nonlinear synthetic models appear to more accurately represent the human vocal folds than do linear models, especially with respect to F0 response.

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.

ELM control with RMP: plasma response models and the role of edge peeling response

NASA Astrophysics Data System (ADS)

Liu, Yueqiang; Ham, C. J.; Kirk, A.; Li, Li; Loarte, A.; Ryan, D. A.; Sun, Youwen; Suttrop, W.; Yang, Xu; Zhou, Lina

2016-11-01

Resonant magnetic perturbations (RMP) have extensively been demonstrated as a plausible technique for mitigating or suppressing large edge localized modes (ELMs). Associated with this is a substantial amount of theory and modelling efforts during recent years. Various models describing the plasma response to the RMP fields have been proposed in the literature, and are briefly reviewed in this work. Despite their simplicity, linear response models can provide alternative criteria, than the vacuum field based criteria, for guiding the choice of the coil configurations to achieve the best control of ELMs. The role of the edge peeling response to the RMP fields is illustrated as a key indicator for the ELM mitigation in low collisionality plasmas, in various tokamak devices.

An AgMIP framework for improved agricultural representation in integrated assessment models

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

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agriculturalmore » Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.« less

An AgMIP framework for improved agricultural representation in integrated assessment models

NASA Astrophysics Data System (ADS)

Ruane, Alex C.; Rosenzweig, Cynthia; Asseng, Senthold; Boote, Kenneth J.; Elliott, Joshua; Ewert, Frank; Jones, James W.; Martre, Pierre; McDermid, Sonali P.; Müller, Christoph; Snyder, Abigail; Thorburn, Peter J.

2017-12-01

Integrated assessment models (IAMs) hold great potential to assess how future agricultural systems will be shaped by socioeconomic development, technological innovation, and changing climate conditions. By coupling with climate and crop model emulators, IAMs have the potential to resolve important agricultural feedback loops and identify unintended consequences of socioeconomic development for agricultural systems. Here we propose a framework to develop robust representation of agricultural system responses within IAMs, linking downstream applications with model development and the coordinated evaluation of key climate responses from local to global scales. We survey the strengths and weaknesses of protocol-based assessments linked to the Agricultural Model Intercomparison and Improvement Project (AgMIP), each utilizing multiple sites and models to evaluate crop response to core climate changes including shifts in carbon dioxide concentration, temperature, and water availability, with some studies further exploring how climate responses are affected by nitrogen levels and adaptation in farm systems. Site-based studies with carefully calibrated models encompass the largest number of activities; however they are limited in their ability to capture the full range of global agricultural system diversity. Representative site networks provide more targeted response information than broadly-sampled networks, with limitations stemming from difficulties in covering the diversity of farming systems. Global gridded crop models provide comprehensive coverage, although with large challenges for calibration and quality control of inputs. Diversity in climate responses underscores that crop model emulators must distinguish between regions and farming system while recognizing model uncertainty. Finally, to bridge the gap between bottom-up and top-down approaches we recommend the deployment of a hybrid climate response system employing a representative network of sites to bias-correct comprehensive gridded simulations, opening the door to accelerated development and a broad range of applications.

Assessment of Response Surface Models using Independent Confirmation Point Analysis

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2010-01-01

This paper highlights various advantages that confirmation-point residuals have over conventional model design-point residuals in assessing the adequacy of a response surface model fitted by regression techniques to a sample of experimental data. Particular advantages are highlighted for the case of design matrices that may be ill-conditioned for a given sample of data. The impact of both aleatory and epistemological uncertainty in response model adequacy assessments is considered.

Teaching Personal and Social Responsibility Model-Based Programmes in Physical Education: A Systematic Review

ERIC Educational Resources Information Center

Pozo, Pablo; Grao-Cruces, Alberto; Pérez-Ordás, Raquel

2018-01-01

The purpose of this study was to conduct a review of research on the Teaching Personal and Social Responsibility model-based programme within physical education. Papers selected for analysis were found through searches of Web of Science, SportDiscus (EBSCO), SCOPUS, and ERIC (ProQuest) databases. The keywords "responsibility model" and…

Bridging Scientific Model Outputs with Emergency Response Needs in Catastrophic Earthquake Responses

ERIC Educational Resources Information Center

Johannes, Tay W.

2010-01-01

In emergency management, scientific models are widely used for running hazard simulations and estimating losses often in support of planning and mitigation efforts. This work expands utility of the scientific model into the response phase of emergency management. The focus is on the common operating picture as it gives context to emergency…

Detecting Aberrant Response Patterns in the Rasch Model. Rapport 87-3.

ERIC Educational Resources Information Center

Kogut, Jan

In this paper, the detection of response patterns aberrant from the Rasch model is considered. For this purpose, a new person fit index, recently developed by I. W. Molenaar (1987) and an iterative estimation procedure are used in a simulation study of Rasch model data mixed with aberrant data. Three kinds of aberrant response behavior are…

Item Response Models for Examinee-Selected Items

ERIC Educational Resources Information Center

Wang, Wen-Chung; Jin, Kuan-Yu; Qiu, Xue-Lan; Wang, Lei

2012-01-01

In some tests, examinees are required to choose a fixed number of items from a set of given items to answer. This practice creates a challenge to standard item response models, because more capable examinees may have an advantage by making wiser choices. In this study, we developed a new class of item response models to account for the choice…

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…

An NCME Instructional Module on Latent DIF Analysis Using Mixture Item Response Models

ERIC Educational Resources Information Center

Cho, Sun-Joo; Suh, Youngsuk; Lee, Woo-yeol

2016-01-01

The purpose of this ITEMS module is to provide an introduction to differential item functioning (DIF) analysis using mixture item response models. The mixture item response models for DIF analysis involve comparing item profiles across latent groups, instead of manifest groups. First, an overview of DIF analysis based on latent groups, called…

Recovery of Graded Response Model Parameters: A Comparison of Marginal Maximum Likelihood and Markov Chain Monte Carlo Estimation

ERIC Educational Resources Information Center

Kieftenbeld, Vincent; Natesan, Prathiba

2012-01-01

Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…

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…

White Complicity and Social Justice Education: Can One Be Culpable without Being Liable?

ERIC Educational Resources Information Center

Applebaum, Barbara

2007-01-01

In part of an ongoing study of white complicity, moral responsibility, and moral agency in social justice education, Barbara Applebaum asks in this essay what model or models of moral responsibility can help white students recognize their white complicity and which models of moral responsibility obscure such acknowledgment. To address this…

An Extension of Least Squares Estimation of IRT Linking Coefficients for the Graded Response Model

ERIC Educational Resources Information Center

Kim, Seonghoon

2010-01-01

The three types (generalized, unweighted, and weighted) of least squares methods, proposed by Ogasawara, for estimating item response theory (IRT) linking coefficients under dichotomous models are extended to the graded response model. A simulation study was conducted to confirm the accuracy of the extended formulas, and a real data study was…

Partially Testing a Process Model for Understanding Victim Responses to an Anticipated Worksite Closure

ERIC Educational Resources Information Center

Blau, Gary

2007-01-01

This study partially tested a recent process model for understanding victim responses to worksite/function closure (W/FC) proposed by Blau [Blau, G. (2006). A process model for understanding victim responses to worksite/function closure. "Human Resource Management Review," 16, 12-28], in a pharmaceutical manufacturing site. Central to the model…

Model Choice and Sample Size in Item Response Theory Analysis of Aphasia Tests

ERIC Educational Resources Information Center

Hula, William D.; Fergadiotis, Gerasimos; Martin, Nadine

2012-01-01

Purpose: The purpose of this study was to identify the most appropriate item response theory (IRT) measurement model for aphasia tests requiring 2-choice responses and to determine whether small samples are adequate for estimating such models. Method: Pyramids and Palm Trees (Howard & Patterson, 1992) test data that had been collected from…

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

NASA Technical Reports Server (NTRS)

Frady, Gregory P.; Duvall, Lowery D.; Fulcher, Clay W. G.; Laverde, Bruce T.; Hunt, Ronald A.

2011-01-01

A rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for a curved orthogrid panel typical of launch vehicle skin structures. Several test article configurations were produced by adding component equipment of differing weights to the flight-like vehicle panel. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was employed to describe the assumed correlation of phased input sound pressures across the energized panel. This application demonstrates the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software modules developed for the RPTF method can be easily adapted for quick replacement of the diffuse acoustic field with other pressure field models; for example a turbulent boundary layer (TBL) model suitable for vehicle ascent. Wind tunnel tests have been proposed to anchor the predictions and provide new insight into modeling approaches for this type of environment. Finally, component vibration environments for design were developed from the measured and predicted responses and compared with those derived from traditional techniques such as Barrett scaling methods for unloaded and component-loaded panels.

Implementation of the zooplankton functional response in plankton models: State of the art, recent challenges and future directions

NASA Astrophysics Data System (ADS)

Morozov, Andrew; Poggiale, Jean-Christophe; Cordoleani, Flora

2012-09-01

The conventional way of describing grazing in plankton models is based on a zooplankton functional response framework, according to which the consumption rate is computed as the product of a certain function of food (the functional response) and the density/biomass of herbivorous zooplankton. A large amount of literature on experimental feeding reports the existence of a zooplankton functional response in microcosms and small mesocosms, which goes a long way towards explaining the popularity of this framework both in mean-field (e.g. NPZD models) and spatially resolved models. On the other hand, the complex foraging behaviour of zooplankton (feeding cycles) as well as spatial heterogeneity of food and grazer distributions (plankton patchiness) across time and space scales raise questions as to the existence of a functional response of herbivores in vivo. In the current review, we discuss limitations of the ‘classical’ zooplankton functional response and consider possible ways to amend this framework to cope with the complexity of real planktonic ecosystems. Our general conclusion is that although the functional response of herbivores often does not exist in real ecosystems (especially in the form observed in the laboratory), this framework can be rather useful in modelling - but it does need some amendment which can be made based on various techniques of model reduction. We also show that the shape of the functional response depends on the spatial resolution (‘frame’) of the model. We argue that incorporating foraging behaviour and spatial heterogeneity in plankton models would not necessarily require the use of individual based modelling - an approach which is now becoming dominant in the literature. Finally, we list concrete future directions and challenges and emphasize the importance of a closer collaboration between plankton biologists and modellers in order to make further progress towards better descriptions of zooplankton grazing.

Pattern Adaptation and Normalization Reweighting.

PubMed

Westrick, Zachary M; Heeger, David J; Landy, Michael S

2016-09-21

Adaptation to an oriented stimulus changes both the gain and preferred orientation of neural responses in V1. Neurons tuned near the adapted orientation are suppressed, and their preferred orientations shift away from the adapter. We propose a model in which weights of divisive normalization are dynamically adjusted to homeostatically maintain response products between pairs of neurons. We demonstrate that this adjustment can be performed by a very simple learning rule. Simulations of this model closely match existing data from visual adaptation experiments. We consider several alternative models, including variants based on homeostatic maintenance of response correlations or covariance, as well as feedforward gain-control models with multiple layers, and we demonstrate that homeostatic maintenance of response products provides the best account of the physiological data. Adaptation is a phenomenon throughout the nervous system in which neural tuning properties change in response to changes in environmental statistics. We developed a model of adaptation that combines normalization (in which a neuron's gain is reduced by the summed responses of its neighbors) and Hebbian learning (in which synaptic strength, in this case divisive normalization, is increased by correlated firing). The model is shown to account for several properties of adaptation in primary visual cortex in response to changes in the statistics of contour orientation. Copyright © 2016 the authors 0270-6474/16/369805-12$15.00/0.

Mathematical Modeling of Allelopathy. III. A Model for Curve-Fitting Allelochemical Dose Responses

PubMed Central

Liu, De Li; An, Min; Johnson, Ian R.; Lovett, John V.

2003-01-01

Bioassay techniques are often used to study the effects of allelochemicals on plant processes, and it is generally observed that the processes are stimulated at low allelochemical concentrations and inhibited as the concentrations increase. A simple empirical model is presented to analyze this type of response. The stimulation-inhibition properties of allelochemical-dose responses can be described by the parameters in the model. The indices, p% reductions, are calculated to assess the allelochemical effects. The model is compared with experimental data for the response of lettuce seedling growth to Centaurepensin, the olfactory response of weevil larvae to α-terpineol, and the responses of annual ryegrass (Lolium multiflorum Lam.), creeping red fescue (Festuca rubra L., cv. Ensylva), Kentucky bluegrass (Poa pratensis L., cv. Kenblue), perennial ryegrass (L. perenne L., cv. Manhattan), and Rebel tall fescue (F. arundinacea Schreb) seedling growth to leachates of Rebel and Kentucky 31 tall fescue. The results show that the model gives a good description to observations and can be used to fit a wide range of dose responses. Assessments of the effects of leachates of Rebel and Kentucky 31 tall fescue clearly differentiate the properties of the allelopathic sources and the relative sensitivities of indicators such as the length of root and leaf. PMID:19330111

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

PubMed

Dong, Xu; Foteinou, Panagiota T; Calvano, Steven E; Lowry, Stephen F; Androulakis, Ioannis P

2010-02-18

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

A Multidimensional Ideal Point Item Response Theory Model for Binary Data.

PubMed

Maydeu-Olivares, Albert; Hernández, Adolfo; McDonald, Roderick P

2006-12-01

We introduce a multidimensional item response theory (IRT) model for binary data based on a proximity response mechanism. Under the model, a respondent at the mode of the item response function (IRF) endorses the item with probability one. The mode of the IRF is the ideal point, or in the multidimensional case, an ideal hyperplane. The model yields closed form expressions for the cell probabilities. We estimate and test the goodness of fit of the model using only information contained in the univariate and bivariate moments of the data. Also, we pit the new model against the multidimensional normal ogive model estimated using NOHARM in four applications involving (a) attitudes toward censorship, (b) satisfaction with life, (c) attitudes of morality and equality, and (d) political efficacy. The normal PDF model is not invariant to simple operations such as reverse scoring. Thus, when there is no natural category to be modeled, as in many personality applications, it should be fit separately with and without reverse scoring for comparisons.

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.

Parental modelling and prompting effects on acceptance of a novel fruit in 2-4-year-old children are dependent on children's food responsiveness.

PubMed

Blissett, Jackie; Bennett, Carmel; Fogel, Anna; Harris, Gillian; Higgs, Suzanne

2016-02-14

Few children consume the recommended portions of fruit or vegetables. This study examined the effects of parental physical prompting and parental modelling in children's acceptance of a novel fruit (NF) and examined the role of children's food-approach and food-avoidance traits on NF engagement and consumption. A total of 120 caregiver-child dyads (fifty-four girls, sixty-six boys) participated in this study. Dyads were allocated to one of the following three conditions: physical prompting but no modelling, physical prompting and modelling or a modelling only control condition. Dyads ate a standardised meal containing a portion of a fruit new to the child. Parents completed measures of children's food approach and avoidance. Willingness to try the NF was observed, and the amount of the NF consumed was measured. Physical prompting but no modelling resulted in greater physical refusal of the NF. There were main effects of enjoyment of food and food fussiness on acceptance. Food responsiveness interacted with condition such that children who were more food responsive had greater NF acceptance in the prompting and modelling conditions in comparison with the modelling only condition. In contrast, children with low food responsiveness had greater acceptance in the modelling control condition than in the prompting but no modelling condition. Physical prompting in the absence of modelling is likely to be detrimental to NF acceptance. Parental use of physical prompting strategies, in combination with modelling of NF intake, may facilitate acceptance of NF, but only in food-responsive children. Modelling consumption best promotes acceptance in children with low food responsiveness.

Attenuation of empennage buffet response through active control of damping using piezoelectric material

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Miller, Jonathan M.; Doggett, Robert V., Jr.

1993-01-01

Dynamic response and damping data obtained from buffet studies conducted in a low-speed wind tunnel by using a simple, rigid model attached to spring supports are presented. The two parallel leaf spring supports provided a means for the model to respond in a vertical translation mode, thus simulating response in an elastic first bending mode. Wake-induced buffeting flow was created by placing an airfoil upstream of the model of that the wake of the airfoil impinged on the model. Model response was sensed by a strain gage mounted on one of the springs. The output signal from the strain gage was fed back through a control law implemented on a desktop computer. The processed signals were used to 'actuate' a piezoelectric bending actuator bonded to the other spring in such a way as to add damping as the model responded. The results of this 'proof-of-concept' study show that the piezoelectric actuator was effective in attenuating the wake-induced buffet response over the range of parameters investigated.

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.

Constitutive Modeling of a Glass Fiber-Reinforced PTFE Gasketed-Joint Under a Re-torque

NASA Astrophysics Data System (ADS)

Williams, James; Gordon, Ali P.

Joints gasketed with viscoelastic seals often receive an application of a secondary torque, i.e., retorque, in order to ensure joint tightness and proper sealing. The motivation of this study is to characterize and analytically model the load and deflection re-torque response of a single 25% glass-fiber reinforced polytetrafluorethylene (PTFE) gasket-bolted joint with serrated flange detail. The Burger-type viscoelastic modeling constants of the material are obtained through isolating the gasket from the bolt by performing a gasket creep test via a MTS electromechanical test frame. The re-load creep response is also investigated by re-loading the gasket after a period of initial creep to observe the response. The modeling constants obtained from the creep tests are used with a Burger-type viscoelastic model to predict the re-torque response of a single bolt-gasket test fixture in order to validate the ability of the model to simulate the re-torque response under various loading conditions and flange detail.

Development of Response Spectral Ground Motion Prediction Equations from Empirical Models for Fourier Spectra and Duration of Ground Motion

NASA Astrophysics Data System (ADS)

Bora, S. S.; Scherbaum, F.; Kuehn, N. M.; Stafford, P.; Edwards, B.

2014-12-01

In a probabilistic seismic hazard assessment (PSHA) framework, it still remains a challenge to adjust ground motion prediction equations (GMPEs) for application in different seismological environments. In this context, this study presents a complete framework for the development of a response spectral GMPE easily adjustable to different seismological conditions; and which does not suffer from the technical problems associated with the adjustment in response spectral domain. Essentially, the approach consists of an empirical FAS (Fourier Amplitude Spectrum) model and a duration model for ground motion which are combined within the random vibration theory (RVT) framework to obtain the full response spectral ordinates. Additionally, FAS corresponding to individual acceleration records are extrapolated beyond the frequency range defined by the data using the stochastic FAS model, obtained by inversion as described in Edwards & Faeh, (2013). To that end, an empirical model for a duration, which is tuned to optimize the fit between RVT based and observed response spectral ordinate, at each oscillator frequency is derived. Although, the main motive of the presented approach was to address the adjustability issues of response spectral GMPEs; comparison, of median predicted response spectra with the other regional models indicate that presented approach can also be used as a stand-alone model. Besides that, a significantly lower aleatory variability (σ<0.5 in log units) in comparison to other regional models, at shorter periods brands it to a potentially viable alternative to the classical regression (on response spectral ordinates) based GMPEs for seismic hazard studies in the near future. The dataset used for the presented analysis is a subset of the recently compiled database RESORCE-2012 across Europe, Middle East and the Mediterranean region.

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.

The uses and limitations of the square‐root‐impedance method for computing site amplification

USGS Publications Warehouse

Boore, David

2013-01-01

The square‐root‐impedance (SRI) method is a fast way of computing approximate site amplification that does not depend on the details from velocity models. The SRI method underestimates the peak response of models with large impedance contrasts near their base, but the amplifications for those models is often close to or equal to the root mean square of the theoretical full resonant (FR) response of the higher modes. On the other hand, for velocity models made up of gradients, with no significant impedance changes across small ranges of depth, the SRI method systematically underestimates the theoretical FR response over a wide frequency range. For commonly used gradient models for generic rock sites, the SRI method underestimates the FR response by about 20%–30%. Notwithstanding the persistent underestimation of amplifications from theoretical FR calculations, however, amplifications from the SRI method may often provide more useful estimates of amplifications than the FR method, because the SRI amplifications are not sensitive to details of the models and will not exhibit the many peaks and valleys characteristic of theoretical full resonant amplifications (jaggedness sometimes not seen in amplifications based on averages of site response from multiple recordings at a given site). The lack of sensitivity to details of the velocity models also makes the SRI method useful in comparing the response of various velocity models, in spite of any systematic underestimation of the response. The quarter‐wavelength average velocity, which is fundamental to the SRI method, is useful by itself in site characterization, and as such, is the fundamental parameter used to characterize the site response in a number of recent ground‐motion prediction equations.

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.

Log-Multiplicative Association Models as Item Response Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Yu, Hsiu-Ting

2007-01-01

Log-multiplicative association (LMA) models, which are special cases of log-linear models, have interpretations in terms of latent continuous variables. Two theoretical derivations of LMA models based on item response theory (IRT) arguments are presented. First, we show that Anderson and colleagues (Anderson & Vermunt, 2000; Anderson & Bockenholt,…

Air Quality Response Modeling for Decision Support | Science ...

EPA Pesticide Factsheets

Air quality management relies on photochemical models to predict the responses of pollutant concentrations to changes in emissions. Such modeling is especially important for secondary pollutants such as ozone and fine particulate matter which vary nonlinearly with changes in emissions. Numerous techniques for probing pollutant-emission relationships within photochemical models have been developed and deployed for a variety of decision support applications. However, atmospheric response modeling remains complicated by the challenge of validating sensitivity results against observable data. This manuscript reviews the state of the science of atmospheric response modeling as well as efforts to characterize the accuracy and uncertainty of sensitivity results. The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being use

Reconciling the Observed and Modeled Southern Hemisphere Circulation Response to Volcanic Eruptions

NASA Astrophysics Data System (ADS)

McGraw, M. C.; Barnes, E. A.; Deser, C.

2016-12-01

Confusion exists regarding the tropospheric circulation response to volcanic eruptions, with models and observations seeming to disagree on the sign of the response. The forced Southern Hemisphere circulation response to the eruptions of Pinatubo and El Chichon is shown to be a robust positive annular mode, using over 200 ensemble members from 38 climate models. It is demonstrated that the models and observations are not at odds, but rather, internal climate variability is large and can overwhelm the forced response. It is further argued that the state of ENSO can at least partially explain the sign of the observed anomalies, and may account for the perceived discrepancy between model and observational studies. The eruptions of both El Chichon and Pinatubo occurred during El Nino events, and it is demonstrated that the SAM anomalies following volcanic eruptions are weaker during El Nino events compared to La Nina events.

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

A parameters optimization method for planar joint clearance model and its application for dynamics simulation of reciprocating compressor

NASA Astrophysics Data System (ADS)

Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li

2015-05-01

In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.

Finite Element Aircraft Simulation of Turbulence

NASA Technical Reports Server (NTRS)

McFarland, R. E.

1997-01-01

A turbulence model has been developed for realtime aircraft simulation that accommodates stochastic turbulence and distributed discrete gusts as a function of the terrain. This model is applicable to conventional aircraft, V/STOL aircraft, and disc rotor model helicopter simulations. Vehicle angular activity in response to turbulence is computed from geometrical and temporal relationships rather than by using the conventional continuum approximations that assume uniform gust immersion and low frequency responses. By using techniques similar to those recently developed for blade-element rotor models, the angular-rate filters of conventional turbulence models are not required. The model produces rotational rates as well as air mass translational velocities in response to both stochastic and deterministic disturbances, where the discrete gusts and turbulence magnitudes may be correlated with significant terrain features or ship models. Assuming isotropy, a two-dimensional vertical turbulence field is created. A novel Gaussian interpolation technique is used to distribute vertical turbulence on the wing span or lateral rotor disc, and this distribution is used to compute roll responses. Air mass velocities are applied at significant centers of pressure in the computation of the aircraft's pitch and roll responses.

Suppression of antigen-specific lymphocyte activation in modeled microgravity

NASA Technical Reports Server (NTRS)

Cooper, D.; Pride, M. W.; Brown, E. L.; Risin, D.; Pellis, N. R.; McIntire, L. V. (Principal Investigator)

2001-01-01

Various parameters of immune suppression are observed in lymphocytes from astronauts during and after a space flight. It is difficult to ascribe this suppression to microgravity effects on immune cells in crew specimens, due to the complex physiological response to space flight and the resultant effect on in vitro immune performance. Use of isolated immune cells in true and modeled microgravity in immune performance tests, suggests a direct effect of microgravity on in vitro cellular function. Specifically, polyclonal activation of T-cells is severely suppressed in true and modeled microgravity. These recent findings suggest a potential suppression of oligoclonal antigen-specific lymphocyte activation in microgravity. We utilized rotating wall vessel (RWV) bioreactors as an analog of microgravity for cell cultures to analyze three models of antigen-specific activation. A mixed-lymphocyte reaction, as a model for a primary immune response, a tetanus toxoid response and a Borrelia burgdorferi response, as models of a secondary immune response, were all suppressed in the RWV bioreactor. Our findings confirm that the suppression of activation observed with polyclonal models also encompasses oligoclonal antigen-specific activation.

Computational modeling of the human auditory periphery: Auditory-nerve responses, evoked potentials and hearing loss.

PubMed

Verhulst, Sarah; Altoè, Alessandro; Vasilkov, Viacheslav

2018-03-01

Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descriptions of cellular components into human auditory models because single-cell data stems from invasive animal recordings while human reference data only exists in the form of population responses (e.g., otoacoustic emissions, auditory evoked potentials). To embed physiological models within a comprehensive human auditory periphery framework, it is important to capitalize on the success of basic functional models of hearing and render their descriptions more biophysical where possible. At the same time, comprehensive models should capture a variety of key auditory features, rather than fitting their parameters to a single reference dataset. In this study, we review and improve existing models of the IHC-AN complex by updating their equations and expressing their fitting parameters into biophysical quantities. The quality of the model framework for human auditory processing is evaluated using recorded auditory brainstem response (ABR) and envelope-following response (EFR) reference data from normal and hearing-impaired listeners. We present a model with 12 fitting parameters from the cochlea to the brainstem that can be rendered hearing impaired to simulate how cochlear gain loss and synaptopathy affect human population responses. The model description forms a compromise between capturing well-described single-unit IHC and AN properties and human population response features. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Nursing resources and responsibilities according to hospital organizational model for management of inflammatory bowel disease in Spain.

PubMed

Marín, Laura; Torrejón, Antonio; Oltra, Lorena; Seoane, Montserrat; Hernández-Sampelayo, Paloma; Vera, María Isabel; Casellas, Francesc; Alfaro, Noelia; Lázaro, Pablo; García-Sánchez, Valle

2011-06-01

Nurses play an important role in the multidisciplinary management of inflammatory bowel disease (IBD), but little is known about this role and the associated resources. To improve knowledge of resource availability for health care activities and the different organizational models in managing IBD in Spain. Cross-sectional study with data obtained by questionnaire directed at Spanish Gastroenterology Services (GS). Five GS models were identified according to whether they have: no specific service for IBD management (Model A); IBD outpatient office for physician consultations (Model B); general outpatient office for nurse consultations (Model C); both, Model B and Model C (Model D); and IBD Unit (Model E) when the hospital has a Comprehensive Care Unit for IBD with telephone helpline, computer, including a Model B. Available resources and activities performed were compared according to GS model (chi-square test and test for linear trend). Responses were received from 107 GS: 33 Model A (31%), 38 Model B (36%), 4 Model C (4%), 16 Model D (15%) and 16 Model E (15%). The model in which nurses have the most resources and responsibilities is the Model E. The more complete the organizational model, the more frequent the availability of nursing resources (educational material, databases, office, and specialized software) and responsibilities (management of walk-in appointments, provision of emotional support, health education, follow-up of drug treatment and treatment adherence) (p<0.05). Nurses have more resources and responsibilities the more complete is the organizational model for IBD management. Development of these areas may improve patient outcomes. Copyright © 2011 European Crohn's and Colitis Organisation. Published by Elsevier B.V. All rights reserved.

A Comparison of Dose-Response Models for the Parotid Gland in a Large Group of Head-and-Neck Cancer Patients

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

Houweling, Antonetta C., E-mail: A.Houweling@umcutrecht.n; Philippens, Marielle E.P.; Dijkema, Tim

2010-03-15

Purpose: The dose-response relationship of the parotid gland has been described most frequently using the Lyman-Kutcher-Burman model. However, various other normal tissue complication probability (NTCP) models exist. We evaluated in a large group of patients the value of six NTCP models that describe the parotid gland dose response 1 year after radiotherapy. Methods and Materials: A total of 347 patients with head-and-neck tumors were included in this prospective parotid gland dose-response study. The patients were treated with either conventional radiotherapy or intensity-modulated radiotherapy. Dose-volume histograms for the parotid glands were derived from three-dimensional dose calculations using computed tomography scans. Stimulatedmore » salivary flow rates were measured before and 1 year after radiotherapy. A threshold of 25% of the pretreatment flow rate was used to define a complication. The evaluated models included the Lyman-Kutcher-Burman model, the mean dose model, the relative seriality model, the critical volume model, the parallel functional subunit model, and the dose-threshold model. The goodness of fit (GOF) was determined by the deviance and a Monte Carlo hypothesis test. Ranking of the models was based on Akaike's information criterion (AIC). Results: None of the models was rejected based on the evaluation of the GOF. The mean dose model was ranked as the best model based on the AIC. The TD{sub 50} in these models was approximately 39 Gy. Conclusions: The mean dose model was preferred for describing the dose-response relationship of the parotid gland.« less

Statistical Comparison of Spike Responses to Natural Stimuli in Monkey Area V1 With Simulated Responses of a Detailed Laminar Network Model for a Patch of V1

PubMed Central

Schuch, Klaus; Logothetis, Nikos K.; Maass, Wolfgang

2011-01-01

A major goal of computational neuroscience is the creation of computer models for cortical areas whose response to sensory stimuli resembles that of cortical areas in vivo in important aspects. It is seldom considered whether the simulated spiking activity is realistic (in a statistical sense) in response to natural stimuli. Because certain statistical properties of spike responses were suggested to facilitate computations in the cortex, acquiring a realistic firing regimen in cortical network models might be a prerequisite for analyzing their computational functions. We present a characterization and comparison of the statistical response properties of the primary visual cortex (V1) in vivo and in silico in response to natural stimuli. We recorded from multiple electrodes in area V1 of 4 macaque monkeys and developed a large state-of-the-art network model for a 5 × 5-mm patch of V1 composed of 35,000 neurons and 3.9 million synapses that integrates previously published anatomical and physiological details. By quantitative comparison of the model response to the “statistical fingerprint” of responses in vivo, we find that our model for a patch of V1 responds to the same movie in a way which matches the statistical structure of the recorded data surprisingly well. The deviation between the firing regimen of the model and the in vivo data are on the same level as deviations among monkeys and sessions. This suggests that, despite strong simplifications and abstractions of cortical network models, they are nevertheless capable of generating realistic spiking activity. To reach a realistic firing state, it was not only necessary to include both N-methyl-d-aspartate and GABAB synaptic conductances in our model, but also to markedly increase the strength of excitatory synapses onto inhibitory neurons (>2-fold) in comparison to literature values, hinting at the importance to carefully adjust the effect of inhibition for achieving realistic dynamics in current network models. PMID:21106898

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.

The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.

PubMed

Tendeiro, Jorge N

2017-01-01

Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.

Software life cycle dynamic simulation model: The organizational performance submodel

NASA Technical Reports Server (NTRS)

Tausworthe, Robert C.

1985-01-01

The submodel structure of a software life cycle dynamic simulation model is described. The software process is divided into seven phases, each with product, staff, and funding flows. The model is subdivided into an organizational response submodel, a management submodel, a management influence interface, and a model analyst interface. The concentration here is on the organizational response model, which simulates the performance characteristics of a software development subject to external and internal influences. These influences emanate from two sources: the model analyst interface, which configures the model to simulate the response of an implementing organization subject to its own internal influences, and the management submodel that exerts external dynamic control over the production process. A complete characterization is given of the organizational response submodel in the form of parameterized differential equations governing product, staffing, and funding levels. The parameter values and functions are allocated to the two interfaces.

The non-linear response of a muscle in transverse compression: assessment of geometry influence using a finite element model.

PubMed

Gras, Laure-Lise; Mitton, David; Crevier-Denoix, Nathalie; Laporte, Sébastien

2012-01-01

Most recent finite element models that represent muscles are generic or subject-specific models that use complex, constitutive laws. Identification of the parameters of such complex, constitutive laws could be an important limit for subject-specific approaches. The aim of this study was to assess the possibility of modelling muscle behaviour in compression with a parametric model and a simple, constitutive law. A quasi-static compression test was performed on the muscles of dogs. A parametric finite element model was designed using a linear, elastic, constitutive law. A multi-variate analysis was performed to assess the effects of geometry on muscle response. An inverse method was used to define Young's modulus. The non-linear response of the muscles was obtained using a subject-specific geometry and a linear elastic law. Thus, a simple muscle model can be used to have a bio-faithful, biomechanical response.

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.

Paleoclimate diagnostics: consistent large-scale temperature responses in warm and cold climates

NASA Astrophysics Data System (ADS)

Izumi, Kenji; Bartlein, Patrick; Harrison, Sandy

2015-04-01

The CMIP5 model simulations of the large-scale temperature responses to increased raditative forcing include enhanced land-ocean contrast, stronger response at higher latitudes than in the tropics, and differential responses in warm and cool season climates to uniform forcing. Here we show that these patterns are also characteristic of CMIP5 model simulations of past climates. The differences in the responses over land as opposed to over the ocean, between high and low latitudes, and between summer and winter are remarkably consistent (proportional and nearly linear) across simulations of both cold and warm climates. Similar patterns also appear in historical observations and paleoclimatic reconstructions, implying that such responses are characteristic features of the climate system and not simple model artifacts, thereby increasing our confidence in the ability of climate models to correctly simulate different climatic states. We also show the possibility that a small set of common mechanisms control these large-scale responses of the climate system across multiple states.

From reactive to proactive and selective control: developing a richer model for stopping inappropriate responses

PubMed Central

Aron, Adam R

2010-01-01

A better understanding of the neural systems underlying impulse control is important for psychiatry. While most impulses are motivational or emotional rather than motoric per se, it is research into the neural architecture of motor response control that has made the greatest strides. This article reviews recent developments in the cognitive neuroscience of stopping responses. Most research of this kind has focused on reactive control – i.e. how subjects stop a response outright when instructed by a signal. It is argued that reactive paradigms are limited as models of control relevant to psychiatry. Instead, a set of paradigms is advocated that begins to model proactive inhibitory control – i.e. how a subject prepares to stop an upcoming response tendency. Proactive inhibitory control is generated according to the goals of the subject, rather than by an external signal, and it can be selectively targeted at a particular response tendency. This may have wider validity than reactive control as an experimental model for stopping inappropriate responses. PMID:20932513

Locating helicopter emergency medical service bases to optimise population coverage versus average response time.

PubMed

Garner, Alan A; van den Berg, Pieter L

2017-10-16

New South Wales (NSW), Australia has a network of multirole retrieval physician staffed helicopter emergency medical services (HEMS) with seven bases servicing a jurisdiction with population concentrated along the eastern seaboard. The aim of this study was to estimate optimal HEMS base locations within NSW using advanced mathematical modelling techniques. We used high resolution census population data for NSW from 2011 which divides the state into areas containing 200-800 people. Optimal HEMS base locations were estimated using the maximal covering location problem facility location optimization model and the average response time model, exploring the number of bases needed to cover various fractions of the population for a 45 min response time threshold or minimizing the overall average response time to all persons, both in green field scenarios and conditioning on the current base structure. We also developed a hybrid mathematical model where average response time was optimised based on minimum population coverage thresholds. Seven bases could cover 98% of the population within 45mins when optimised for coverage or reach the entire population of the state within an average of 21mins if optimised for response time. Given the existing bases, adding two bases could either increase the 45 min coverage from 91% to 97% or decrease the average response time from 21mins to 19mins. Adding a single specialist prehospital rapid response HEMS to the area of greatest population concentration decreased the average state wide response time by 4mins. The optimum seven base hybrid model that was able to cover 97.75% of the population within 45mins, and all of the population in an average response time of 18 mins included the rapid response HEMS model. HEMS base locations can be optimised based on either percentage of the population covered, or average response time to the entire population. We have also demonstrated a hybrid technique that optimizes response time for a given number of bases and minimum defined threshold of population coverage. Addition of specialized rapid response HEMS services to a system of multirole retrieval HEMS may reduce overall average response times by improving access in large urban areas.

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

DOE PAGES

Thomas, Edward V.; Lewis, John R.; Anderson-Cook, Christine M.; ...

2017-11-21

nverse prediction is important in a wide variety of scientific and engineering contexts. One might use inverse prediction to predict fundamental properties/characteristics of an object using measurements obtained from it. This can be accomplished by “inverting” parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are science based; but often, forward models are empirically based, using the results of experimentation. For empirically-based forward models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). While nature dictates the causal relationship between factorsmore » and responses, experimenters can influence control of the type, accuracy, and precision of forward models that can be constructed via selection of factors, factor levels, and the set of trials that are performed. Whether the forward models are based on science, experiments or both, researchers can influence the ability to perform inverse prediction by selecting informative response variables. By using an errors-in-variables framework for inverse prediction, this paper shows via simple analysis and examples how the capability of a multivariate response (with respect to being informative and discriminating) can vary depending on how well the various responses complement one another over the range of the factor-space of interest. Insights derived from this analysis could be useful for selecting a set of response variables among candidates in cases where the number of response variables that can be acquired is limited by difficulty, expense, and/or availability of material.« less

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

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

Thomas, Edward V.; Lewis, John R.; Anderson-Cook, Christine M.

nverse prediction is important in a wide variety of scientific and engineering contexts. One might use inverse prediction to predict fundamental properties/characteristics of an object using measurements obtained from it. This can be accomplished by “inverting” parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are science based; but often, forward models are empirically based, using the results of experimentation. For empirically-based forward models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). While nature dictates the causal relationship between factorsmore » and responses, experimenters can influence control of the type, accuracy, and precision of forward models that can be constructed via selection of factors, factor levels, and the set of trials that are performed. Whether the forward models are based on science, experiments or both, researchers can influence the ability to perform inverse prediction by selecting informative response variables. By using an errors-in-variables framework for inverse prediction, this paper shows via simple analysis and examples how the capability of a multivariate response (with respect to being informative and discriminating) can vary depending on how well the various responses complement one another over the range of the factor-space of interest. Insights derived from this analysis could be useful for selecting a set of response variables among candidates in cases where the number of response variables that can be acquired is limited by difficulty, expense, and/or availability of material.« less

Modeling of a Surface Acoustic Wave Strain Sensor

NASA Technical Reports Server (NTRS)

Wilson, W. C.; Atkinson, Gary M.

2010-01-01

NASA Langley Research Center is investigating Surface Acoustic Wave (SAW) sensor technology for harsh environments aimed at aerospace applications. To aid in development of sensors a model of a SAW strain sensor has been developed. The new model extends the modified matrix method to include the response of Orthogonal Frequency Coded (OFC) reflectors and the response of SAW devices to strain. These results show that the model accurately captures the strain response of a SAW sensor on a Langasite substrate. The results of the model of a SAW Strain Sensor on Langasite are presented

Validation and upgrading of physically based mathematical models

NASA Technical Reports Server (NTRS)

Duval, Ronald

1992-01-01

The validation of the results of physically-based mathematical models against experimental results was discussed. Systematic techniques are used for: (1) isolating subsets of the simulator mathematical model and comparing the response of each subset to its experimental response for the same input conditions; (2) evaluating the response error to determine whether it is the result of incorrect parameter values, incorrect structure of the model subset, or unmodeled external effects of cross coupling; and (3) modifying and upgrading the model and its parameter values to determine the most physically appropriate combination of changes.

A Comparison of Linking and Concurrent Calibration under the Graded Response Model.

ERIC Educational Resources Information Center

Kim, Seock-Ho; Cohen, Allan S.

Applications of item response theory to practical testing problems including equating, differential item functioning, and computerized adaptive testing, require that item parameter estimates be placed onto a common metric. In this study, two methods for developing a common metric for the graded response model under item response theory were…

Hillslope threshold response to rainfall: (2) development and use of a macroscale model

Treesearch

Chris B. Graham; Jeffrey J. McDonnell

2010-01-01

Hillslope hydrological response to precipitation is extremely complex and poorly modeled. One possible approach for reducing the complexity of hillslope response and its mathematical parameterization is to look for macroscale hydrological behavior. Hillslope threshold response to storm precipitation is one such macroscale behavior observed at field sites across the...

Using SAS PROC MCMC for Item Response Theory Models

PubMed Central

Samonte, Kelli

2014-01-01

Interest in using Bayesian methods for estimating item response theory models has grown at a remarkable rate in recent years. This attentiveness to Bayesian estimation has also inspired a growth in available software such as WinBUGS, R packages, BMIRT, MPLUS, and SAS PROC MCMC. This article intends to provide an accessible overview of Bayesian methods in the context of item response theory to serve as a useful guide for practitioners in estimating and interpreting item response theory (IRT) models. Included is a description of the estimation procedure used by SAS PROC MCMC. Syntax is provided for estimation of both dichotomous and polytomous IRT models, as well as a discussion on how to extend the syntax to accommodate more complex IRT models. PMID:29795834

A computer program for predicting nonlinear uniaxial material responses using viscoplastic models

NASA Technical Reports Server (NTRS)

Chang, T. Y.; Thompson, R. L.

1984-01-01

A computer program was developed for predicting nonlinear uniaxial material responses using viscoplastic constitutive models. Four specific models, i.e., those due to Miller, Walker, Krieg-Swearengen-Rhode, and Robinson, are included. Any other unified model is easily implemented into the program in the form of subroutines. Analysis features include stress-strain cycling, creep response, stress relaxation, thermomechanical fatigue loop, or any combination of these responses. An outline is given on the theoretical background of uniaxial constitutive models, analysis procedure, and numerical integration methods for solving the nonlinear constitutive equations. In addition, a discussion on the computer program implementation is also given. Finally, seven numerical examples are included to demonstrate the versatility of the computer program developed.

Using process algebra to develop predator-prey models of within-host parasite dynamics.

PubMed

McCaig, Chris; Fenton, Andy; Graham, Andrea; Shankland, Carron; Norman, Rachel

2013-07-21

As a first approximation of immune-mediated within-host parasite dynamics we can consider the immune response as a predator, with the parasite as its prey. In the ecological literature of predator-prey interactions there are a number of different functional responses used to describe how a predator reproduces in response to consuming prey. Until recently most of the models of the immune system that have taken a predator-prey approach have used simple mass action dynamics to capture the interaction between the immune response and the parasite. More recently Fenton and Perkins (2010) employed three of the most commonly used prey-dependent functional response terms from the ecological literature. In this paper we make use of a technique from computing science, process algebra, to develop mathematical models. The novelty of the process algebra approach is to allow stochastic models of the population (parasite and immune cells) to be developed from rules of individual cell behaviour. By using this approach in which individual cellular behaviour is captured we have derived a ratio-dependent response similar to that seen in the previous models of immune-mediated parasite dynamics, confirming that, whilst this type of term is controversial in ecological predator-prey models, it is appropriate for models of the immune system. Copyright © 2013 Elsevier Ltd. All rights reserved.

Robust Unit Commitment Considering Uncertain Demand Response

DOE PAGES

Liu, Guodong; Tomsovic, Kevin

2014-09-28

Although price responsive demand response has been widely accepted as playing an important role in the reliable and economic operation of power system, the real response from demand side can be highly uncertain due to limited understanding of consumers' response to pricing signals. To model the behavior of consumers, the price elasticity of demand has been explored and utilized in both research and real practice. However, the price elasticity of demand is not precisely known and may vary greatly with operating conditions and types of customers. To accommodate the uncertainty of demand response, alternative unit commitment methods robust to themore » uncertainty of the demand response require investigation. In this paper, a robust unit commitment model to minimize the generalized social cost is proposed for the optimal unit commitment decision taking into account uncertainty of the price elasticity of demand. By optimizing the worst case under proper robust level, the unit commitment solution of the proposed model is robust against all possible realizations of the modeled uncertain demand response. Numerical simulations on the IEEE Reliability Test System show the e ectiveness of the method. Finally, compared to unit commitment with deterministic price elasticity of demand, the proposed robust model can reduce the average Locational Marginal Prices (LMPs) as well as the price volatility.« less

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.

Analyzing Multiple-Choice Questions by Model Analysis and Item Response Curves

NASA Astrophysics Data System (ADS)

Wattanakasiwich, P.; Ananta, S.

2010-07-01

In physics education research, the main goal is to improve physics teaching so that most students understand physics conceptually and be able to apply concepts in solving problems. Therefore many multiple-choice instruments were developed to probe students' conceptual understanding in various topics. Two techniques including model analysis and item response curves were used to analyze students' responses from Force and Motion Conceptual Evaluation (FMCE). For this study FMCE data from more than 1000 students at Chiang Mai University were collected over the past three years. With model analysis, we can obtain students' alternative knowledge and the probabilities for students to use such knowledge in a range of equivalent contexts. The model analysis consists of two algorithms—concentration factor and model estimation. This paper only presents results from using the model estimation algorithm to obtain a model plot. The plot helps to identify a class model state whether it is in the misconception region or not. Item response curve (IRC) derived from item response theory is a plot between percentages of students selecting a particular choice versus their total score. Pros and cons of both techniques are compared and discussed.

An Evaluation of Human Thermal Models for the Study of Immersion Hypothermia Protection Equipment

DTIC Science & Technology

1979-10-12

exhibited by the five experimental observations, largely due to somatotype differences among the subjects. None of the individual responses Is represented...not less than 35°C). A mathematical model capable of accurately simulating the thermal responses of a protected man in a cold environment would be an...flow) responses . The models are most generally expressed as a set of differential equa- tions. Early models were solved using analog computers. The

Three-dimensional Electromagnetic Modeling of the Hawaiian Swell

NASA Astrophysics Data System (ADS)

Avdeev, D.; Utada, H.; Kuvshinov, A.; Koyama, T.

2004-12-01

An anomalous behavior of the geomagnetic deep sounding (GDS) responses at the Honolulu geomagnetic observatory has been reported by many researchers. Kuvshinov et al (2004) found that the predicted GDS Dst C-response does not match the experimental data -- 10-20% disagreement occurs for all periods of 2 to 30 days, qualitatively implying a more resistive, rather than conductive, structure beneath the Hawaiian Islands. Simpson et al. (2000) found that the GDS Sq C-response at the Honolulu observatory is about 4 times larger than that at a Hawaii island site, again suggesting a more resistive (than elsewhere around) structure beneath the observatory. Constable and Heinson (2004, http://mahi.ucsd.edu/Steve/swell.pdf), presenting a 2-D interpretation of the magnetotelluric (MT) and GDS responses recently obtained at 7 seafloor sites to the south of the Hawaii Islands, concluded that the dataset require the presence of a narrow conducting plume just beneath the islands. The main motivation of our work is to reveal the reason of the anomalous behavior of the Honolulu response. Obviously, the cause may be due to heterogeneity of either the conductivity or the source field. We examine this problem in some detail with reference to the Constable and Heinson's seafloor dataset, as well as the available dataset from the Honolulu observatory. To address the problem we apply numerical modeling using the three-dimensional (3-D) forward modeling code of Avdeev et al. (1997, 2002). With this code we simulate various regional 3-D conductivity models that may produce EM responses that better fit the experimental datasets, at least qualitatively. Also, to explain some features of the experimental long-period GDS responses we numerically studied a possible effect in the responses caused by the equatorial electrojet. Our 3-D modeling results show that, in particular: (1) The GDS responses are better explained by models with a resistive lithosphere whereas the MT data are better fit by models without one; (2) A conductive plume under the Hawaiian Islands may not be required by the MT and GDS datasets considered; (3) An equatorial electrojet might affect the imaginary part of the GDS responses at periods of 2 h and more; (4) The anomalous large value of 0.4 observed in the real part of the seafloor GDS responses still cannot be explained by the 3-D models considered. It seems to require more complicated models.

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

A nonlinear filter-bank model of the guinea-pig cochlear nerve: Rate responses

NASA Astrophysics Data System (ADS)

Sumner, Christian J.; O'Mard, Lowel P.; Lopez-Poveda, Enrique A.; Meddis, Ray

2003-06-01

The aim of this study is to produce a functional model of the auditory nerve (AN) response of the guinea-pig that reproduces a wide range of important responses to auditory stimulation. The model is intended for use as an input to larger scale models of auditory processing in the brain-stem. A dual-resonance nonlinear filter architecture is used to reproduce the mechanical tuning of the cochlea. Transduction to the activity on the AN is accomplished with a recently proposed model of the inner-hair-cell. Together, these models have been shown to be able to reproduce the response of high-, medium-, and low-spontaneous rate fibers from the guinea-pig AN at high best frequencies (BFs). In this study we generate parameters that allow us to fit the AN model to data from a wide range of BFs. By varying the characteristics of the mechanical filtering as a function of the BF it was possible to reproduce the BF dependence of frequency-threshold tuning curves, AN rate-intensity functions at and away from BF, compression of the basilar membrane at BF as inferred from AN responses, and AN iso-intensity functions. The model is a convenient computational tool for the simulation of the range of nonlinear tuning and rate-responses found across the length of the guinea-pig cochlear nerve.

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

Taxonomy for Modeling Demand Response Resources

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

Olsen, Daniel; Kiliccote, Sila; Sohn, Michael

2014-08-01

Demand response resources are an important component of modern grid management strategies. Accurate characterizations of DR resources are needed to develop systems of optimally managed grid operations and to plan future investments in generation, transmission, and distribution. The DOE Demand Response and Energy Storage Integration Study (DRESIS) project researched the degree to which demand response (DR) and energy storage can provide grid flexibility and stability in the Western Interconnection. In this work, DR resources were integrated with traditional generators in grid forecasting tools, specifically a production cost model of the Western Interconnection. As part of this study, LBNL developed amore » modeling framework for characterizing resource availability and response attributes of DR resources consistent with the governing architecture of the simulation modeling platform. In this report, we identify and describe the following response attributes required to accurately characterize DR resources: allowable response frequency, maximum response duration, minimum time needed to achieve load changes, necessary pre- or re-charging of integrated energy storage, costs of enablement, magnitude of controlled resources, and alignment of availability. We describe a framework for modeling these response attributes, and apply this framework to characterize 13 DR resources including residential, commercial, and industrial end-uses. We group these end-uses into three broad categories based on their response capabilities, and define a taxonomy for classifying DR resources within these categories. The three categories of resources exhibit different capabilities and differ in value to the grid. Results from the production cost model of the Western Interconnection illustrate that minor differences in resource attributes can have significant impact on grid utilization of DR resources. The implications of these findings will be explored in future DR valuation studies.« less

High fidelity computational characterization of the mechanical response of thermally aged polycarbonate

NASA Astrophysics Data System (ADS)

Zhang, Zesheng; Zhang, Lili; Jasa, John; Li, Wenlong; Gazonas, George; Negahban, Mehrdad

2017-07-01

A representative all-atom molecular dynamics (MD) system of polycarbonate (PC) is built and conditioned to capture and predict the behaviours of PC in response to a broad range of thermo-mechanical loadings for various thermal aging. The PC system is constructed to have a distribution of molecular weights comparable to a widely used commercial PC (LEXAN 9034), and thermally conditioned to produce models for aged and unaged PC. The MD responses of these models are evaluated through comparisons to existing experimental results carried out at much lower loading rates, but done over a broad range of temperatures and loading modes. These experiments include monotonic extension/compression/shear, unilaterally and bilaterally confined compression, and load-reversal during shear. It is shown that the MD simulations show both qualitative and quantitative similarity with the experimental response. The quantitative similarity is evaluated by comparing the dilatational response under bilaterally confined compression, the shear flow viscosity and the equivalent yield stress. The consistency of the in silico response to real laboratory experiments strongly suggests that the current PC models are physically and mechanically relevant and potentially can be used to investigate thermo-mechanical response to loading conditions that would not easily be possible. These MD models may provide valuable insight into the molecular sources of certain observations, and could possibly offer new perspectives on how to develop constitutive models that are based on better understanding the response of PC under complex loadings. To this latter end, the models are used to predict the response of PC to complex loading modes that would normally be difficult to do or that include characteristics that would be difficult to measure. These include the responses of unaged and aged PC to unilaterally confined extension/compression, cyclic uniaxial/shear loadings, and saw-tooth extension/compression/shear.

Response Styles in Rating Scales: Simultaneous Modeling of Content-Related Effects and the Tendency to Middle or Extreme Categories

ERIC Educational Resources Information Center

Tutz, Gerhard; Berger, Moritz

2016-01-01

Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…

Asymptotic Properties of Induced Maximum Likelihood Estimates of Nonlinear Models for Item Response Variables: The Finite-Generic-Item-Pool Case.

ERIC Educational Resources Information Center

Jones, Douglas H.

The progress of modern mental test theory depends very much on the techniques of maximum likelihood estimation, and many popular applications make use of likelihoods induced by logistic item response models. While, in reality, item responses are nonreplicate within a single examinee and the logistic models are only ideal, practitioners make…

Variable Complexity Optimization of Composite Structures

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.

2002-01-01

The use of several levels of modeling in design has been dubbed variable complexity modeling. The work under the grant focused on developing variable complexity modeling strategies with emphasis on response surface techniques. Applications included design of stiffened composite plates for improved damage tolerance, the use of response surfaces for fitting weights obtained by structural optimization, and design against uncertainty using response surface techniques.

Applications of Multidimensional Item Response Theory Models with Covariates to Longitudinal Test Data. Research Report. ETS RR-16-21

ERIC Educational Resources Information Center

Fu, Jianbin

2016-01-01

The multidimensional item response theory (MIRT) models with covariates proposed by Haberman and implemented in the "mirt" program provide a flexible way to analyze data based on item response theory. In this report, we discuss applications of the MIRT models with covariates to longitudinal test data to measure skill differences at the…

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.

Dynamic Behavior of Sand: Annual Report FY 11

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

Antoun, T; Herbold, E; Johnson, S

2012-03-15

Currently, design of earth-penetrating munitions relies heavily on empirical relationships to estimate behavior, making it difficult to design novel munitions or address novel target situations without expensive and time-consuming full-scale testing with relevant system and target characteristics. Enhancing design through numerical studies and modeling could help reduce the extent and duration of full-scale testing if the models have enough fidelity to capture all of the relevant parameters. This can be separated into three distinct problems: that of the penetrator structural and component response, that of the target response, and that of the coupling between the two. This project focuses onmore » enhancing understanding of the target response, specifically granular geomaterials, where the temporal and spatial multi-scale nature of the material controls its response. As part of the overarching goal of developing computational capabilities to predict the performance of conventional earth-penetrating weapons, this project focuses specifically on developing new models and numerical capabilities for modeling sand response in ALE3D. There is general recognition that granular materials behave in a manner that defies conventional continuum approaches which rely on response locality and which degrade in the presence of strong response nonlinearities, localization, and phase gradients. There are many numerical tools available to address parts of the problem. However, to enhance modeling capability, this project is pursuing a bottom-up approach of building constitutive models from higher fidelity, smaller spatial scale simulations (rather than from macro-scale observations of physical behavior as is traditionally employed) that are being augmented to address the unique challenges of mesoscale modeling of dynamically loaded granular materials. Through understanding response and sensitivity at the grain-scale, it is expected that better reduced order representations of response can be formulated at the continuum scale as illustrated in Figure 1 and Figure 2. The final result of this project is to implement such reduced order models in the ALE3D material library for general use.« less

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.

Modeling Effective Dosages in Hormetic Dose-Response Studies

PubMed Central

Belz, Regina G.; Piepho, Hans-Peter

2012-01-01

Background Two hormetic modifications of a monotonically decreasing log-logistic dose-response function are most often used to model stimulatory effects of low dosages of a toxicant in plant biology. As just one of these empirical models is yet properly parameterized to allow inference about quantities of interest, this study contributes the parameterized functions for the second hormetic model and compares the estimates of effective dosages between both models based on 23 hormetic data sets. Based on this, the impact on effective dosage estimations was evaluated, especially in case of a substantially inferior fit by one of the two models. Methodology/Principal Findings The data sets evaluated described the hormetic responses of four different test plant species exposed to 15 different chemical stressors in two different experimental dose-response test designs. Out of the 23 data sets, one could not be described by any of the two models, 14 could be better described by one of the two models, and eight could be equally described by both models. In cases of misspecification by any of the two models, the differences between effective dosages estimates (0–1768%) greatly exceeded the differences observed when both models provided a satisfactory fit (0–26%). This suggests that the conclusions drawn depending on the model used may diverge considerably when using an improper hormetic model especially regarding effective dosages quantifying hormesis. Conclusions/Significance The study showed that hormetic dose responses can take on many shapes and that this diversity can not be captured by a single model without risking considerable misinterpretation. However, the two empirical models considered in this paper together provide a powerful means to model, prove, and now also to quantify a wide range of hormetic responses by reparameterization. Despite this, they should not be applied uncritically, but after statistical and graphical assessment of their adequacy. PMID:22438929

Causes of variation among rice models in yield response to CO2 examined with Free-Air CO2 Enrichment and growth chamber experiments.

PubMed

Hasegawa, Toshihiro; Li, Tao; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Baker, Jeffrey; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fugice, Job; Fumoto, Tamon; Gaydon, Donald; Kumar, Soora Naresh; Lafarge, Tanguy; Marcaida Iii, Manuel; Masutomi, Yuji; Nakagawa, Hiroshi; Oriol, Philippe; Ruget, Françoise; Singh, Upendra; Tang, Liang; Tao, Fulu; Wakatsuki, Hitomi; Wallach, Daniel; Wang, Yulong; Wilson, Lloyd Ted; Yang, Lianxin; Yang, Yubin; Yoshida, Hiroe; Zhang, Zhao; Zhu, Jianguo

2017-11-01

The CO 2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO 2 ] (E-[CO 2 ]) by comparison to free-air CO 2 enrichment (FACE) and chamber experiments. The model ensemble reproduced the experimental results well. However, yield prediction in response to E-[CO 2 ] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO 2 ] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO 2 ] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice morphological development is conservative to carbon acquisition. Uncertainty will be reduced by incorporating this conservative nature of the morphological response to E-[CO 2 ] into the models. Nitrogen levels, particularly under limited situations, make the prediction more uncertain. Improving models to account for [CO 2 ] × N interactions is necessary to better evaluate management practices under climate change.

Fitting measurement models to vocational interest data: are dominance models ideal?

PubMed

Tay, Louis; Drasgow, Fritz; Rounds, James; Williams, Bruce A

2009-09-01

In this study, the authors examined the item response process underlying 3 vocational interest inventories: the Occupational Preference Inventory (C.-P. Deng, P. I. Armstrong, & J. Rounds, 2007), the Interest Profiler (J. Rounds, T. Smith, L. Hubert, P. Lewis, & D. Rivkin, 1999; J. Rounds, C. M. Walker, et al., 1999), and the Interest Finder (J. E. Wall & H. E. Baker, 1997; J. E. Wall, L. L. Wise, & H. E. Baker, 1996). Item response theory (IRT) dominance models, such as the 2-parameter and 3-parameter logistic models, assume that item response functions (IRFs) are monotonically increasing as the latent trait increases. In contrast, IRT ideal point models, such as the generalized graded unfolding model, have IRFs that peak where the latent trait matches the item. Ideal point models are expected to fit better because vocational interest inventories ask about typical behavior, as opposed to requiring maximal performance. Results show that across all 3 interest inventories, the ideal point model provided better descriptions of the response process. The importance of specifying the correct item response model for precise measurement is discussed. In particular, scores computed by a dominance model were shown to be sometimes illogical: individuals endorsing mostly realistic or mostly social items were given similar scores, whereas scores based on an ideal point model were sensitive to which type of items respondents endorsed.

The Role of Air-sea Coupling in the Response of Climate Extremes to Aerosols

NASA Astrophysics Data System (ADS)

Mahajan, S.

2017-12-01

Air-sea interactions dominate the climate of surrounding regions and thus also modulate the climate response to local and remote aerosol forcings. To clearly isolate the role of air-sea coupling in the climate response to aerosols, we conduct experiments with a full complexity atmosphere model that is coupled to a series of ocean models progressively increasing in complexity. The ocean models range from a data ocean model with prescribed SSTs, to a slab ocean model that only allows thermodynamic interactions, to a full dynamic ocean model. In a preliminary study, we have conducted single forcing experiments with black carbon aerosols in an atmosphere GCM coupled to a data ocean model and a slab ocean model. We find that while black carbon aerosols can intensify mean and extreme summer monsoonal precipitation over the Indian sub-continent, air-sea coupling can dramatically modulate this response. Black carbon aerosols in the vicinity of the Arabian Sea result in an increase of sea surface temperatures there in the slab ocean model, which intensify the low-level Somali Jet. The associated increase in moisture transport into Western India enhances the mean as well as extreme precipitation. In prescribed SST experiments, where SSTs are not allowed to respond BC aerosols, the response is muted. We will present results from a hierarchy of GCM simulations that investigate the role of air-sea coupling in the climate response to aerosols in more detail.

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.

Behavioural and computational varieties of response inhibition in eye movements.

PubMed

Cutsuridis, Vassilis

2017-04-19

Response inhibition is the ability to override a planned or an already initiated response. It is the hallmark of executive control as its deficits favour impulsive behaviours, which may be detrimental to an individual's life. This article reviews behavioural and computational guises of response inhibition. It focuses only on inhibition of oculomotor responses. It first reviews behavioural paradigms of response inhibition in eye movement research, namely the countermanding and antisaccade paradigms, both proven to be useful tools for the study of response inhibition in cognitive neuroscience and psychopathology. Then, it briefly reviews the neural mechanisms of response inhibition in these two behavioural paradigms. Computational models that embody a hypothesis and/or a theory of mechanisms underlying performance in both behavioural paradigms as well as provide a critical analysis of strengths and weaknesses of these models are discussed. All models assume the race of decision processes. The decision process in each paradigm that wins the race depends on different mechanisms. It has been shown that response latency is a stochastic process and has been proven to be an important measure of the cognitive control processes involved in response stopping in healthy and patient groups. Then, the inhibitory deficits in different brain diseases are reviewed, including schizophrenia and obsessive-compulsive disorder. Finally, new directions are suggested to improve the performance of models of response inhibition by drawing inspiration from successes of models in other domains.This article is part of the themed issue 'Movement suppression: brain mechanisms for stopping and stillness'. © 2017 The Author(s).

Simulation-based Bayesian inference for latent traits of item response models: Introduction to the ltbayes package for R.

PubMed

Johnson, Timothy R; Kuhn, Kristine M

2015-12-01

This paper introduces the ltbayes package for R. This package includes a suite of functions for investigating the posterior distribution of latent traits of item response models. These include functions for simulating realizations from the posterior distribution, profiling the posterior density or likelihood function, calculation of posterior modes or means, Fisher information functions and observed information, and profile likelihood confidence intervals. Inferences can be based on individual response patterns or sets of response patterns such as sum scores. Functions are included for several common binary and polytomous item response models, but the package can also be used with user-specified models. This paper introduces some background and motivation for the package, and includes several detailed examples of its use.

[Light response characteristics of photosynthesis and model comparison of Distylium chinense in different flooding durations].

PubMed

Liu, Ze-bin; Cheng, Rui-mei; Xiao, Wen-fa; Guo, Quan-shui; Wang, Na

2015-04-01

The light responses of photosynthesis of two-year-old Distytum chinense seedlings subjected to a simulated reservoir flooding environment in autumn and winter seasons were measured by using a Li-6400 XT portable photosynthesis system, and the light response curves were fitted and analyzed by three models of the rectangular hyperbola, non-rectangular hyperbola and modified rectangular hyperbola to investigate the applicability of different light response models for the D. chinense in different flooding durations and the adaption regulation of light response parameters to flooding stress. The results showed that the fitting effect of the non-rectangular hyperbola model for light response process of D. chinense under normal growth condition and under short-term flooding (15 days of flooding) was better than that of the other two models, while the fitting effect of the modified rectangular hyperbola model for light response process of D. chinense under longer-term flooding (30, 45 and 60 days of flooding) was better than that of the other two models. The modified rectangular hyperbola model gave the best fitted results of light compensation point (LCP) , maximum net photosynthetic rate (P(n max)) and light saturation point (LSP), and the non-rectangular hyperbola model gave the best fitted result of dark respiration rate (R(d)). The apparent quantum yield (Φ), P(n max) and LSP of D. chinense gradually decreased, and the LCP and R(d) of D. chinense gradually increased in early flooding (30 days), but D. chinense gradually produced adaptability for flooding as the flooding duration continued to increase, and various physiological indexes were gradually stabilized. Thus, this species has adaptability to some degree to the flooding environment.

Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003.

PubMed

Schöllnberger, Helmut; Eidemüller, Markus; Cullings, Harry M; Simonetto, Cristoforo; Neff, Frauke; Kaiser, Jan Christian

2018-03-01

The scientific community faces important discussions on the validity of the linear no-threshold (LNT) model for radiation-associated cardiovascular diseases at low and moderate doses. In the present study, mortalities from cerebrovascular diseases (CeVD) and heart diseases from the latest data on atomic bomb survivors were analyzed. The analysis was performed with several radio-biologically motivated linear and nonlinear dose-response models. For each detrimental health outcome one set of models was identified that all fitted the data about equally well. This set was used for multi-model inference (MMI), a statistical method of superposing different models to allow risk estimates to be based on several plausible dose-response models rather than just relying on a single model of choice. MMI provides a more accurate determination of the dose response and a more comprehensive characterization of uncertainties. It was found that for CeVD, the dose-response curve from MMI is located below the linear no-threshold model at low and medium doses (0-1.4 Gy). At higher doses MMI predicts a higher risk compared to the LNT model. A sublinear dose-response was also found for heart diseases (0-3 Gy). The analyses provide no conclusive answer to the question whether there is a radiation risk below 0.75 Gy for CeVD and 2.6 Gy for heart diseases. MMI suggests that the dose-response curves for CeVD and heart diseases in the Lifespan Study are sublinear at low and moderate doses. This has relevance for radiotherapy treatment planning and for international radiation protection practices in general.

Perturbative tests of theoretical transport models using cold pulse and modulated electron cyclotron heating experiments

NASA Astrophysics Data System (ADS)

Kinsey, J. E.; Waltz, R. E.; DeBoo, J. C.

1999-05-01

It is difficult to discriminate between various tokamak transport models using standardized statistical measures to assess the goodness of fit with steady-state density and temperature profiles in tokamaks. This motivates consideration of transient transport experiments as a technique for testing the temporal response predicted by models. Results are presented comparing the predictions from the Institute for Fusion Studies—Princeton Plasma Physics Laboratory (IFS/PPPL), gyro-Landau-fluid (GLF23), Multi-mode (MM), Current Diffusive Ballooning Mode (CDBM), and Mixed-shear (MS) transport models against data from ohmic cold pulse and modulated electron cyclotron heating (ECH) experiments. In ohmically heated discharges with rapid edge cooling due to trace impurity injection, it is found that critical gradient models containing a strong temperature ratio (Ti/Te) dependence can exhibit behavior that is qualitatively consistent both spatially and temporally with experimental observation while depending solely on local parameters. On the DIII-D tokamak [J. L. Luxon and L. G. Davis, Fusion Technol. 8, 441 (1985)], off-axis modulated ECH experiments have been conducted in L-mode (low confinement mode) and the perturbed electron and ion temperature response to multiple heat pulses has been measured across the plasma core. Comparing the predicted Fourier phase of the temperature perturbations, it is found that no single model yielded agreement with both electron and ion phases for all cases. In general, it was found that the IFS/PPPL, GLF23, and MS models agreed well with the ion response, but not with the electron response. The CDBM and MM models agreed well with the electron response, but not with the ion response. For both types of transient experiments, temperature coupling between the electron and ion transport is found to be an essential feature needed in the models for reproducing the observed perturbative response.

Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach

PubMed Central

Sershen, Cheryl L.; Plimpton, Steven J.; May, Elebeoba E.

2016-01-01

Mycobacterium tuberculosis associated granuloma formation can be viewed as a structural immune response that can contain and halt the spread of the pathogen. In several mammalian hosts, including non-human primates, Mtb granulomas are often hypoxic, although this has not been observed in wild type murine infection models. While a presumed consequence, the structural contribution of the granuloma to oxygen limitation and the concomitant impact on Mtb metabolic viability and persistence remains to be fully explored. We develop a multiscale computational model to test to what extent in vivo Mtb granulomas become hypoxic, and investigate the effects of hypoxia on host immune response efficacy and mycobacterial persistence. Our study integrates a physiological model of oxygen dynamics in the extracellular space of alveolar tissue, an agent-based model of cellular immune response, and a systems biology-based model of Mtb metabolic dynamics. Our theoretical studies suggest that the dynamics of granuloma organization mediates oxygen availability and illustrates the immunological contribution of this structural host response to infection outcome. Furthermore, our integrated model demonstrates the link between structural immune response and mechanistic drivers influencing Mtbs adaptation to its changing microenvironment and the qualitative infection outcome scenarios of clearance, containment, dissemination, and a newly observed theoretical outcome of transient containment. We observed hypoxic regions in the containment granuloma similar in size to granulomas found in mammalian in vivo models of Mtb infection. In the case of the containment outcome, our model uniquely demonstrates that immune response mediated hypoxic conditions help foster the shift down of bacteria through two stages of adaptation similar to thein vitro non-replicating persistence (NRP) observed in the Wayne model of Mtb dormancy. The adaptation in part contributes to the ability of Mtb to remain dormant for years after initial infection. PMID:26913242

A case study of development and application of a streamlined control and response modeling system for PM2.5 attainment assessment in China.

PubMed

Long, Shicheng; Zhu, Yun; Jang, Carey; Lin, Che-Jen; Wang, Shuxiao; Zhao, Bin; Gao, Jian; Deng, Shuang; Xie, Junping; Qiu, Xuezhen

2016-03-01

This article describes the development and application of a streamlined air control and response modeling system with a novel response surface modeling-linear coupled fitting method and a new module to provide streamlined model data for PM2.5 attainment assessment in China. This method is capable of significantly reducing the dimensions required to establish a response surface model, as well as capturing more realistic response of PM2.5 to emission changes with a limited number of model simulations. The newly developed module establishes a data link between the system and the Software for Model Attainment Test-Community Edition (SMAT-CE), and has the ability to rapidly provide model responses to emission control scenarios for SMAT-CE using a simple interface. The performance of this streamlined system is demonstrated through a case study of the Yangtze River Delta (YRD) in China. Our results show that this system is capable of reproducing the Community Multi-Scale Air Quality (CMAQ) model simulation results with maximum mean normalized error<3.5%. It is also demonstrated that primary emissions make a major contribution to ambient levels of PM2.5 in January and August (e.g., more than 50% contributed by primary emissions in Shanghai), and Shanghai needs to have regional emission control both locally and in its neighboring provinces to meet China's annual PM2.5 National Ambient Air Quality Standard. The streamlined system provides a real-time control/response assessment to identify the contributions of major emission sources to ambient PM2.5 (and potentially O3 as well) and streamline air quality data for SMAT-CE to perform attainment assessments. Copyright © 2015. Published by Elsevier B.V.

Representing life in the Earth system with soil microbial functional traits in the MIMICS model

NASA Astrophysics Data System (ADS)

Wieder, W. R.; Grandy, A. S.; Kallenbach, C. M.; Taylor, P. G.; Bonan, G. B.

2015-06-01

Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes, and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon (C) cycle-climate feedbacks. We used a microbial trait-based soil C model with two physiologically distinct microbial communities, and evaluate how this model represents soil C storage and response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS) model; these functional groups are akin to "gleaner" vs. "opportunist" plankton in the ocean, or r- vs. K-strategists in plant and animal communities. Here we compare MIMICS to a conventional soil C model, DAYCENT (the daily time-step version of the CENTURY model), in cross-site comparisons of nitrogen (N) enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that MIMICS projects much slower rates of soil C accumulation than a conventional soil biogeochemistry in response to increasing C inputs with elevated carbon dioxide (CO2) - a finding that would reduce the size of the land C sink estimated by the Earth system. Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

Oxygen Modulates the Effectiveness of Granuloma Mediated Host Response to Mycobacterium tuberculosis: A Multiscale Computational Biology Approach.

PubMed

Sershen, Cheryl L; Plimpton, Steven J; May, Elebeoba E

2016-01-01

Mycobacterium tuberculosis associated granuloma formation can be viewed as a structural immune response that can contain and halt the spread of the pathogen. In several mammalian hosts, including non-human primates, Mtb granulomas are often hypoxic, although this has not been observed in wild type murine infection models. While a presumed consequence, the structural contribution of the granuloma to oxygen limitation and the concomitant impact on Mtb metabolic viability and persistence remains to be fully explored. We develop a multiscale computational model to test to what extent in vivo Mtb granulomas become hypoxic, and investigate the effects of hypoxia on host immune response efficacy and mycobacterial persistence. Our study integrates a physiological model of oxygen dynamics in the extracellular space of alveolar tissue, an agent-based model of cellular immune response, and a systems biology-based model of Mtb metabolic dynamics. Our theoretical studies suggest that the dynamics of granuloma organization mediates oxygen availability and illustrates the immunological contribution of this structural host response to infection outcome. Furthermore, our integrated model demonstrates the link between structural immune response and mechanistic drivers influencing Mtbs adaptation to its changing microenvironment and the qualitative infection outcome scenarios of clearance, containment, dissemination, and a newly observed theoretical outcome of transient containment. We observed hypoxic regions in the containment granuloma similar in size to granulomas found in mammalian in vivo models of Mtb infection. In the case of the containment outcome, our model uniquely demonstrates that immune response mediated hypoxic conditions help foster the shift down of bacteria through two stages of adaptation similar to the in vitro non-replicating persistence (NRP) observed in the Wayne model of Mtb dormancy. The adaptation in part contributes to the ability of Mtb to remain dormant for years after initial infection.

Climate change effects on agriculture: Economic responses to biophysical shocks

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

Nelson, Gerald; Valin, Hugo; Sands, Ronald

Agricultural production is sensitive to weather and will thus be directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments inmore » yields, area, consumption, and international trade. We apply biophysical shocks derived from the IPCC’s Representative Concentration Pathway that result in end-of-century radiative forcing of 8.5 watts per square meter. The mean biophysical impact on crop yield with no incremental CO2 fertilization is a 17 percent reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11 percent, increase area of major crops by 12 percent, and reduce consumption by 2 percent. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences includes model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.« less

Measuring the Cognitions, Emotions, and Motivation Associated With Avoidance Behaviors in the Context of Pain: Preliminary Development of the Negative Responsivity to Pain Scales.

PubMed

Jensen, Mark P; Ward, L Charles; Thorn, Beverly E; Ehde, Dawn M; Day, Melissa A

2017-04-01

We recently proposed a Behavioral Inhibition System-Behavioral Activation System (BIS-BAS) model to help explain the effects of pain treatments. In this model, treatments are hypothesized to operate primarily through their effects on the domains within 2 distinct neurophysiological systems that underlie approach (BAS) and avoidance (BIS) behaviors. Measures of the model's domains are needed to evaluate and modify the model. An item pool of negative responses to pain (NRP; hypothesized to be BIS related) and positive responses (PR; hypothesized to be BAS related) were administered to 395 undergraduates, 325 of whom endorsed recurrent pain. The items were administered to 176 of these individuals again 1 week later. Analyses were conducted to develop and validate scales assessing NRP and PR domains. Three NRP scales (Despondent Response to Pain, Fear of Pain, and Avoidant Response to Pain) and 2 PR scales (Happy/Hopeful Responses and Approach Response) emerged. Consistent with the model, the scales formed 2 relatively independent overarching domains. The scales also demonstrated excellent internal consistency, and associations with criterion variables supported their validity. However, whereas the NRP scales evidenced adequate test-retest stability, the 2 PR scales were not adequately stable. The study yielded 3 brief scales assessing NRP, which may be used to further evaluate the BIS-BAS model and to advance research elucidating the mechanisms of psychosocial pain treatments. The findings also provide general support for the BIS-BAS model, while also suggesting that some minor modifications in the model are warranted.

Representing life in the Earth system with soil microbial functional traits in the MIMICS model

NASA Astrophysics Data System (ADS)

Wieder, W. R.; Grandy, A. S.; Kallenbach, C. M.; Taylor, P. G.; Bonan, G. B.

2015-02-01

Projecting biogeochemical responses to global environmental change requires multi-scaled perspectives that consider organismal diversity, ecosystem processes and global fluxes. However, microbes, the drivers of soil organic matter decomposition and stabilization, remain notably absent from models used to project carbon cycle-climate feedbacks. We used a microbial trait-based soil carbon (C) model, with two physiologically distinct microbial communities to improve current estimates of soil C storage and their likely response to perturbations. Drawing from the application of functional traits used to model other ecosystems, we incorporate copiotrophic and oligotrophic microbial functional groups in the MIcrobial-MIneral Carbon Stabilization (MIMICS) model, which incorporates oligotrophic and copiotrophic functional groups, akin to "gleaner" vs. "opportunist" plankton in the ocean, or r vs. K strategists in plant and animals communities. Here we compare MIMICS to a conventional soil C model, DAYCENT, in cross-site comparisons of nitrogen (N) enrichment effects on soil C dynamics. MIMICS more accurately simulates C responses to N enrichment; moreover, it raises important hypotheses involving the roles of substrate availability, community-level enzyme induction, and microbial physiological responses in explaining various soil biogeochemical responses to N enrichment. In global-scale analyses, we show that current projections from Earth system models likely overestimate the strength of the land C sink in response to increasing C inputs with elevated carbon dioxide (CO2). Our findings illustrate that tradeoffs between theory and utility can be overcome to develop soil biogeochemistry models that evaluate and advance our theoretical understanding of microbial dynamics and soil biogeochemical responses to environmental change.

Characterization of Deficiencies in the Frequency Domain Forced Response Analysis Technique for Supersonic Turbine Bladed Disks

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Schmauch, Preston

2012-01-01

Turbine blades in rocket and jet engine turbomachinery experience enormous harmonic loading conditions. These loads result from the integer number of upstream and downstream stator vanes as well as the other turbine stages. Assessing the blade structural integrity is a complex task requiring an initial characterization of whether resonance is possible and then performing a forced response analysis if that condition is met. The standard technique for forced response analysis in rocket engine turbines is to decompose a computational fluid dynamics (CFD).generated flow field into its harmonic components, and to then perform a frequency response analysis at the problematic natural frequencies using cyclically symmetric structural dynamic models. Recent CFD analysis and water-flow testing at NASA/MSFC, though, indicates that this technique may miss substantial harmonic and non ]harmonic excitation sources that become present in complex flows. This complex content can only be captured by a CFD flow field encompassing at least an entire revolution. A substantial development effort to create a series of software programs to enable application of the 360 degree forcing function in a frequency response analysis on cyclic symmetric models has been completed (to be described in a future paper), but the question still remains whether the frequency response analysis itself is capable of capturing the excitation content sufficiently. Two studies comparing frequency response analysis with transient response analysis, therefore, of bladed-disks undergoing this complex flow environment have been performed. The first is of a bladed disk with each blade modeled by simple beam elements and the disk modeled with plates (using the finite element code MSC/NASTRAN). The focus of this model is to be representative of response of realistic bladed disks, and so the dimensions are roughly equivalent to the new J2X rocket engine 1st stage fuel pump turbine. The simplicity of the model allows the CFD load to be able to be readily applied, along with analytical and experimental variations in both the temporal and spatial fourier components of the excitation. In addition, this model is a first step in identifying response differences between transient and frequency forced response analysis techniques. The second phase assesses this difference for a much more realistic solid model of a bladed-disk in order to evaluate the effect of the spatial variation in loading on blade dominated modes. Neither research on the accuracy of the frequency response method when used in this context or a comprehensive study of the effect of test-observed variation on blade forced response have been found in the literature, so this research is a new contribution to practical structural dynamic analysis of gas turbines. The primary excitation of the upstream nozzles interacts with the blades on fuel pump of the J2X causes the 5th Nodal diameter modes to be excited, as explained by Tyler and Sofrin1, so a modal analysis was first performed on the beam/plate model and the 5ND bladed-disk mode at 40167 hz was identified and chosen to be the one excited at resonance (see figure 1). The first forced response analysis with this model focuses on identifying differences between frequency and transient response analyses. A hypothesis going into the analysis was that perhaps the frequency response was enforcing a temporal periodicity that did not really exist, and so therefore it would overestimate the response. As high dynamic response was a considerable source of stress in the J2X, examining this concept could potentially be beneficial for the program.

Insights into mechanisms governing forest carbon response to nitrogen deposition: a model-data comparison using observed responses to nitrogen addition

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Bonan, G. B.; Goodale, C. L.

2013-01-01

In many forest ecosystems, nitrogen (N) deposition enhances plant uptake of carbon dioxide, thus reducing climate warming from fossil fuel emissions. Therefore, accurately modeling how forest carbon (C) sequestration responds to N deposition is critical for understanding how future changes in N availability will influence climate. Here, we use observations of forest C response to N inputs along N deposition gradients and at five temperate forest sites with fertilization experiments to test and improve a~global biogeochemical model (CLM-CN 4.0). We show that the CLM-CN plant C growth response to N deposition was smaller than observed and the modeled response to N fertilization was larger than observed. A set of modifications to the CLM-CN improved the correspondence between model predictions and observational data (1) by increasing the aboveground C storage in response to historical N deposition (1850-2004) from 14 to 34 kg C per additional kg N added through deposition and (2) by decreasing the aboveground net primary productivity response to N fertilization experiments from 91 to 57 g C m-2 yr-1. Modeled growth response to N deposition was most sensitive to altering the processes that control plant N uptake and the pathways of N loss. The response to N deposition also increased with a more closed N cycle (reduced N fixation and N gas loss) and decreased when prioritizing microbial over plant uptake of soil inorganic N. The net effect of all the modifications to the CLM-CN resulted in greater retention of N deposition and a greater role of synergy between N deposition and rising atmospheric CO2 as a mechanism governing increases in temperate forest primary production over the 20th century. Overall, testing models with both the response to gradual increases in N inputs over decades (N deposition) and N pulse additions of N over multiple years (N fertilization) allows for greater understanding of the mechanisms governing C-N coupling.

Insights into mechanisms governing forest carbon response to nitrogen deposition: a model-data comparison using observed responses to nitrogen addition

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Bonan, G. B.; Goodale, C. L.

2013-06-01

In many forest ecosystems, nitrogen (N) deposition enhances plant uptake of carbon dioxide, thus reducing climate warming from fossil fuel emissions. Therefore, accurately modeling how forest carbon (C) sequestration responds to N deposition is critical for understanding how future changes in N availability will influence climate. Here, we use observations of forest C response to N inputs along N deposition gradients and at five temperate forest sites with fertilization experiments to test and improve a global biogeochemical model (CLM-CN 4.0). We show that the CLM-CN plant C growth response to N deposition was smaller than observed and the modeled response to N fertilization was larger than observed. A set of modifications to the CLM-CN improved the correspondence between model predictions and observational data (1) by increasing the aboveground C storage in response to historical N deposition (1850-2004) from 14 to 34 kg C per additional kg N added through deposition and (2) by decreasing the aboveground net primary productivity response to N fertilization experiments from 91 to 57 g C m-2 yr-1. Modeled growth response to N deposition was most sensitive to altering the processes that control plant N uptake and the pathways of N loss. The response to N deposition also increased with a more closed N cycle (reduced N fixation and N gas loss) and decreased when prioritizing microbial over plant uptake of soil inorganic N. The net effect of all the modifications to the CLM-CN resulted in greater retention of N deposition and a greater role of synergy between N deposition and rising atmospheric CO2 as a mechanism governing increases in temperate forest primary production over the 20th century. Overall, testing models with both the response to gradual increases in N inputs over decades (N deposition) and N pulse additions of N over multiple years (N fertilization) allows for greater understanding of the mechanisms governing C-N coupling.

Extended Mixed-Efects Item Response Models with the MH-RM Algorithm

ERIC Educational Resources Information Center

Chalmers, R. Philip

2015-01-01

A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…

Constrained and Unconstrained Partial Adjacent Category Logit Models for Ordinal Response Variables

ERIC Educational Resources Information Center

Fullerton, Andrew S.; Xu, Jun

2018-01-01

Adjacent category logit models are ordered regression models that focus on comparisons of adjacent categories. These models are particularly useful for ordinal response variables with categories that are of substantive interest. In this article, we consider unconstrained and constrained versions of the partial adjacent category logit model, which…

The School Implementation Scale: Measuring Implementation in Response to Intervention Models

ERIC Educational Resources Information Center

Erickson, Amy Gaumer; Noonan, Pattie M.; Jenson, Ronda

2012-01-01

Models of response to intervention (RTI) have been widely developed and implemented and have expanded to include integrated academic/behavior RTI models. Until recently, evaluation of model effectiveness has focused primarily on student-level data, but additional measures of treatment integrity within these multi-tiered models are emerging to…

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

A potato model intercomparison across varying climates and productivity levels

USDA-ARS?s Scientific Manuscript database

A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States) ...

A Prestressed Cable Network Model of the Adherent Cell Cytoskeleton

PubMed Central

Coughlin, Mark F.; Stamenović, Dimitrije

2003-01-01

A prestressed cable network is used to model the deformability of the adherent cell actin cytoskeleton. The overall and microstructural model geometries and cable mechanical properties were assigned values based on observations from living cells and mechanical measurements on isolated actin filaments, respectively. The models were deformed to mimic cell poking (CP), magnetic twisting cytometry (MTC) and magnetic bead microrheometry (MBM) measurements on living adherent cells. The models qualitatively and quantitatively captured the fibroblast cell response to the deformation imposed by CP while exhibiting only some qualitative features of the cell response to MTC and MBM. The model for CP revealed that the tensed peripheral actin filaments provide the key resistance to indentation. The actin filament tension that provides mechanical integrity to the network was estimated at ∼158 pN, and the nonlinear mechanical response during CP originates from filament kinematics. The MTC and MBM simulations revealed that the model is incomplete, however, these simulations show cable tension as a key determinant of the model response. PMID:12547813

A prestressed cable network model of the adherent cell cytoskeleton.

PubMed

Coughlin, Mark F; Stamenović, Dimitrije

2003-02-01

A prestressed cable network is used to model the deformability of the adherent cell actin cytoskeleton. The overall and microstructural model geometries and cable mechanical properties were assigned values based on observations from living cells and mechanical measurements on isolated actin filaments, respectively. The models were deformed to mimic cell poking (CP), magnetic twisting cytometry (MTC) and magnetic bead microrheometry (MBM) measurements on living adherent cells. The models qualitatively and quantitatively captured the fibroblast cell response to the deformation imposed by CP while exhibiting only some qualitative features of the cell response to MTC and MBM. The model for CP revealed that the tensed peripheral actin filaments provide the key resistance to indentation. The actin filament tension that provides mechanical integrity to the network was estimated at approximately 158 pN, and the nonlinear mechanical response during CP originates from filament kinematics. The MTC and MBM simulations revealed that the model is incomplete, however, these simulations show cable tension as a key determinant of the model response.

A Review of the Combination of Experimental Measurements and Fibril-Reinforced Modeling for Investigation of Articular Cartilage and Chondrocyte Response to Loading

PubMed Central

Wilson, Wouter; Isaksson, Hanna; Jurvelin, Jukka S.; Herzog, Walter; Korhonen, Rami K.

2013-01-01

The function of articular cartilage depends on its structure and composition, sensitively impaired in disease (e.g. osteoarthritis, OA). Responses of chondrocytes to tissue loading are modulated by the structure. Altered cell responses as an effect of OA may regulate cartilage mechanotransduction and cell biosynthesis. To be able to evaluate cell responses and factors affecting the onset and progression of OA, local tissue and cell stresses and strains in cartilage need to be characterized. This is extremely challenging with the presently available experimental techniques and therefore computational modeling is required. Modern models of articular cartilage are inhomogeneous and anisotropic, and they include many aspects of the real tissue structure and composition. In this paper, we provide an overview of the computational applications that have been developed for modeling the mechanics of articular cartilage at the tissue and cellular level. We concentrate on the use of fibril-reinforced models of cartilage. Furthermore, we introduce practical considerations for modeling applications, including also experimental tests that can be combined with the modeling approach. At the end, we discuss the prospects for patient-specific models when aiming to use finite element modeling analysis and evaluation of articular cartilage function, cellular responses, failure points, OA progression, and rehabilitation. PMID:23653665

Modeling the hysteretic moisture and temperature responses of soil carbon decomposition resulting from organo-mineral interactions

NASA Astrophysics Data System (ADS)

Tang, J.; Riley, W. J.

2017-12-01

Most existing soil carbon cycle models have modeled the moisture and temperature dependence of soil respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how soil carbon decomposition responds to changes in soil moisture and temperature under the influence of organo-mineral interactions. We found that both the temperature and moisture responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and moisture forcing affect soil carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and moisture response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and moisture forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and moisture dependency produces significantly different estimations of soil carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.

Linking normative models of natural tasks to descriptive models of neural response.

PubMed

Jaini, Priyank; Burge, Johannes

2017-10-01

Understanding how nervous systems exploit task-relevant properties of sensory stimuli to perform natural tasks is fundamental to the study of perceptual systems. However, there are few formal methods for determining which stimulus properties are most useful for a given natural task. As a consequence, it is difficult to develop principled models for how to compute task-relevant latent variables from natural signals, and it is difficult to evaluate descriptive models fit to neural response. Accuracy maximization analysis (AMA) is a recently developed Bayesian method for finding the optimal task-specific filters (receptive fields). Here, we introduce AMA-Gauss, a new faster form of AMA that incorporates the assumption that the class-conditional filter responses are Gaussian distributed. Then, we use AMA-Gauss to show that its assumptions are justified for two fundamental visual tasks: retinal speed estimation and binocular disparity estimation. Next, we show that AMA-Gauss has striking formal similarities to popular quadratic models of neural response: the energy model and the generalized quadratic model (GQM). Together, these developments deepen our understanding of why the energy model of neural response have proven useful, improve our ability to evaluate results from subunit model fits to neural data, and should help accelerate psychophysics and neuroscience research with natural stimuli.

Identification and experimental validation of damping ratios of different human body segments through anthropometric vibratory model in standing posture.

PubMed

Gupta, T C

2007-08-01

A 15 degrees of freedom lumped parameter vibratory model of human body is developed, for vertical mode vibrations, using anthropometric data of the 50th percentile US male. The mass and stiffness of various segments are determined from the elastic modulii of bones and tissues and from the anthropometric data available, assuming the shape of all the segments is ellipsoidal. The damping ratio of each segment is estimated on the basis of the physical structure of the body in a particular posture. Damping constants of various segments are calculated from these damping ratios. The human body is modeled as a linear spring-mass-damper system. The optimal values of the damping ratios of the body segments are estimated, for the 15 degrees of freedom model of the 50th percentile US male, by comparing the response of the model with the experimental response. Formulating a similar vibratory model of the 50th percentile Indian male and comparing the frequency response of the model with the experimental response of the same group of subjects validate the modeling procedure. A range of damping ratios has been considered to develop a vibratory model, which can predict the vertical harmonic response of the human body.

A method to model anticipatory postural control in driver braking events.

PubMed

Östh, Jonas; Eliasson, Erik; Happee, Riender; Brolin, Karin

2014-09-01

Human body models (HBMs) for vehicle occupant simulations have recently been extended with active muscles and postural control strategies. Feedback control has been used to model occupant responses to autonomous braking interventions. However, driver postural responses during driver initiated braking differ greatly from autonomous braking. In the present study, an anticipatory postural response was hypothesized, modelled in a whole-body HBM with feedback controlled muscles, and validated using existing volunteer data. The anticipatory response was modelled as a time dependent change in the reference value for the feedback controllers, which generates correcting moments to counteract the braking deceleration. The results showed that, in 11 m/s(2) driver braking simulations, including the anticipatory postural response reduced the peak forward displacement of the head by 100mm, of the shoulder by 30 mm, while the peak head flexion rotation was reduced by 18°. The HBM kinematic response was within a one standard deviation corridor of corresponding test data from volunteers performing maximum braking. It was concluded that the hypothesized anticipatory responses can be modelled by changing the reference positions of the individual joint feedback controllers that regulate muscle activation levels. The addition of anticipatory postural control muscle activations appears to explain the difference in occupant kinematics between driver and autonomous braking. This method of modelling postural reactions can be applied to the simulation of other driver voluntary actions, such as emergency avoidance by steering. Copyright © 2014. Published by Elsevier B.V.

Anomalous neuronal responses to fluctuated inputs

NASA Astrophysics Data System (ADS)

Hosaka, Ryosuke; Sakai, Yutaka

2015-10-01

The irregular firing of a cortical neuron is thought to result from a highly fluctuating drive that is generated by the balance of excitatory and inhibitory synaptic inputs. A previous study reported anomalous responses of the Hodgkin-Huxley neuron to the fluctuated inputs where an irregularity of spike trains is inversely proportional to an input irregularity. In the current study, we investigated the origin of these anomalous responses with the Hindmarsh-Rose neuron model, map-based models, and a simple mixture of interspike interval distributions. First, we specified the parameter regions for the bifurcations in the Hindmarsh-Rose model, and we confirmed that the model reproduced the anomalous responses in the dynamics of the saddle-node and subcritical Hopf bifurcations. For both bifurcations, the Hindmarsh-Rose model shows bistability in the resting state and the repetitive firing state, which indicated that the bistability was the origin of the anomalous input-output relationship. Similarly, the map-based model that contained bistability reproduced the anomalous responses, while the model without bistability did not. These results were supported by additional findings that the anomalous responses were reproduced by mimicking the bistable firing with a mixture of two different interspike interval distributions. Decorrelation of spike trains is important for neural information processing. For such spike train decorrelation, irregular firing is key. Our results indicated that irregular firing can emerge from fluctuating drives, even weak ones, under conditions involving bistability. The anomalous responses, therefore, contribute to efficient processing in the brain.

RAS mutations predict radiologic and pathologic response in patients treated with chemotherapy prior to resection of colorectal liver metastases

PubMed Central

Mise, Yoshihiro; Kopetz, Scott; Loyer, Evelyne M.; Andreou, Andreas; Cooper, Amanda B.; Kaur, Harmeet; Aloia, Thomas A.; Maru, Dipen M.; Vauthey, Jean-Nicolas

2014-01-01

Purpose RAS mutations have been reported to be a potential prognostic factor in patients with colorectal liver metastases (CLM). However, the impact of RAS mutations on response to chemotherapy remains unclear. We sought to determine the association between RAS mutations and response to preoperative chemotherapy and their impact on survival in patients undergoing curative resection of CLM. Methods RAS mutational status was assessed and its relation to morphologic response and pathologic response was investigated in 184 patients meeting inclusion criteria. Predictors of survival were assessed. The prognostic impact of RAS mutational status was then analyzed using two different multivariate models including either radiologic morphologic response (model 1) or pathologic response (model 2). Results Optimal morphologic response and major pathologic response were more common in patients with wild-type RAS (32.9% and 58.9%, respectively) than in patients with RAS mutations (10.5% and 36.8%; P =.006 and .015, respectively). Multivariate analysis confirmed that wild-type RAS was a strong predictor of optimal morphologic response (odds ratio [OR], 4.38; 95% CI, 1.45-13.2) and major pathologic response (OR,2.79; 95% CI, 1.29-6.04). RAS mutations were independently correlated with both overall survival and recurrence free-survival (hazard ratios, 3.25 and 2.02, respectively, in model 1, and 3.19 and 2.23, respectively, in model 2). Subanalysis revealed that RAS mutational status clearly stratified prognosis in patients with inadequate response to preoperative chemotherapy. Conclusion RAS mutational status can be used to complement the current prognostic indicators for patients undergoing curative resection of CLM after preoperative modern chemotherapy. PMID:25227306

RAS mutations predict radiologic and pathologic response in patients treated with chemotherapy before resection of colorectal liver metastases.

PubMed

Zimmitti, Giuseppe; Shindoh, Junichi; Mise, Yoshihiro; Kopetz, Scott; Loyer, Evelyne M; Andreou, Andreas; Cooper, Amanda B; Kaur, Harmeet; Aloia, Thomas A; Maru, Dipen M; Vauthey, Jean-Nicolas

2015-03-01

RAS mutations have been reported to be a potential prognostic factor in patients with colorectal liver metastases (CLM). However, the impact of RAS mutations on response to chemotherapy remains unclear. The purpose of this study was to investigate the correlation between RAS mutations and response to preoperative chemotherapy and their impact on survival in patients undergoing curative resection of CLM. RAS mutational status was assessed and its relation to morphologic response and pathologic response was investigated in 184 patients meeting inclusion criteria. Predictors of survival were assessed. The prognostic impact of RAS mutational status was then analyzed using two different multivariate models, including either radiologic morphologic response (model 1) or pathologic response (model 2). Optimal morphologic response and major pathologic response were more common in patients with wild-type RAS (32.9 and 58.9%, respectively) than in patients with RAS mutations (10.5 and 36.8%; P = 0.006 and 0.015, respectively). Multivariate analysis confirmed that wild-type RAS was a strong predictor of optimal morphologic response [odds ratio (OR), 4.38; 95% CI 1.45-13.15] and major pathologic response (OR, 2.61; 95% CI 1.17-5.80). RAS mutations were independently correlated with both overall survival and recurrence free-survival (hazard ratios, 3.57 and 2.30, respectively, in model 1, and 3.19 and 2.09, respectively, in model 2). Subanalysis revealed that RAS mutational status clearly stratified survival in patients with inadequate response to preoperative chemotherapy. RAS mutational status can be used to complement the current prognostic indicators for patients undergoing curative resection of CLM after preoperative modern chemotherapy.

Numerical study of the direct pressure effect of acoustic waves in planar premixed flames

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

Schmidt, H.; Jimenez, C.

Recently the unsteady response of 1-D premixed flames to acoustic pressure waves for the range of frequencies below and above the inverse of the flame transit time was investigated experimentally using OH chemiluminescence Wangher (2008). They compared the frequency dependence of the measured response to the prediction of an analytical model proposed by Clavin et al. (1990), derived from the standard flame model (one-step Arrhenius kinetics) and to a similar model proposed by McIntosh (1991). Discrepancies between the experimental results and the model led to the conclusion that the standard model does not provide an adequate description of the unsteadymore » response of real flames and that it is necessary to investigate more realistic chemical models. Here we follow exactly this suggestion and perform numerical studies of the response of lean methane flames using different reaction mechanisms. We find that the global flame response obtained with both detailed chemistry (GRI3.0) and a reduced multi-step model by Peters (1996) lies slightly above the predictions of the analytical model, but is close to experimental results. We additionally used an irreversible one-step Arrhenius reaction model and show the effect of the pressure dependence of the global reaction rate in the flame response. Our results suggest first that the current models have to be extended to capture the amplitude and phase results of the detailed mechanisms, and second that the correlation between the heat release and the measured OH* chemiluminescence should be studied deeper. (author)« less

Lateralization of temporal lobe epilepsy by multimodal multinomial hippocampal response-driven models.

PubMed

Nazem-Zadeh, Mohammad-Reza; Elisevich, Kost V; Schwalb, Jason M; Bagher-Ebadian, Hassan; Mahmoudi, Fariborz; Soltanian-Zadeh, Hamid

2014-12-15

Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment. Copyright © 2014 Elsevier B.V. All rights reserved.

Adaptation and inhibition underlie responses to time-varying interaural phase cues in a model of inferior colliculus neurons.

PubMed

Borisyuk, Alla; Semple, Malcolm N; Rinzel, John

2002-10-01

A mathematical model was developed for exploring the sensitivity of low-frequency inferior colliculus (IC) neurons to interaural phase disparity (IPD). The formulation involves a firing-rate-type model that does not include spikes per se. The model IC neuron receives IPD-tuned excitatory and inhibitory inputs (viewed as the output of a collection of cells in the medial superior olive). The model cell possesses cellular properties of firing rate adaptation and postinhibitory rebound (PIR). The descriptions of these mechanisms are biophysically reasonable, but only semi-quantitative. We seek to explain within a minimal model the experimentally observed mismatch between responses to IPD stimuli delivered dynamically and those delivered statically (McAlpine et al. 2000; Spitzer and Semple 1993). The model reproduces many features of the responses to static IPD presentations, binaural beat, and partial range sweep stimuli. These features include differences in responses to a stimulus presented in static or dynamic context: sharper tuning and phase shifts in response to binaural beats, and hysteresis and "rise-from-nowhere" in response to partial range sweeps. Our results suggest that dynamic response features are due to the structure of inputs and the presence of firing rate adaptation and PIR mechanism in IC cells, but do not depend on a specific biophysical mechanism. We demonstrate how the model's various components contribute to shaping the observed phenomena. For example, adaptation, PIR, and transmission delay shape phase advances and delays in responses to binaural beats, adaptation and PIR shape hysteresis in different ranges of IPD, and tuned inhibition underlies asymmetry in dynamic tuning properties. We also suggest experiments to test our modeling predictions: in vitro simulation of the binaural beat (phase advance at low beat frequencies, its dependence on firing rate), in vivo partial range sweep experiments (dependence of the hysteresis curve on parameters), and inhibition blocking experiments (to study inhibitory tuning properties by observation of phase shifts).

Modeling the intracellular pathogen-immune interaction with cure rate

NASA Astrophysics Data System (ADS)

Dubey, Balram; Dubey, Preeti; Dubey, Uma S.

2016-09-01

Many common and emergent infectious diseases like Influenza, SARS, Hepatitis, Ebola etc. are caused by viral pathogens. These infections can be controlled or prevented by understanding the dynamics of pathogen-immune interaction in vivo. In this paper, interaction of pathogens with uninfected and infected cells in presence or absence of immune response are considered in four different cases. In the first case, the model considers the saturated nonlinear infection rate and linear cure rate without absorption of pathogens into uninfected cells and without immune response. The next model considers the effect of absorption of pathogens into uninfected cells while all other terms are same as in the first case. The third model incorporates innate immune response, humoral immune response and Cytotoxic T lymphocytes (CTL) mediated immune response with cure rate and without absorption of pathogens into uninfected cells. The last model is an extension of the third model in which the effect of absorption of pathogens into uninfected cells has been considered. Positivity and boundedness of solutions are established to ensure the well-posedness of the problem. It has been found that all the four models have two equilibria, namely, pathogen-free equilibrium point and pathogen-present equilibrium point. In each case, stability analysis of each equilibrium point is investigated. Pathogen-free equilibrium is globally asymptotically stable when basic reproduction number is less or equal to unity. This implies that control or prevention of infection is independent of initial concentration of uninfected cells, infected cells, pathogens and immune responses in the body. The proposed models show that introduction of immune response and cure rate strongly affects the stability behavior of the system. Further, on computing basic reproduction number, it has been found to be minimum for the fourth model vis-a-vis other models. The analytical findings of each model have been exemplified by numerical simulations.

An investigation of human body model morphing for the assessment of abdomen responses to impact against a population of test subjects.

PubMed

Beillas, Philippe; Berthet, Fabien

2017-05-29

Human body models have the potential to better describe the human anatomy and variability than dummies. However, data sets available to verify the human response to impact are typically limited in numbers, and they are not size or gender specific. The objective of this study was to investigate the use of model morphing methodologies within that context. In this study, a simple human model scaling methodology was developed to morph two detailed human models (Global Human Body Model Consortium models 50th male, M50, and 5th female, F05) to the dimensions of post mortem human surrogates (PMHS) used in published literature. The methodology was then successfully applied to 52 PMHS tested in 14 impact conditions loading the abdomen. The corresponding 104 simulations were compared to the responses of the PMHS and to the responses of the baseline models without scaling (28 simulations). The responses were analysed using the CORA method and peak values. The results suggest that model scaling leads to an improvement of the predicted force and deflection but has more marginal effects on the predicted abdominal compressions. M50 and F05 models scaled to the same PMHS were also found to have similar external responses, but large differences were found between the two sets of models for the strain energy densities in the liver and the spleen for mid-abdomen impact simulations. These differences, which were attributed to the anatomical differences in the abdomen of the baseline models, highlight the importance of the selection of the impact condition for simulation studies, especially if the organ location is not known in the test. While the methodology could be further improved, it shows the feasibility of using model scaling methodologies to compare human models of different sizes and to evaluate scaling approaches within the context of human model validation.

A Comparison of Three Polytomous Item Response Theory Models in the Context of Testlet Scoring.

ERIC Educational Resources Information Center

Cook, Karon F.; Dodd, Barbara G.; Fitzpatrick, Steven J.

1999-01-01

The partial-credit model, the generalized partial-credit model, and the graded-response model were compared in the context of testlet scoring using Scholastic Assessment Tests results (n=2,548) and a simulated data set. Results favor the partial-credit model in this context; considerations for model selection in other contexts are discussed. (SLD)

An NCME Instructional Module on Item-Fit Statistics for Item Response Theory Models

ERIC Educational Resources Information Center

Ames, Allison J.; Penfield, Randall D.

2015-01-01

Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing…

Improvement in latent variable indirect response modeling of multiple categorical clinical endpoints: application to modeling of guselkumab treatment effects in psoriatic patients.

PubMed

Hu, Chuanpu; Randazzo, Bruce; Sharma, Amarnath; Zhou, Honghui

2017-10-01

Exposure-response modeling plays an important role in optimizing dose and dosing regimens during clinical drug development. The modeling of multiple endpoints is made possible in part by recent progress in latent variable indirect response (IDR) modeling for ordered categorical endpoints. This manuscript aims to investigate the level of improvement achievable by jointly modeling two such endpoints in the latent variable IDR modeling framework through the sharing of model parameters. This is illustrated with an application to the exposure-response of guselkumab, a human IgG1 monoclonal antibody in clinical development that blocks IL-23. A Phase 2b study was conducted in 238 patients with psoriasis for which disease severity was assessed using Psoriasis Area and Severity Index (PASI) and Physician's Global Assessment (PGA) scores. A latent variable Type I IDR model was developed to evaluate the therapeutic effect of guselkumab dosing on 75, 90 and 100% improvement of PASI scores from baseline and PGA scores, with placebo effect empirically modeled. The results showed that the joint model is able to describe the observed data better with fewer parameters compared with the common approach of separately modeling the endpoints.

Biological Modeling As A Method for Data Evaluation and ...

EPA Pesticide Factsheets

Biological Models, evaluating consistency of data and integrating diverse data, examples of pharmacokinetics and response and pharmacodynamics Biological Models, evaluating consistency of data and integrating diverse data, examples of pharmacokinetics and response and pharmacodynamics

Validity of Multiprocess IRT Models for Separating Content and Response Styles

ERIC Educational Resources Information Center

Plieninger, Hansjörg; Meiser, Thorsten

2014-01-01

Response styles, the tendency to respond to Likert-type items irrespective of content, are a widely known threat to the reliability and validity of self-report measures. However, it is still debated how to measure and control for response styles such as extreme responding. Recently, multiprocess item response theory models have been proposed that…

The Dirichlet-Multinomial Model for Multivariate Randomized Response Data and Small Samples

ERIC Educational Resources Information Center

Avetisyan, Marianna; Fox, Jean-Paul

2012-01-01

In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when observing multivariate response data. The beta-binomial model for binary RR data will be generalized…

Using the Nominal Response Model to Evaluate Response Category Discrimination in the PROMIS Emotional Distress Item Pools

ERIC Educational Resources Information Center

Preston, Kathleen; Reise, Steven; Cai, Li; Hays, Ron D.

2011-01-01

The authors used a nominal response item response theory model to estimate category boundary discrimination (CBD) parameters for items drawn from the Emotional Distress item pools (Depression, Anxiety, and Anger) developed in the Patient-Reported Outcomes Measurement Information Systems (PROMIS) project. For polytomous items with ordered response…

A Model for Screening Twice-Exceptional Students (Gifted with Learning Disabilities) within a Response to Intervention Paradigm

ERIC Educational Resources Information Center

McCallum, R. Steve; Bell, Sherry Mee; Coles, Jeremy Thomas; Miller, Kelli Caldwell; Hopkins, Michael B.; Hilton-Prillhart, Angela

2013-01-01

The purpose of this article is to present a model for screening for twice-exceptional status (i.e., gifted students who have a learning disability). Curriculum-based measures (Monitoring Instructional Responsiveness: Reading and Monitoring Instructional Responsiveness: Math) were administered to 1,242 third-grade students within a Response to…

Item Response Models for Local Dependence among Multiple Ratings

ERIC Educational Resources Information Center

Wang, Wen-Chung; Su, Chi-Ming; Qiu, Xue-Lan

2014-01-01

Ratings given to the same item response may have a stronger correlation than those given to different item responses, especially when raters interact with one another before giving ratings. The rater bundle model was developed to account for such local dependence by forming multiple ratings given to an item response as a bundle and assigning…

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…

Thermal cut-off response modelling of universal motors

NASA Astrophysics Data System (ADS)

Thangaveloo, Kashveen; Chin, Yung Shin

2017-04-01

This paper presents a model to predict the thermal cut-off (TCO) response behaviour in universal motors. The mathematical model includes the calculations of heat loss in the universal motor and the flow characteristics around the TCO component which together are the main parameters for TCO response prediction. In order to accurately predict the TCO component temperature, factors like the TCO component resistance, the effect of ambient, and the flow conditions through the motor are taken into account to improve the prediction accuracy of the model.

Topical Modulation of the Burn Wound Inflammatory Response to Improve Short and Long Term Outcomes

DTIC Science & Technology

2015-10-15

between p38MAPK signaling, wound inflammatory response, wound healing and long-term scar formation using a burn model in the female red Duroc pig ... pig model burn model as the appropriate wound healing model that resembles human response. At the end of the project, we will have a well-defined animal...scarring (period before the award of the current grant). Table 1 Study ID Wound Dates Treatment Pigs # Duration of study Pg001 Dermatome Feb

Topical Modulation of the Burn Wound Inflammatory Response to Improve Short and Long Term Outcomes

DTIC Science & Technology

2015-10-01

between p38MAPK signaling, wound inflammatory response, wound healing and long-term scar formation using a burn model in the female red Duroc pig ... pig model burn model as the appropriate wound healing model that resembles human response. At the end of the project, we will have a well-defined animal...scarring (period before the award of the current grant). Table 1 Study ID Wound Dates Treatment Pigs # Duration of study Pg001 Dermatome Feb

Modified Maxium Likelihood Estimation Method for Completely Separated and Quasi-Completely Separated Data for a Dose-Response Model

DTIC Science & Technology

2015-08-01

McCullagh, P.; Nelder, J.A. Generalized Linear Model , 2nd ed.; Chapman and Hall: London, 1989. 7. Johnston, J. Econometric Methods, 3rd ed.; McGraw...FOR A DOSE-RESPONSE MODEL ECBC-TN-068 Kyong H. Park Steven J. Lagan RESEARCH AND TECHNOLOGY DIRECTORATE August 2015 Approved for public release...Likelihood Estimation Method for Completely Separated and Quasi-Completely Separated Data for a Dose-Response Model 5a. CONTRACT NUMBER 5b. GRANT

PHYSIOLOCIGALLY BASED PHARMACOKINETIC (PBPK) MODELING AND MODE OF ACTION IN DOSE-RESPONSE ASSESSMENT

EPA Science Inventory

PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODELING AND MODE OF ACTION IN DOSE-RESPONSE ASSESSMENT. Barton HA. Experimental Toxicology Division, National Health and Environmental Effects Laboratory, ORD, U.S. EPA
Dose-response analysis requires quantitatively linking infor...

Mean field model of acetylcholine mediated dynamics in the cerebral cortex.

PubMed

Clearwater, J M; Rennie, C J; Robinson, P A

2007-12-01

A recent continuum model of the large scale electrical activity of the cerebral cortex is generalized to include cholinergic modulation. In this model, dynamic modulation of synaptic strength acts over the time scales of nicotinic and muscarinic receptor action. The cortical model is analyzed to determine the effect of acetylcholine (ACh) on its steady states, linear stability, spectrum, and temporal responses to changes in subcortical input. ACh increases the firing rate in steady states of the system. Changing ACh concentration does not introduce oscillatory behavior into the system, but increases the overall spectral power. Model responses to pulses in subcortical input are affected by the tonic level of ACh concentration, with higher levels of ACh increasing the magnitude firing rate response of excitatory cortical neurons to pulses of subcortical input. Numerical simulations are used to explore the temporal dynamics of the model in response to changes in ACh concentration. Evidence is seen of a transition from a state in which intracortical inputs are emphasized to a state where thalamic afferents have enhanced influence. Perturbations in ACh concentration cause changes in the firing rate of cortical neurons, with rapid responses due to fast acting facilitatory effects of nicotinic receptors on subcortical afferents, and slower responses due to muscarinic suppression of intracortical connections. Together, these numerical simulations demonstrate that the actions of ACh could be a significant factor modulating early components of evoked response potentials.

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

Modeling Population and Ecosystem Response to Sublethal Toxicant Exposure

DTIC Science & Technology

2000-09-30

Modeling Population and Ecosystem Response to Sublethal Toxicant Exposure Principal Investigator: Roger M. Nisbet Department of Ecology, Evolution...DATES COVERED 00-00-2000 to 00-00-2000 4. TITLE AND SUBTITLE Modeling Population and Ecosystem Response to Sublethal Toxicant Exposure 5a...those of real populations. We have also investigated how toxicants may affect the stability of the system. If the toxicant effect is primarily an

A 1-D model of the nonlinear dynamics of the human lumbar intervertebral disc

NASA Astrophysics Data System (ADS)

Marini, Giacomo; Huber, Gerd; Püschel, Klaus; Ferguson, Stephen J.

2017-01-01

Lumped parameter models of the spine have been developed to investigate its response to whole body vibration. However, these models assume the behaviour of the intervertebral disc to be linear-elastic. Recently, the authors have reported on the nonlinear dynamic behaviour of the human lumbar intervertebral disc. This response was shown to be dependent on the applied preload and amplitude of the stimuli. However, the mechanical properties of a standard linear elastic model are not dependent on the current deformation state of the system. The aim of this study was therefore to develop a model that is able to describe the axial, nonlinear quasi-static response and to predict the nonlinear dynamic characteristics of the disc. The ability to adapt the model to an individual disc's response was a specific focus of the study, with model validation performed against prior experimental data. The influence of the numerical parameters used in the simulations was investigated. The developed model exhibited an axial quasi-static and dynamic response, which agreed well with the corresponding experiments. However, the model needs further improvement to capture additional peculiar characteristics of the system dynamics, such as the change of mean point of oscillation exhibited by the specimens when oscillating in the region of nonlinear resonance. Reference time steps were identified for specific integration scheme. The study has demonstrated that taking into account the nonlinear-elastic behaviour typical of the intervertebral disc results in a predicted system oscillation much closer to the physiological response than that provided by linear-elastic models. For dynamic analysis, the use of standard linear-elastic models should be avoided, or restricted to study cases where the amplitude of the stimuli is relatively small.

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.

Ordinal probability effect measures for group comparisons in multinomial cumulative link models.

PubMed

Agresti, Alan; Kateri, Maria

2017-03-01

We consider simple ordinal model-based probability effect measures for comparing distributions of two groups, adjusted for explanatory variables. An "ordinal superiority" measure summarizes the probability that an observation from one distribution falls above an independent observation from the other distribution, adjusted for explanatory variables in a model. The measure applies directly to normal linear models and to a normal latent variable model for ordinal response variables. It equals Φ(β/2) for the corresponding ordinal model that applies a probit link function to cumulative multinomial probabilities, for standard normal cdf Φ and effect β that is the coefficient of the group indicator variable. For the more general latent variable model for ordinal responses that corresponds to a linear model with other possible error distributions and corresponding link functions for cumulative multinomial probabilities, the ordinal superiority measure equals exp(β)/[1+exp(β)] with the log-log link and equals approximately exp(β/2)/[1+exp(β/2)] with the logit link, where β is the group effect. Another ordinal superiority measure generalizes the difference of proportions from binary to ordinal responses. We also present related measures directly for ordinal models for the observed response that need not assume corresponding latent response models. We present confidence intervals for the measures and illustrate with an example. © 2016, The International Biometric Society.

Pilot-model analysis and simulation study of effect of control task desired control response

NASA Technical Reports Server (NTRS)

Adams, J. J.; Gera, J.; Jaudon, J. B.

1978-01-01

A pilot model analysis was performed that relates pilot control compensation, pilot aircraft system response, and aircraft response characteristics for longitudinal control. The results show that a higher aircraft short period frequency is required to achieve superior pilot aircraft system response in an altitude control task than is required in an attitude control task. These results were confirmed by a simulation study of target tracking. It was concluded that the pilot model analysis provides a theoretical basis for determining the effect of control task on pilot opinions.

Modeling the action-potential-sensitive nonlinear-optical response of myelinated nerve fibers and short-term memory

NASA Astrophysics Data System (ADS)

Shneider, M. N.; Voronin, A. A.; Zheltikov, A. M.

2011-11-01

The Goldman-Albus treatment of the action-potential dynamics is combined with a phenomenological description of molecular hyperpolarizabilities into a closed-form model of the action-potential-sensitive second-harmonic response of myelinated nerve fibers with nodes of Ranvier. This response is shown to be sensitive to nerve demyelination, thus enabling an optical diagnosis of various demyelinating diseases, including multiple sclerosis. The model is applied to examine the nonlinear-optical response of a three-neuron reverberating circuit—the basic element of short-term memory.

Digital simulation and experimental evaluation of the CO2-H(plus) control of pulmonary ventilation

NASA Technical Reports Server (NTRS)

Milhorn, H. T., Jr.; Reynolds, W. J.

1972-01-01

Previous models of the CO2-H(+) control of ventilation have been concerned either with the response to CO2 inhalation, or the response to perfusion of the surface of the medulla with mock cerebrospinal fluid having a high P sub CO2. Simulation of both responses with the same model has not been attempted. The purpose of the present study was two fold; first to develop such a model and, second, to obtain experimental data from human subjects for both developing this model and for evaluating this and future models.

A Third-Order Item Response Theory Model for Modeling the Effects of Domains and Subdomains in Large-Scale Educational Assessment Surveys

ERIC Educational Resources Information Center

Rijmen, Frank; Jeon, Minjeong; von Davier, Matthias; Rabe-Hesketh, Sophia

2014-01-01

Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…

DEVELOPMENT AND MODIFICATION OF A RESPONSE CLASS VIA POSITIVE AND NEGATIVE REINFORCEMENT: A TRANSLATIONAL APPROACH

PubMed Central

Mendres, Amber E; Borrero, John C

2010-01-01

When responses function to produce the same reinforcer, a response class exists. Researchers have examined response classes in applied settings; however, the challenges associated with conducting applied research on response class development have recently necessitated the development of an analogue response class model. To date, little research has examined response classes that are strengthened by negative reinforcement. The current investigation was designed to develop a laboratory model of a response class through positive reinforcement (i.e., points exchangeable for money) and through negative reinforcement (i.e., the avoidance of scheduled point losses) with 11 college students as participants and clicks as the operant. Results of both the positive and negative reinforcement evaluations showed that participants usually selected the least effortful response that produced points or the avoidance of point losses, respectively. The applied implications of the findings are discussed, along with the relevance of the present model to the study of punishment and resurgence. PMID:21541150

SCIENTIFIC UNCERTAINTIES IN ATMOSPHERIC MERCURY MODELS III: BOUNDARY AND INITIAL CONDITIONS, MODEL GRID RESOLUTION, AND HG(II) REDUCTION MECHANISMS

EPA Science Inventory

In this study we investigate the CMAQ model response in terms of simulated mercury concentration and deposition to boundary/initial conditions (BC/IC), model grid resolution (12- versus 36-km), and two alternative Hg(II) reduction mechanisms. The model response to the change of g...

A Multidimensional Item Response Model: Constrained Latent Class Analysis Using the Gibbs Sampler and Posterior Predictive Checks.

ERIC Educational Resources Information Center

Hoijtink, Herbert; Molenaar, Ivo W.

1997-01-01

This paper shows that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. Parameters of this latent class model are estimated using an application of the Gibbs sampler, and model fit is investigated using posterior predictive checks. (SLD)

A Person Fit Test for IRT Models for Polytomous Items

ERIC Educational Resources Information Center

Glas, C. A. W.; Dagohoy, Anna Villa T.

2007-01-01

A person fit test based on the Lagrange multiplier test is presented for three item response theory models for polytomous items: the generalized partial credit model, the sequential model, and the graded response model. The test can also be used in the framework of multidimensional ability parameters. It is shown that the Lagrange multiplier…

Asking Sensitive Questions: A Statistical Power Analysis of Randomized Response Models

ERIC Educational Resources Information Center

Ulrich, Rolf; Schroter, Hannes; Striegel, Heiko; Simon, Perikles

2012-01-01

This article derives the power curves for a Wald test that can be applied to randomized response models when small prevalence rates must be assessed (e.g., detecting doping behavior among elite athletes). These curves enable the assessment of the statistical power that is associated with each model (e.g., Warner's model, crosswise model, unrelated…

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

Stimulus-response compatibility and psychological refractory period effects: implications for response selection

NASA Technical Reports Server (NTRS)

Lien, Mei-Ching; Proctor, Robert W.

2002-01-01

The purpose of this paper was to provide insight into the nature of response selection by reviewing the literature on stimulus-response compatibility (SRC) effects and the psychological refractory period (PRP) effect individually and jointly. The empirical findings and theoretical explanations of SRC effects that have been studied within a single-task context suggest that there are two response-selection routes-automatic activation and intentional translation. In contrast, all major PRP models reviewed in this paper have treated response selection as a single processing stage. In particular, the response-selection bottleneck (RSB) model assumes that the processing of Task 1 and Task 2 comprises two separate streams and that the PRP effect is due to a bottleneck located at response selection. Yet, considerable evidence from studies of SRC in the PRP paradigm shows that the processing of the two tasks is more interactive than is suggested by the RSB model and by most other models of the PRP effect. The major implication drawn from the studies of SRC effects in the PRP context is that response activation is a distinct process from final response selection. Response activation is based on both long-term and short-term task-defined S-R associations and occurs automatically and in parallel for the two tasks. The final response selection is an intentional act required even for highly compatible and practiced tasks and is restricted to processing one task at a time. Investigations of SRC effects and response-selection variables in dual-task contexts should be conducted more systematically because they provide significant insight into the nature of response-selection mechanisms.

An investigation of helicopter dynamic coupling using an analytical model

NASA Technical Reports Server (NTRS)

Keller, Jeffrey D.

1995-01-01

Many attempts have been made in recent years to predict the off-axis response of a helicopter to control inputs, and most have had little success. Since physical insight is limited by the complexity of numerical simulation models, this paper examines the off-axis response problem using an analytical model, with the goal of understanding the mechanics of the coupling. A new induced velocity model is extended to include the effects of wake distortion from pitch rate. It is shown that the inclusion of these results in a significant change in the lateral flap response to a steady pitch rate. The proposed inflow model is coupled with the full rotor/body dynamics, and comparisons are made between the model and flight test data for a UH-60 in hover. Results show that inclusion of induced velocity variations due to shaft rate improves correlation in the pitch response to lateral cycle inputs.

Annular mode changes in the CMIP5 simulations

NASA Astrophysics Data System (ADS)

Gillett, N. P.; Fyfe, J. C.

2013-03-01

We investigate simulated changes in the annular modes in historical and RCP 4.5 scenario simulations of 37 models from the fifth Coupled Model Intercomparison Project (CMIP5), a much larger ensemble of models than has previously been used to investigate annular mode trends, with improved resolution and forcings. The CMIP5 models on average simulate increases in the Northern Annular Mode (NAM) and Southern Annular Mode (SAM) in every season by 2100, and no CMIP5 model simulates a significant decrease in either the NAM or SAM in any season. No significant increase in the NAM or North Atlantic Oscillation (NAO) is simulated in response to volcanic aerosol, and no significant NAM or NAO response to solar irradiance variations is simulated. The CMIP5 models simulate a significant negative SAM response to volcanic aerosol in MAM and JJA, and a significant positive SAM response to solar irradiance variations in MAM, JJA and DJF.

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

Finite Element Modeling of the Buckling Response of Sandwich Panels

NASA Technical Reports Server (NTRS)

Rose, Cheryl A.; Moore, David F.; Knight, Norman F., Jr.; Rankin, Charles C.

2002-01-01

A comparative study of different modeling approaches for predicting sandwich panel buckling response is described. The study considers sandwich panels with anisotropic face sheets and a very thick core. Results from conventional analytical solutions for sandwich panel overall buckling and face-sheet-wrinkling type modes are compared with solutions obtained using different finite element modeling approaches. Finite element solutions are obtained using layered shell element models, with and without transverse shear flexibility, layered shell/solid element models, with shell elements for the face sheets and solid elements for the core, and sandwich models using a recently developed specialty sandwich element. Convergence characteristics of the shell/solid and sandwich element modeling approaches with respect to in-plane and through-the-thickness discretization, are demonstrated. Results of the study indicate that the specialty sandwich element provides an accurate and effective modeling approach for predicting both overall and localized sandwich panel buckling response. Furthermore, results indicate that anisotropy of the face sheets, along with the ratio of principle elastic moduli, affect the buckling response and these effects may not be represented accurately by analytical solutions. Modeling recommendations are also provided.

High Strain Rate Deformation Modeling of a Polymer Matrix Composite. Part 1; Matrix Constitutive Equations

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Stouffer, Donald C.

1998-01-01

Recently applications have exposed polymer matrix composite materials to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under these extreme conditions. In this first paper of a two part report, background information is presented, along with the constitutive equations which will be used to model the rate dependent nonlinear deformation response of the polymer matrix. Strain rate dependent inelastic constitutive models which were originally developed to model the viscoplastic deformation of metals have been adapted to model the nonlinear viscoelastic deformation of polymers. The modified equations were correlated by analyzing the tensile/ compressive response of both 977-2 toughened epoxy matrix and PEEK thermoplastic matrix over a variety of strain rates. For the cases examined, the modified constitutive equations appear to do an adequate job of modeling the polymer deformation response. A second follow-up paper will describe the implementation of the polymer deformation model into a composite micromechanical model, to allow for the modeling of the nonlinear, rate dependent deformation response of polymer matrix composites.

Can responses to basic non-numerical visual features explain neural numerosity responses?

PubMed

Harvey, Ben M; Dumoulin, Serge O

2017-04-01

Humans and many animals can distinguish between stimuli that differ in numerosity, the number of objects in a set. Human and macaque parietal lobes contain neurons that respond to changes in stimulus numerosity. However, basic non-numerical visual features can affect neural responses to and perception of numerosity, and visual features often co-vary with numerosity. Therefore, it is debated whether numerosity or co-varying low-level visual features underlie neural and behavioral responses to numerosity. To test the hypothesis that non-numerical visual features underlie neural numerosity responses in a human parietal numerosity map, we analyze responses to a group of numerosity stimulus configurations that have the same numerosity progression but vary considerably in their non-numerical visual features. Using ultra-high-field (7T) fMRI, we measure responses to these stimulus configurations in an area of posterior parietal cortex whose responses are believed to reflect numerosity-selective activity. We describe an fMRI analysis method to distinguish between alternative models of neural response functions, following a population receptive field (pRF) modeling approach. For each stimulus configuration, we first quantify the relationships between numerosity and several non-numerical visual features that have been proposed to underlie performance in numerosity discrimination tasks. We then determine how well responses to these non-numerical visual features predict the observed fMRI responses, and compare this to the predictions of responses to numerosity. We demonstrate that a numerosity response model predicts observed responses more accurately than models of responses to simple non-numerical visual features. As such, neural responses in cognitive processing need not reflect simpler properties of early sensory inputs. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Incorporating social groups' responses in a descriptive model for second- and higher-order impact identification

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

Sutheerawatthana, Pitch, E-mail: pitch.venture@gmail.co; Minato, Takayuki, E-mail: minato@k.u-tokyo.ac.j

The response of a social group is a missing element in the formal impact assessment model. Previous discussion of the involvement of social groups in an intervention has mainly focused on the formation of the intervention. This article discusses the involvement of social groups in a different way. A descriptive model is proposed by incorporating a social group's response into the concept of second- and higher-order effects. The model is developed based on a cause-effect relationship through the observation of phenomena in case studies. The model clarifies the process by which social groups interact with a lower-order effect and thenmore » generate a higher-order effect in an iterative manner. This study classifies social groups' responses into three forms-opposing, modifying, and advantage-taking action-and places them in six pathways. The model is expected to be used as an analytical tool for investigating and identifying impacts in the planning stage and as a framework for monitoring social groups' responses during the implementation stage of a policy, plan, program, or project (PPPPs).« less

High Speed Civil Transport Aircraft Simulation: Reference-H Cycle 1, MATLAB Implementation

NASA Technical Reports Server (NTRS)

Sotack, Robert A.; Chowdhry, Rajiv S.; Buttrill, Carey S.

1999-01-01

The mathematical model and associated code to simulate a high speed civil transport aircraft - the Boeing Reference H configuration - are described. The simulation was constructed in support of advanced control law research. In addition to providing time histories of the dynamic response, the code includes the capabilities for calculating trim solutions and for generating linear models. The simulation relies on the nonlinear, six-degree-of-freedom equations which govern the motion of a rigid aircraft in atmospheric flight. The 1962 Standard Atmosphere Tables are used along with a turbulence model to simulate the Earth atmosphere. The aircraft model has three parts - an aerodynamic model, an engine model, and a mass model. These models use the data from the Boeing Reference H cycle 1 simulation data base. Models for the actuator dynamics, landing gear, and flight control system are not included in this aircraft model. Dynamic responses generated by the nonlinear simulation are presented and compared with results generated from alternate simulations at Boeing Commercial Aircraft Company and NASA Langley Research Center. Also, dynamic responses generated using linear models are presented and compared with dynamic responses generated using the nonlinear simulation.

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.

Spiritual and Affective Responses to a Physical Church and Corresponding Virtual Model.

PubMed

Murdoch, Matt; Davies, Jim

2017-11-01

Architectural and psychological theories posit that built environments have the potential to elicit complex psychological responses. However, few researchers have seriously explored this potential. Given the increasing importance and fidelity of virtual worlds, such research should explore whether virtual models of built environments are also capable of eliciting complex psychological responses. The goal of this study was to test these hypotheses, using a church, a corresponding virtual model, and an inclusive measure of state spirituality ("spiritual feelings"). Participants (n = 33) explored a physical church and corresponding virtual model, completing a measure of spiritual feelings after exploring the outside and inside of each version of the church. Using spiritual feelings after exploring the outside of the church as a baseline measure, change in state spirituality was assessed by taking the difference between spiritual feelings after exploring the inside and outside of the church (inside-outside) for both models. Although this change was greater in response to the physical church, there was no significant difference between the two models in eliciting such change in spiritual feelings. Despite the limitations of this exploratory study, these findings indicate that both built environments and corresponding virtual models are capable of evoking complex psychological responses.

Method for Vibration Response Simulation and Sensor Placement Optimization of a Machine Tool Spindle System with a Bearing Defect

PubMed Central

Cao, Hongrui; Niu, Linkai; He, Zhengjia

2012-01-01

Bearing defects are one of the most important mechanical sources for vibration and noise generation in machine tool spindles. In this study, an integrated finite element (FE) model is proposed to predict the vibration responses of a spindle bearing system with localized bearing defects and then the sensor placement for better detection of bearing faults is optimized. A nonlinear bearing model is developed based on Jones' bearing theory, while the drawbar, shaft and housing are modeled as Timoshenko's beam. The bearing model is then integrated into the FE model of drawbar/shaft/housing by assembling equations of motion. The Newmark time integration method is used to solve the vibration responses numerically. The FE model of the spindle-bearing system was verified by conducting dynamic tests. Then, the localized bearing defects were modeled and vibration responses generated by the outer ring defect were simulated as an illustration. The optimization scheme of the sensor placement was carried out on the test spindle. The results proved that, the optimal sensor placement depends on the vibration modes under different boundary conditions and the transfer path between the excitation and the response. PMID:23012514

Physics-based Entry, Descent and Landing Risk Model

NASA Technical Reports Server (NTRS)

Gee, Ken; Huynh, Loc C.; Manning, Ted

2014-01-01

A physics-based risk model was developed to assess the risk associated with thermal protection system failures during the entry, descent and landing phase of a manned spacecraft mission. In the model, entry trajectories were computed using a three-degree-of-freedom trajectory tool, the aerothermodynamic heating environment was computed using an engineering-level computational tool and the thermal response of the TPS material was modeled using a one-dimensional thermal response tool. The model was capable of modeling the effect of micrometeoroid and orbital debris impact damage on the TPS thermal response. A Monte Carlo analysis was used to determine the effects of uncertainties in the vehicle state at Entry Interface, aerothermodynamic heating and material properties on the performance of the TPS design. The failure criterion was set as a temperature limit at the bondline between the TPS and the underlying structure. Both direct computation and response surface approaches were used to compute the risk. The model was applied to a generic manned space capsule design. The effect of material property uncertainty and MMOD damage on risk of failure were analyzed. A comparison of the direct computation and response surface approach was undertaken.

Nonlinear response of unidirectional boron/aluminum

NASA Technical Reports Server (NTRS)

Pindera, M.-J.; Herakovich, C. T.; Becker, W.; Aboudi, J.

1990-01-01

Experimental results obtained for unidirectional boron/aluminum subjected to combined loading using off-axis tension, compression and Iosipescu shear specimens are correlated with a nonlinear micromechanics model. It is illustrated that the nonlinear response in the principal material directions is markedly influenced by the different loading modes and different ratios of the applied stress components. The observed nonlinear response under pure and combined loading is discussed in terms of initial yielding, subsequent hardening, stress-interaction effects and unloading-reloading characteristics. The micromechanics model is based on the concept of a repeating unit cell representative of the composite-at-large and employs the unified theory of Bodner and Partom to model the inelastic response of the matrix. It is shown that the employed micromechanics model is sufficiently general to predict the observed nonlinear response of unidirectional boron/aluminum with good accuracy.

Kuk's Model Adjusted for Protection and Efficiency

ERIC Educational Resources Information Center

Su, Shu-Ching; Sedory, Stephen A.; Singh, Sarjinder

2015-01-01

In this article, we adjust the Kuk randomized response model for collecting information on a sensitive characteristic for increased protection and efficiency by making use of forced "yes" and forced "no" responses. We first describe Kuk's model and then the proposed adjustment to Kuk's model. Next, by means of a simulation…

Item Response Modeling of Paired Comparison and Ranking Data

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto; Brown, Anna

2010-01-01

The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…

The Generalized Multilevel Facets Model for Longitudinal Data

ERIC Educational Resources Information Center

Hung, Lai-Fa; Wang, Wen-Chung

2012-01-01

In the human sciences, ability tests or psychological inventories are often repeatedly conducted to measure growth. Standard item response models do not take into account possible autocorrelation in longitudinal data. In this study, the authors propose an item response model to account for autocorrelation. The proposed three-level model consists…

A Bayesian Semiparametric Latent Variable Model for Mixed Responses

ERIC Educational Resources Information Center

Fahrmeir, Ludwig; Raach, Alexander

2007-01-01

In this paper we introduce a latent variable model (LVM) for mixed ordinal and continuous responses, where covariate effects on the continuous latent variables are modelled through a flexible semiparametric Gaussian regression model. We extend existing LVMs with the usual linear covariate effects by including nonparametric components for nonlinear…

Optimal monetary policy and oil price shocks

NASA Astrophysics Data System (ADS)

Kormilitsina, Anna

This dissertation is comprised of two chapters. In the first chapter, I investigate the role of systematic U.S. monetary policy in the presence of oil price shocks. The second chapter is devoted to studying different approaches to modeling energy demand. In an influential paper, Bernanke, Gertler, and Watson (1997) and (2004) argue that systematic monetary policy exacerbated the recessions the U.S. economy experienced in the aftermath of post World War II oil price shocks. In the first chapter of this dissertation, I critically evaluate this claim in the context of an estimated medium-scale model of the U.S. business cycle. Specifically, I solve for the Ramsey optimal monetary policy in the medium-scale dynamic stochastic general equilibrium model (henceforth DSGE) of Schmitt-Grohe and Uribe (2005). To model the demand for oil, I use the approach of Finn (2000). According to this approach, the utilization of capital services requires oil usage. In the related literature on the macroeconomic effects of oil price shocks, it is common to calibrate structural parameters of the model. In contrast to this literature, I estimate the parameters of my DSGE model. The estimation strategy involves matching the impulse responses from the theoretical model to responses predicted by an empirical model. For estimation, I use the alternative to the classical Laplace type estimator proposed by Chernozhukov and Hong (2003). To obtain the empirical impulse responses, I identify an oil price shock in a structural VAR (SVAR) model of the U.S. business cycle. The SVAR model predicts that, in response to an oil price increase, GDP, investment, hours, capital utilization, and the real wage fall, while the nominal interest rate and inflation rise. These findings are economically intuitive and in line with the existing empirical evidence. Comparing the actual and the Ramsey optimal monetary policy response to an oil price shock, I find that the optimal policy allows for more inflation, a larger drop in wages, and a rise in hours compared to those actually observed. The central finding of this Chapter is that the optimal policy is associated with a smaller drop in GDP and other macroeconomic variables. The latter results therefore confirm the claim of Bernanke, Gertler and Watson that monetary policy was to a large extent responsible for the recessions that followed the oil price shocks. However, under the optimal policy, interest rates are tightened even more than what is predicted by the empirical model. This result contrasts sharply with the claim of Bernanke, Gertler, and Watson that the Federal Reserve exacerbated recessions by the excessive tightening of interest rates in response to the oil price increases. In contrast to related studies that focus on output stabilization, I find that eliminating the negative response of GDP to an oil price shock is not desirable. In the second chapter of this dissertation, I compare two approaches to modeling energy sector. Because the share of energy in GDP is small, models of energy have been criticized for their inability to explain sizeable effects of energy price increases on the economic activity. I find that if the price of energy is an exogenous AR(1) process, then the two modeling approaches produce the responses of GDP similar in size to responses observed in most empirical studies, but fail to produce the timing and the shape of the response. DSGE framework can solve the timing and the shape of impulse responses problem, however, fails to replicate the size of the impulse responses. Thus, in DSGE frameworks, amplifying mechanisms for the effect of the energy price shock and estimation based calibration of model parameters are needed to produce the size of the GDP response to the energy price shock.

Orexinergic Neurotransmission in Temperature Responses to Methamphetamine and Stress: Mathematical Modeling as a Data Assimilation Approach

PubMed Central

Behrouzvaziri, Abolhassan; Fu, Daniel; Tan, Patrick; Yoo, Yeonjoo; Zaretskaia, Maria V.; Rusyniak, Daniel E.; Molkov, Yaroslav I.; Zaretsky, Dmitry V.

2015-01-01

Experimental Data Orexinergic neurotransmission is involved in mediating temperature responses to methamphetamine (Meth). In experiments in rats, SB-334867 (SB), an antagonist of orexin receptors (OX1R), at a dose of 10 mg/kg decreases late temperature responses (t>60 min) to an intermediate dose of Meth (5 mg/kg). A higher dose of SB (30 mg/kg) attenuates temperature responses to low dose (1 mg/kg) of Meth and to stress. In contrast, it significantly exaggerates early responses (t<60 min) to intermediate and high doses (5 and 10 mg/kg) of Meth. As pretreatment with SB also inhibits temperature response to the stress of injection, traditional statistical analysis of temperature responses is difficult. Mathematical Modeling We have developed a mathematical model that explains the complexity of temperature responses to Meth as the interplay between excitatory and inhibitory nodes. We have extended the developed model to include the stress of manipulations and the effects of SB. Stress is synergistic with Meth on the action on excitatory node. Orexin receptors mediate an activation of on both excitatory and inhibitory nodes by low doses of Meth, but not on the node activated by high doses (HD). Exaggeration of early responses to high doses of Meth involves disinhibition: low dose of SB decreases tonic inhibition of HD and lowers the activation threshold, while the higher dose suppresses the inhibitory component. Using a modeling approach to data assimilation appears efficient in separating individual components of complex response with statistical analysis unachievable by traditional data processing methods. PMID:25993564

Multi-scale modeling of the CD8 immune response

NASA Astrophysics Data System (ADS)

Barbarroux, Loic; Michel, Philippe; Adimy, Mostafa; Crauste, Fabien

2016-06-01

During the primary CD8 T-Cell immune response to an intracellular pathogen, CD8 T-Cells undergo exponential proliferation and continuous differentiation, acquiring cytotoxic capabilities to address the infection and memorize the corresponding antigen. After cleaning the organism, the only CD8 T-Cells left are antigen-specific memory cells whose role is to respond stronger and faster in case they are presented this very same antigen again. That is how vaccines work: a small quantity of a weakened pathogen is introduced in the organism to trigger the primary response, generating corresponding memory cells in the process, giving the organism a way to defend himself in case it encounters the same pathogen again. To investigate this process, we propose a non linear, multi-scale mathematical model of the CD8 T-Cells immune response due to vaccination using a maturity structured partial differential equation. At the intracellular scale, the level of expression of key proteins is modeled by a delay differential equation system, which gives the speeds of maturation for each cell. The population of cells is modeled by a maturity structured equation whose speeds are given by the intracellular model. We focus here on building the model, as well as its asymptotic study. Finally, we display numerical simulations showing the model can reproduce the biological dynamics of the cell population for both the primary response and the secondary responses.

Mechanisms governing the visco-elastic responses of living cells assessed by foam and tensegrity models.

PubMed

Cañadas, P; Laurent, V M; Chabrand, P; Isabey, D; Wendling-Mansuy, S

2003-11-01

The visco-elastic properties of living cells, measured to date by various authors, vary considerably, depending on the experimental methods and/or on the theoretical models used. In the present study, two mechanisms thought to be involved in cellular visco-elastic responses were analysed, based on the idea that the cytoskeleton plays a fundamental role in cellular mechanical responses. For this purpose, the predictions of an open unit-cell model and a 30-element visco-elastic tensegrity model were tested, taking into consideration similar properties of the constitutive F-actin. The quantitative predictions of the time constant and viscosity modulus obtained by both models were compared with previously published experimental data obtained from living cells. The small viscosity modulus values (10(0)-10(3) Pa x s) predicted by the tensegrity model may reflect the combined contributions of the spatially rearranged constitutive filaments and the internal tension to the overall cytoskeleton response to external loading. In contrast, the high viscosity modulus values (10(3)-10(5) Pa x s) predicted by the unit-cell model may rather reflect the mechanical response of the cytoskeleton to the bending of the constitutive filaments and/or to the deformation of internal components. The present results suggest the existence of a close link between the overall visco-elastic response of micromanipulated cells and the underlying architecture.

Multi-scale modeling of the CD8 immune response

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

Barbarroux, Loic, E-mail: loic.barbarroux@doctorant.ec-lyon.fr; Ecole Centrale de Lyon, 36 avenue Guy de Collongue, 69134 Ecully; Michel, Philippe, E-mail: philippe.michel@ec-lyon.fr

During the primary CD8 T-Cell immune response to an intracellular pathogen, CD8 T-Cells undergo exponential proliferation and continuous differentiation, acquiring cytotoxic capabilities to address the infection and memorize the corresponding antigen. After cleaning the organism, the only CD8 T-Cells left are antigen-specific memory cells whose role is to respond stronger and faster in case they are presented this very same antigen again. That is how vaccines work: a small quantity of a weakened pathogen is introduced in the organism to trigger the primary response, generating corresponding memory cells in the process, giving the organism a way to defend himself inmore » case it encounters the same pathogen again. To investigate this process, we propose a non linear, multi-scale mathematical model of the CD8 T-Cells immune response due to vaccination using a maturity structured partial differential equation. At the intracellular scale, the level of expression of key proteins is modeled by a delay differential equation system, which gives the speeds of maturation for each cell. The population of cells is modeled by a maturity structured equation whose speeds are given by the intracellular model. We focus here on building the model, as well as its asymptotic study. Finally, we display numerical simulations showing the model can reproduce the biological dynamics of the cell population for both the primary response and the secondary responses.« less

Pharmacokinetic Modelling to Predict FVIII:C Response to Desmopressin and Its Reproducibility in Nonsevere Haemophilia A Patients.

PubMed

Schütte, Lisette M; van Hest, Reinier M; Stoof, Sara C M; Leebeek, Frank W G; Cnossen, Marjon H; Kruip, Marieke J H A; Mathôt, Ron A A

2018-04-01

 Nonsevere haemophilia A (HA) patients can be treated with desmopressin. Response of factor VIII activity (FVIII:C) differs between patients and is difficult to predict.  Our aims were to describe FVIII:C response after desmopressin and its reproducibility by population pharmacokinetic (PK) modelling.  Retrospective data of 128 nonsevere HA patients (age 7-75 years) receiving an intravenous or intranasal dose of desmopressin were used. PK modelling of FVIII:C was performed by nonlinear mixed effect modelling. Reproducibility of FVIII:C response was defined as less than 25% difference in peak FVIII:C between administrations.  A total of 623 FVIII:C measurements from 142 desmopressin administrations were available; 14 patients had received two administrations at different occasions. The FVIII:C time profile was best described by a two-compartment model with first-order absorption and elimination. Interindividual variability of the estimated baseline FVIII:C, central volume of distribution and clearance were 37, 43 and 50%, respectively. The most recently measured FVIII:C (FVIII-recent) was significantly associated with FVIII:C response to desmopressin ( p  < 0.001). Desmopressin administration resulted in an absolute FVIII:C increase of 0.47 IU/mL (median, interquartile range: 0.32-0.65 IU/mL, n  = 142). C response was reproducible in 6 out of 14 patients receiving two desmopressin administrations.  FVIII:C response to desmopressin in nonsevere HA patients was adequately described by a population PK model. Large variability in FVIII:C response was observed, which could only partially be explained by FVIII-recent. C response was not reproducible in a small subset of patients. Therefore, monitoring FVIII:C around surgeries or bleeding might be considered. Research is needed to study this further. Schattauer Stuttgart.

Joint Planning Of Energy Storage and Transmission Considering Wind-Storage Combined System and Demand Side Response

NASA Astrophysics Data System (ADS)

Huang, Y.; Liu, B. Z.; Wang, K. Y.; Ai, X.

2017-12-01

In response to the new requirements of the operation mode of wind-storage combined system and demand side response for transmission network planning, this paper presents a joint planning of energy storage and transmission considering wind-storage combined system and demand side response. Firstly, the charge-discharge strategy of energy storage system equipped at the outlet of wind farm and demand side response strategy are analysed to achieve the best comprehensive benefits through the coordination of the two. Secondly, in the general transmission network planning model with wind power, both energy storage cost and demand side response cost are added to the objective function. Not only energy storage operation constraints and but also demand side response constraints are introduced into the constraint condition. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of the charge-discharge strategy of energy storage system equipped at the outlet of the wind farm and demand side response strategy, which belongs to a typical mixed integer linear programming model that can be solved by mature optimization software. The case study based on the Garver-6 bus system shows that the validity of the proposed model is verified by comparison with general transmission network planning model. Furthermore, the results demonstrate that the joint planning model can gain more economic benefits through setting up different cases.

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

An Application of Unfolding and Cumulative Item Response Theory Models for Noncognitive Scaling: Examining the Assumptions and Applicability of the Generalized Graded Unfolding Model

ERIC Educational Resources Information Center

Sgammato, Adrienne N.

2009-01-01

This study examined the applicability of a relatively new unidimensional, unfolding item response theory (IRT) model called the generalized graded unfolding model (GGUM; Roberts, Donoghue, & Laughlin, 2000). A total of four scaling methods were applied. Two commonly used cumulative IRT models for polytomous data, the Partial Credit Model and…

The treatment of climate science in Integrated Assessment Modelling: integration of climate step function response in an energy system integrated assessment model.

NASA Astrophysics Data System (ADS)

Dessens, Olivier

2016-04-01

Integrated Assessment Models (IAMs) are used as crucial inputs to policy-making on climate change. These models simulate aspect of the economy and climate system to deliver future projections and to explore the impact of mitigation and adaptation policies. The IAMs' climate representation is extremely important as it can have great influence on future political action. The step-function-response is a simple climate model recently developed by the UK Met Office and is an alternate method of estimating the climate response to an emission trajectory directly from global climate model step simulations. Good et al., (2013) have formulated a method of reconstructing general circulation models (GCMs) climate response to emission trajectories through an idealized experiment. This method is called the "step-response approach" after and is based on an idealized abrupt CO2 step experiment results. TIAM-UCL is a technology-rich model that belongs to the family of, partial-equilibrium, bottom-up models, developed at University College London to represent a wide spectrum of energy systems in 16 regions of the globe (Anandarajah et al. 2011). The model uses optimisation functions to obtain cost-efficient solutions, in meeting an exogenously defined set of energy-service demands, given certain technological and environmental constraints. Furthermore, it employs linear programming techniques making the step function representation of the climate change response adapted to the model mathematical formulation. For the first time, we have introduced the "step-response approach" method developed at the UK Met Office in an IAM, the TIAM-UCL energy system, and we investigate the main consequences of this modification on the results of the model in term of climate and energy system responses. The main advantage of this approach (apart from the low computational cost it entails) is that its results are directly traceable to the GCM involved and closely connected to well-known methods of analysing GCMs with the step-experiments. Acknowledgments: This work is supported by the FP7 HELIX project (www.helixclimate.eu) References: Anandarajah, G., Pye, S., Usher, W., Kesicki, F., & Mcglade, C. (2011). TIAM-UCL Global model documentation. https://www.ucl.ac.uk/energy-models/models/tiam-ucl/tiam-ucl-manual Good, P., Gregory, J. M., Lowe, J. A., & Andrews, T. (2013). Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections. Climate Dynamics, 40(3-4), 1041-1053.

A Nonlinear Model for Transient Responses from Light-Adapted Wolf Spider Eyes

PubMed Central

DeVoe, Robert D.

1967-01-01

A quantitative model is proposed to test the hypothesis that the dynamics of nonlinearities in retinal action potentials from light-adapted wolf spider eyes may be due to delayed asymmetries in responses of the visual cells. For purposes of calculation, these delayed asymmetries are generated in an analogue by a time-variant resistance. It is first shown that for small incremental stimuli, the linear behavior of such a resistance describes peaking and low frequency phase lead in frequency responses of the eye to sinusoidal modulations of background illumination. It also describes the overshoots in linear step responses. It is next shown that the analogue accounts for nonlinear transient and short term DC responses to large positive and negative step stimuli and for the variations in these responses with changes in degree of light adaptation. Finally, a physiological model is proposed in which the delayed asymmetries in response are attributed to delayed rectification by the visual cell membrane. In this model, cascaded chemical reactions may serve to transduce visual stimuli into membrane resistance changes. PMID:6056011

Mechanical response and buckling of a polymer simulation model of the cell nucleus

NASA Astrophysics Data System (ADS)

Banigan, Edward; Stephens, Andrew; Marko, John

The cell nucleus must robustly resist extra- and intracellular forces to maintain genome architecture. Micromanipulation experiments measuring nuclear mechanical response reveal that the nucleus has two force response regimes: a linear short-extension response due to the chromatin interior and a stiffer long-extension response from lamin A, comprising the intermediate filament protein shell. To explain these results, we developed a quantitative simulation model with realistic parameters for chromatin and the lamina. Our model predicts that crosslinking between chromatin and the lamina is essential for responding to small strains and that changes to the interior topological organization can alter the mechanical response of the whole nucleus. Thus, chromatin polymer elasticity, not osmotic pressure, is the dominant regulator of this force response. Our model reveals a novel buckling transition for polymer shells: as force increases, the shell buckles transverse to the applied force. This transition, which arises from topological constrains in the lamina, can be mitigated by tuning the properties of the chromatin interior. Thus, we find that the genome is a resistive mechanical element that can be tuned by its organization and connectivity to the lamina.

Consumer experience of formal crisis-response services and preferred methods of crisis intervention.

PubMed

Boscarato, Kara; Lee, Stuart; Kroschel, Jon; Hollander, Yitzchak; Brennan, Alice; Warren, Narelle

2014-08-01

The manner in which people with mental illness are supported in a crisis is crucial to their recovery. The current study explored mental health consumers' experiences with formal crisis services (i.e. police and crisis assessment and treatment (CAT) teams), preferred crisis supports, and opinions of four collaborative interagency response models. Eleven consumers completed one-on-one, semistructured interviews. The results revealed that the perceived quality of previous formal crisis interventions varied greatly. Most participants preferred family members or friends to intervene. However, where a formal response was required, general practitioners and mental health case managers were preferred; no participant wanted a police response, and only one indicated a preference for CAT team assistance. Most participants welcomed collaborative crisis interventions. Of four collaborative interagency response models currently being trialled internationally, participants most strongly supported the Ride-Along Model, which enables a police officer and a mental health clinician to jointly respond to distressed consumers in the community. The findings highlight the potential for an interagency response model to deliver a crisis response aligned with consumers' preferences. © 2014 Australian College of Mental Health Nurses Inc.

Generalized IRT Models for Extreme Response Style

ERIC Educational Resources Information Center

Jin, Kuan-Yu; Wang, Wen-Chung

2014-01-01

Extreme response style (ERS) is a systematic tendency for a person to endorse extreme options (e.g., strongly disagree, strongly agree) on Likert-type or rating-scale items. In this study, we develop a new class of item response theory (IRT) models to account for ERS so that the target latent trait is free from the response style and the tendency…

A Simulation Study on Methods of Correcting for the Effects of Extreme Response Style

ERIC Educational Resources Information Center

Wetzel, Eunike; Böhnke, Jan R.; Rose, Norman

2016-01-01

The impact of response styles such as extreme response style (ERS) on trait estimation has long been a matter of concern to researchers and practitioners. This simulation study investigated three methods that have been proposed for the correction of trait estimates for ERS effects: (a) mixed Rasch models, (b) multidimensional item response models,…

Social Responsibility as a Management Control System

DTIC Science & Technology

2004-06-01

the model from corporate America onto the Naval Postgraduate School to examine where socially responsible management control systems operate to control...examples. Finally, we overlay the model from corporate America onto the Naval Postgraduate School to examine where socially responsible management...34 CSRwire: The Corporate Social Responsibility Newswire Service. htt://www.csrwire.com/page.cgi/intro.html.. 16 March 2004. Core Values, http

Scaling effects in the impact response of graphite-epoxy composite beams

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fasanella, Edwin L.

1989-01-01

In support of crashworthiness studies on composite airframes and substructure, an experimental and analytical study was conducted to characterize size effects in the large deflection response of scale model graphite-epoxy beams subjected to impact. Scale model beams of 1/2, 2/3, 3/4, 5/6, and full scale were constructed of four different laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic. The beam specimens were subjected to eccentric axial impact loads which were scaled to provide homologous beam responses. Comparisons of the load and strain time histories between the scale model beams and the prototype should verify the scale law and demonstrate the use of scale model testing for determining impact behavior of composite structures. The nonlinear structural analysis finite element program DYCAST (DYnamic Crash Analysis of STructures) was used to model the beam response. DYCAST analysis predictions of beam strain response are compared to experimental data and the results are presented.

Generalized analytic solutions and response characteristics of magnetotelluric fields on anisotropic infinite faults

NASA Astrophysics Data System (ADS)

Bing, Xue; Yicai, Ji

2018-06-01

In order to understand directly and analyze accurately the detected magnetotelluric (MT) data on anisotropic infinite faults, two-dimensional partial differential equations of MT fields are used to establish a model of anisotropic infinite faults using the Fourier transform method. A multi-fault model is developed to expand the one-fault model. The transverse electric mode and transverse magnetic mode analytic solutions are derived using two-infinite-fault models. The infinite integral terms of the quasi-analytic solutions are discussed. The dual-fault model is computed using the finite element method to verify the correctness of the solutions. The MT responses of isotropic and anisotropic media are calculated to analyze the response functions by different anisotropic conductivity structures. The thickness and conductivity of the media, influencing MT responses, are discussed. The analytic principles are also given. The analysis results are significant to how MT responses are perceived and to the data interpretation of the complex anisotropic infinite faults.

Bayes Factor Covariance Testing in Item Response Models.

PubMed

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Role of Coronary Myogenic Response in Pressure-Flow Autoregulation in Swine: A Meta-Analysis With Coronary Flow Modeling

PubMed Central

Dick, Gregory M.; Namani, Ravi; Patel, Bhavesh; Kassab, Ghassan S.

2018-01-01

Myogenic responses (pressure-dependent contractions) of coronary arterioles play a role in autoregulation (relatively constant flow vs. pressure). Publications on myogenic reactivity in swine coronaries vary in caliber, analysis, and degree of responsiveness. Further, data on myogenic responses and autoregulation in swine have not been completely compiled, compared, and modeled. Thus, it has been difficult to understand these physiological phenomena. Our purpose was to: (a) analyze myogenic data with standard criteria; (b) assign results to diameter categories defined by morphometry; and (c) use our novel multiscale flow model to determine the extent to which ex vivo myogenic reactivity can explain autoregulation in vivo. When myogenic responses from the literature are an input for our model, the predicted coronary autoregulation approaches in vivo observations. More complete and appropriate data are now available to investigate the regulation of coronary blood flow in swine, a highly relevant model for human physiology and disease. PMID:29875686

Mean-variance analysis of block-iterative reconstruction algorithms modeling 3D detector response in SPECT

NASA Astrophysics Data System (ADS)

Lalush, D. S.; Tsui, B. M. W.

1998-06-01

We study the statistical convergence properties of two fast iterative reconstruction algorithms, the rescaled block-iterative (RBI) and ordered subset (OS) EM algorithms, in the context of cardiac SPECT with 3D detector response modeling. The Monte Carlo method was used to generate nearly noise-free projection data modeling the effects of attenuation, detector response, and scatter from the MCAT phantom. One thousand noise realizations were generated with an average count level approximating a typical T1-201 cardiac study. Each noise realization was reconstructed using the RBI and OS algorithms for cases with and without detector response modeling. For each iteration up to twenty, we generated mean and variance images, as well as covariance images for six specific locations. Both OS and RBI converged in the mean to results that were close to the noise-free ML-EM result using the same projection model. When detector response was not modeled in the reconstruction, RBI exhibited considerably lower noise variance than OS for the same resolution. When 3D detector response was modeled, the RBI-EM provided a small improvement in the tradeoff between noise level and resolution recovery, primarily in the axial direction, while OS required about half the number of iterations of RBI to reach the same resolution. We conclude that OS is faster than RBI, but may be sensitive to errors in the projection model. Both OS-EM and RBI-EM are effective alternatives to the EVIL-EM algorithm, but noise level and speed of convergence depend on the projection model used.

Single-cell-based computer simulation of the oxygen-dependent tumour response to irradiation

NASA Astrophysics Data System (ADS)

Harting, Christine; Peschke, Peter; Borkenstein, Klaus; Karger, Christian P.

2007-08-01

Optimization of treatment plans in radiotherapy requires the knowledge of tumour control probability (TCP) and normal tissue complication probability (NTCP). Mathematical models may help to obtain quantitative estimates of TCP and NTCP. A single-cell-based computer simulation model is presented, which simulates tumour growth and radiation response on the basis of the response of the constituting cells. The model contains oxic, hypoxic and necrotic tumour cells as well as capillary cells which are considered as sources of a radial oxygen profile. Survival of tumour cells is calculated by the linear quadratic model including the modified response due to the local oxygen concentration. The model additionally includes cell proliferation, hypoxia-induced angiogenesis, apoptosis and resorption of inactivated tumour cells. By selecting different degrees of angiogenesis, the model allows the simulation of oxic as well as hypoxic tumours having distinctly different oxygen distributions. The simulation model showed that poorly oxygenated tumours exhibit an increased radiation tolerance. Inter-tumoural variation of radiosensitivity flattens the dose response curve. This effect is enhanced by proliferation between fractions. Intra-tumoural radiosensitivity variation does not play a significant role. The model may contribute to the mechanistic understanding of the influence of biological tumour parameters on TCP. It can in principle be validated in radiation experiments with experimental tumours.

Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation.

PubMed

Fitzpatrick, Matthew C; Keller, Stephen R

2015-01-01

Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism-environment relationships that combines genomic data and community-level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA-5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community-level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species-level assessments of climate change vulnerability. © 2014 John Wiley & Sons Ltd/CNRS.

Neurobiological model of stimulated dopamine neurotransmission to interpret fast-scan cyclic voltammetry data.

PubMed

Harun, Rashed; Grassi, Christine M; Munoz, Miranda J; Torres, Gonzalo E; Wagner, Amy K

2015-03-02

Fast-scan cyclic voltammetry (FSCV) is an electrochemical method that can assess real-time in vivo dopamine (DA) concentration changes to study the kinetics of DA neurotransmission. Electrical stimulation of dopaminergic (DAergic) pathways can elicit FSCV DA responses that largely reflect a balance of DA release and reuptake. Interpretation of these evoked DA responses requires a framework to discern the contribution of DA release and reuptake. The current, widely implemented interpretive framework for doing so is the Michaelis-Menten (M-M) model, which is grounded on two assumptions- (1) DA release rate is constant during stimulation, and (2) DA reuptake occurs through dopamine transporters (DAT) in a manner consistent with M-M enzyme kinetics. Though the M-M model can simulate evoked DA responses that rise convexly, response types that predominate in the ventral striatum, the M-M model cannot simulate dorsal striatal responses that rise concavely. Based on current neurotransmission principles and experimental FSCV data, we developed a novel, quantitative, neurobiological framework to interpret DA responses that assumes DA release decreases exponentially during stimulation and continues post-stimulation at a diminishing rate. Our model also incorporates dynamic M-M kinetics to describe DA reuptake as a process of decreasing reuptake efficiency. We demonstrate that this quantitative, neurobiological model is an extension of the traditional M-M model that can simulate heterogeneous regional DA responses following manipulation of stimulation duration, frequency, and DA pharmacology. The proposed model can advance our interpretive framework for future in vivo FSCV studies examining regional DA kinetics and their alteration by disease and DA pharmacology. Copyright © 2015 Elsevier B.V. All rights reserved.

Development and validation of age-dependent FE human models of a mid-sized male thorax.

PubMed

El-Jawahri, Raed E; Laituri, Tony R; Ruan, Jesse S; Rouhana, Stephen W; Barbat, Saeed D

2010-11-01

The increasing number of people over 65 years old (YO) is an important research topic in the area of impact biomechanics, and finite element (FE) modeling can provide valuable support for related research. There were three objectives of this study: (1) Estimation of the representative age of the previously-documented Ford Human Body Model (FHBM) -- an FE model which approximates the geometry and mass of a mid-sized male, (2) Development of FE models representing two additional ages, and (3) Validation of the resulting three models to the extent possible with respect to available physical tests. Specifically, the geometry of the model was compared to published data relating rib angles to age, and the mechanical properties of different simulated tissues were compared to a number of published aging functions. The FHBM was determined to represent a 53-59 YO mid-sized male. The aforementioned aging functions were used to develop FE models representing two additional ages: 35 and 75 YO. The rib model was validated against human rib specimens and whole rib tests, under different loading conditions, with and without modeled fracture. In addition, the resulting three age-dependent models were validated by simulating cadaveric tests of blunt and sled impacts. The responses of the models, in general, were within the cadaveric response corridors. When compared to peak responses from individual cadavers similar in size and age to the age-dependent models, some responses were within one standard deviation of the test data. All the other responses, but one, were within two standard deviations.

An update on modeling dose-response relationships: Accounting for correlated data structure and heterogeneous error variance in linear and nonlinear mixed models.

PubMed

Gonçalves, M A D; Bello, N M; Dritz, S S; Tokach, M D; DeRouchey, J M; Woodworth, J C; Goodband, R D

2016-05-01

Advanced methods for dose-response assessments are used to estimate the minimum concentrations of a nutrient that maximizes a given outcome of interest, thereby determining nutritional requirements for optimal performance. Contrary to standard modeling assumptions, experimental data often present a design structure that includes correlations between observations (i.e., blocking, nesting, etc.) as well as heterogeneity of error variances; either can mislead inference if disregarded. Our objective is to demonstrate practical implementation of linear and nonlinear mixed models for dose-response relationships accounting for correlated data structure and heterogeneous error variances. To illustrate, we modeled data from a randomized complete block design study to evaluate the standardized ileal digestible (SID) Trp:Lys ratio dose-response on G:F of nursery pigs. A base linear mixed model was fitted to explore the functional form of G:F relative to Trp:Lys ratios and assess model assumptions. Next, we fitted 3 competing dose-response mixed models to G:F, namely a quadratic polynomial (QP) model, a broken-line linear (BLL) ascending model, and a broken-line quadratic (BLQ) ascending model, all of which included heteroskedastic specifications, as dictated by the base model. The GLIMMIX procedure of SAS (version 9.4) was used to fit the base and QP models and the NLMIXED procedure was used to fit the BLL and BLQ models. We further illustrated the use of a grid search of initial parameter values to facilitate convergence and parameter estimation in nonlinear mixed models. Fit between competing dose-response models was compared using a maximum likelihood-based Bayesian information criterion (BIC). The QP, BLL, and BLQ models fitted on G:F of nursery pigs yielded BIC values of 353.7, 343.4, and 345.2, respectively, thus indicating a better fit of the BLL model. The BLL breakpoint estimate of the SID Trp:Lys ratio was 16.5% (95% confidence interval [16.1, 17.0]). Problems with the estimation process rendered results from the BLQ model questionable. Importantly, accounting for heterogeneous variance enhanced inferential precision as the breadth of the confidence interval for the mean breakpoint decreased by approximately 44%. In summary, the article illustrates the use of linear and nonlinear mixed models for dose-response relationships accounting for heterogeneous residual variances, discusses important diagnostics and their implications for inference, and provides practical recommendations for computational troubleshooting.

Development of a detector model for generation of synthetic radiographs of cargo containers

NASA Astrophysics Data System (ADS)

White, Timothy A.; Bredt, Ofelia P.; Schweppe, John E.; Runkle, Robert C.

2008-05-01

Creation of synthetic cargo-container radiographs that possess attributes of their empirical counterparts requires accurate models of the imaging-system response. Synthetic radiographs serve as surrogate data in studies aimed at determining system effectiveness for detecting target objects when it is impractical to collect a large set of empirical radiographs. In the case where a detailed understanding of the detector system is available, an accurate detector model can be derived from first-principles. In the absence of this detail, it is necessary to derive empirical models of the imaging-system response from radiographs of well-characterized objects. Such a case is the topic of this work, where we demonstrate the development of an empirical model of a gamma-ray radiography system with the intent of creating a detector-response model that translates uncollided photon transport calculations into realistic synthetic radiographs. The detector-response model is calibrated to field measurements of well-characterized objects thus incorporating properties such as system sensitivity, spatial resolution, contrast and noise.

Characterization and Modeling of Thoraco-Abdominal Response to Blast Waves. Volume 4. Biomechanical Model of Thorax Response to Blast Loading

DTIC Science & Technology

1985-05-01

non- zero Dirichlet boundary conditions and/or general mixed type boundary conditions. Note that Neumann type boundary condi- tion enters the problem by...Background ................................. ................... I 1.3 General Description ..... ............ ........... . ....... ...... 2 2. ANATOMICAL...human and varions loading conditions for the definition of a generalized safety guideline of blast exposure. To model the response of a sheep torso

Pragmatic hydraulic theory predicts stomatal responses to climatic water deficits.

PubMed

Sperry, John S; Wang, Yujie; Wolfe, Brett T; Mackay, D Scott; Anderegg, William R L; McDowell, Nate G; Pockman, William T

2016-11-01

Ecosystem models have difficulty predicting plant drought responses, partially from uncertainty in the stomatal response to water deficits in soil and atmosphere. We evaluate a 'supply-demand' theory for water-limited stomatal behavior that avoids the typical scaffold of empirical response functions. The premise is that canopy water demand is regulated in proportion to threat to supply posed by xylem cavitation and soil drying. The theory was implemented in a trait-based soil-plant-atmosphere model. The model predicted canopy transpiration (E), canopy diffusive conductance (G), and canopy xylem pressure (P canopy ) from soil water potential (P soil ) and vapor pressure deficit (D). Modeled responses to D and P soil were consistent with empirical response functions, but controlling parameters were hydraulic traits rather than coefficients. Maximum hydraulic and diffusive conductances and vulnerability to loss in hydraulic conductance dictated stomatal sensitivity and hence the iso- to anisohydric spectrum of regulation. The model matched wide fluctuations in G and P canopy across nine data sets from seasonally dry tropical forest and piñon-juniper woodland with < 26% mean error. Promising initial performance suggests the theory could be useful in improving ecosystem models. Better understanding of the variation in hydraulic properties along the root-stem-leaf continuum will simplify parameterization. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

[Assessment on the ability of emergency response at the county center for disease control and prevention level in flooding-prone areas].

PubMed

Chen, Wei; Zeng, Guang

2006-02-01

To establish a comprehensive assessment model on the ability of emergency response within the public health system in flooding-prone areas. A hierarchy process theory was used to establish the initial assessing framework. Delphi method was used to screen and choose the ultimate indicators and their weights before an assessment model was set up under the 'synthetic scored method' to assess the ability of the emergency response among twenty county public health units. We then used the 'analysis of variation (ANOVA)' methodology to test the feasibility of distinguishing the ability of emergency response among different county health units and correlation analysis was used to assess the independence of indicators in the assessing model. A comprehensive model was then established including twenty first-class indicators and fifty-six second-class indicators and the degree of ability to emergency response with flooding of public health units was evaluated. There were five public health units having higher, ten having moderate but five with lower levels on emergency response. The assessment model was proved to be a good method in differentiating the ability of public health units, using independent indicators. The assessment model which we established seemed to be practical and reliable.

System analysis of the dynamic response of the coronary circulation to a sudden change in heart rate.

PubMed

Dankelman, J; Stassen, H G; Spaan, J A

1990-03-01

In this study the response of driving pressure/flow ration on an abrupt change in heart rate was analysed. The difference between the response obtained with constant pressure and constant flow perfusion was also studied. The responses show a fast initial reversed phase followed by a slow phase caused by regulation. To test whether the initial phase could be the result of mechanical changes in the coronary circulation, a model for regulation was extended by the addition of four different mechanical models originating from the literature. These extended models were able to explain the fast initial phase. However, the mechanical model consisting of an intramyocardial compliance (C = 0.08 ml mm Hg-1 100 g-1) with a variable venous resistance, and the model consisting of a waterfall and a small compliance (C = 0.007 ml mm Hg-1 100g-1) both explained these responses best. The analysis showed that there is no direct relationship between rate of change of vascular tone and rate of change of pressure/flow ratio. However, on the basis of the two extended models, it can be predicted that the half-time for the response of regulation to be complete is about 9s with constant pressure perfusion and 15 s with constant flow perfusion.

Estimating Single-Trial Responses in EEG

NASA Technical Reports Server (NTRS)

Shah, A. S.; Knuth, K. H.; Truccolo, W. A.; Mehta, A. D.; Fu, K. G.; Johnston, T. A.; Ding, M.; Bressler, S. L.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms

A template-based approach for responsibility management in executable business processes

NASA Astrophysics Data System (ADS)

Cabanillas, Cristina; Resinas, Manuel; Ruiz-Cortés, Antonio

2018-05-01

Process-oriented organisations need to manage the different types of responsibilities their employees may have w.r.t. the activities involved in their business processes. Despite several approaches provide support for responsibility modelling, in current Business Process Management Systems (BPMS) the only responsibility considered at runtime is the one related to performing the work required for activity completion. Others like accountability or consultation must be implemented by manually adding activities in the executable process model, which is time-consuming and error-prone. In this paper, we address this limitation by enabling current BPMS to execute processes in which people with different responsibilities interact to complete the activities. We introduce a metamodel based on Responsibility Assignment Matrices (RAM) to model the responsibility assignment for each activity, and a flexible template-based mechanism that automatically transforms such information into BPMN elements, which can be interpreted and executed by a BPMS. Thus, our approach does not enforce any specific behaviour for the different responsibilities but new templates can be modelled to specify the interaction that best suits the activity requirements. Furthermore, libraries of templates can be created and reused in different processes. We provide a reference implementation and build a library of templates for a well-known set of responsibilities.

Response to Oud & Folmer: Randomness and Residuals

ERIC Educational Resources Information Center

Steele, Joel S.; Ferrer, Emilio

2011-01-01

This article presents our response to Oud and Folmer's "Modeling Oscillation, Approximately or Exactly?" (2011), which criticizes aspects of our article, "Latent Differential Equation Modeling of Self-Regulatory and Coregulatory Affective Processes" (2011). In this response, we present a conceptual explanation of the derivative-based estimation…

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

EPA Science Inventory

Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this stu...

Estimating disease prevalence from two-phase surveys with non-response at the second phase

PubMed Central

Gao, Sujuan; Hui, Siu L.; Hall, Kathleen S.; Hendrie, Hugh C.

2010-01-01

SUMMARY In this paper we compare several methods for estimating population disease prevalence from data collected by two-phase sampling when there is non-response at the second phase. The traditional weighting type estimator requires the missing completely at random assumption and may yield biased estimates if the assumption does not hold. We review two approaches and propose one new approach to adjust for non-response assuming that the non-response depends on a set of covariates collected at the first phase: an adjusted weighting type estimator using estimated response probability from a response model; a modelling type estimator using predicted disease probability from a disease model; and a regression type estimator combining the adjusted weighting type estimator and the modelling type estimator. These estimators are illustrated using data from an Alzheimer’s disease study in two populations. Simulation results are presented to investigate the performances of the proposed estimators under various situations. PMID:10931514

Architecture of a minimal signaling pathway explains the T-cell response to a 1 million-fold variation in antigen affinity and dose

PubMed Central

Lever, Melissa; Lim, Hong-Sheng; Kruger, Philipp; Nguyen, John; Trendel, Nicola; Abu-Shah, Enas; Maini, Philip Kumar; van der Merwe, Philip Anton

2016-01-01

T cells must respond differently to antigens of varying affinity presented at different doses. Previous attempts to map peptide MHC (pMHC) affinity onto T-cell responses have produced inconsistent patterns of responses, preventing formulations of canonical models of T-cell signaling. Here, a systematic analysis of T-cell responses to 1 million-fold variations in both pMHC affinity and dose produced bell-shaped dose–response curves and different optimal pMHC affinities at different pMHC doses. Using sequential model rejection/identification algorithms, we identified a unique, minimal model of cellular signaling incorporating kinetic proofreading with limited signaling coupled to an incoherent feed-forward loop (KPL-IFF) that reproduces these observations. We show that the KPL-IFF model correctly predicts the T-cell response to antigen copresentation. Our work offers a general approach for studying cellular signaling that does not require full details of biochemical pathways. PMID:27702900

Architecture of a minimal signaling pathway explains the T-cell response to a 1 million-fold variation in antigen affinity and dose.

PubMed

Lever, Melissa; Lim, Hong-Sheng; Kruger, Philipp; Nguyen, John; Trendel, Nicola; Abu-Shah, Enas; Maini, Philip Kumar; van der Merwe, Philip Anton; Dushek, Omer

2016-10-25

T cells must respond differently to antigens of varying affinity presented at different doses. Previous attempts to map peptide MHC (pMHC) affinity onto T-cell responses have produced inconsistent patterns of responses, preventing formulations of canonical models of T-cell signaling. Here, a systematic analysis of T-cell responses to 1 million-fold variations in both pMHC affinity and dose produced bell-shaped dose-response curves and different optimal pMHC affinities at different pMHC doses. Using sequential model rejection/identification algorithms, we identified a unique, minimal model of cellular signaling incorporating kinetic proofreading with limited signaling coupled to an incoherent feed-forward loop (KPL-IFF) that reproduces these observations. We show that the KPL-IFF model correctly predicts the T-cell response to antigen copresentation. Our work offers a general approach for studying cellular signaling that does not require full details of biochemical pathways.

Predictive models to determine imagery strategies employed by children to judge hand laterality.

PubMed

Spruijt, Steffie; Jongsma, Marijtje L A; van der Kamp, John; Steenbergen, Bert

2015-01-01

A commonly used paradigm to study motor imagery is the hand laterality judgment task. The present study aimed to determine which strategies young children employ to successfully perform this task. Children of 5 to 8 years old (N = 92) judged laterality of back and palm view hand pictures in different rotation angles. Response accuracy and response duration were registered. Response durations of the trials with a correct judgment were fitted to a-priori defined predictive sinusoid models, representing different strategies to successfully perform the hand laterality judgment task. The first model predicted systematic changes in response duration as a function of rotation angle of the displayed hand. The second model predicted that response durations are affected by biomechanical constraints of hand rotation. If observed data could be best described by the first model, this would argue for a mental imagery strategy that does not involve motor processes to solve the task. The second model reflects a motor imagery strategy to solve the task. In line with previous research, we showed an age-related increase in response accuracy and decrease in response duration in children. Observed data for both back and palm view showed that motor imagery strategies were used to perform hand laterality judgments, but that not all the children use these strategies (appropriately) at all times. A direct comparison of response duration patterns across age sheds new light on age-related differences in the strategies employed to solve the task. Importantly, the employment of the motor imagery strategy for successful task performance did not change with age.

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

NASA Technical Reports Server (NTRS)

Bassu, Simona; Brisson, Nadine; Grassini, Patricio; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W.; Rosenzweig, Cynthia; Ruane, Alex C.; Adam, Myriam;

How do various maize crop models vary in their responses to climate change factors?

PubMed

Bassu, Simona; Brisson, Nadine; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W; Rosenzweig, Cynthia; Ruane, Alex C; Adam, Myriam; Baron, Christian; Basso, Bruno; Biernath, Christian; Boogaard, Hendrik; Conijn, Sjaak; Corbeels, Marc; Deryng, Delphine; De Sanctis, Giacomo; Gayler, Sebastian; Grassini, Patricio; Hatfield, Jerry; Hoek, Steven; Izaurralde, Cesar; Jongschaap, Raymond; Kemanian, Armen R; Kersebaum, K Christian; Kim, Soo-Hyung; Kumar, Naresh S; Makowski, David; Müller, Christoph; Nendel, Claas; Priesack, Eckart; Pravia, Maria Virginia; Sau, Federico; Shcherbak, Iurii; Tao, Fulu; Teixeira, Edmar; Timlin, Dennis; Waha, Katharina

2014-07-01

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information. © 2014 John Wiley & Sons Ltd.

Social Information Processing Mediates the Intergenerational Transmission of Aggressiveness in Romantic Relationships

PubMed Central

Fite, Jennifer E.; Bates, John E.; Holtzworth-Munroe, Amy; Dodge, Kenneth A.; Nay, Sandra Y.; Pettit, Gregory S.

2012-01-01

This study explored the K. A. Dodge (1986) model of social information processing as a mediator of the association between interparental relationship conflict and subsequent offspring romantic relationship conflict in young adulthood. The authors tested 4 social information processing stages (encoding, hostile attributions, generation of aggressive responses, and positive evaluation of aggressive responses) in separate models to explore their independent effects as potential mediators. There was no evidence of mediation for encoding and attributions. However, there was evidence of significant mediation for both the response generation and response evaluation stages of the model. Results suggest that the ability of offspring to generate varied social responses and effectively evaluate the potential outcome of their responses at least partially mediates the intergenerational transmission of relationship conflict. PMID:18540765

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.

Contrasting response to nutrient manipulation in Arctic mesocosms are reproduced by a minimum microbial food web model.

PubMed

Larsen, Aud; Egge, Jorun K; Nejstgaard, Jens C; Di Capua, Iole; Thyrhaug, Runar; Bratbak, Gunnar; Thingstad, T Frede

2015-03-01

A minimum mathematical model of the marine pelagic microbial food web has previously shown to be able to reproduce central aspects of observed system response to different bottom-up manipulations in a mesocosm experiment Microbial Ecosystem Dynamics (MEDEA) in Danish waters. In this study, we apply this model to two mesocosm experiments (Polar Aquatic Microbial Ecology (PAME)-I and PAME-II) conducted at the Arctic location Kongsfjorden, Svalbard. The different responses of the microbial community to similar nutrient manipulation in the three mesocosm experiments may be described as diatom-dominated (MEDEA), bacteria-dominated (PAME-I), and flagellated-dominated (PAME-II). When allowing ciliates to be able to feed on small diatoms, the model describing the diatom-dominated MEDEA experiment give a bacteria-dominated response as observed in PAME I in which the diatom community comprised almost exclusively small-sized cells. Introducing a high initial mesozooplankton stock as observed in PAME-II, the model gives a flagellate-dominated response in accordance with the observed response also of this experiment. The ability of the model originally developed for temperate waters to reproduce population dynamics in a 10°C colder Arctic fjord, does not support the existence of important shifts in population balances over this temperature range. Rather, it suggests a quite resilient microbial food web when adapted to in situ temperature. The sensitivity of the model response to its mesozooplankton component suggests, however, that the seasonal vertical migration of Arctic copepods may be a strong forcing factor on Arctic microbial food webs.

A model-based approach to investigating the pathophysiological mechanisms of hypertension and response to antihypertensive therapies: extending the Guyton model.

PubMed

Hallow, K Melissa; Lo, Arthur; Beh, Jeni; Rodrigo, Manoj; Ermakov, Sergey; Friedman, Stuart; de Leon, Hector; Sarkar, Anamika; Xiong, Yuan; Sarangapani, Ramesh; Schmidt, Henning; Webb, Randy; Kondic, Anna Georgieva

2014-05-01

Reproducibly differential responses to different classes of antihypertensive agents are observed among hypertensive patients and may be due to interindividual differences in hypertension pathology. Computational models provide a tool for investigating the impact of underlying disease mechanisms on the response to antihypertensive therapies with different mechanisms of action. We present the development, calibration, validation, and application of an extension of the Guyton/Karaaslan model of blood pressure regulation. The model incorporates a detailed submodel of the renin-angiotensin-aldosterone system (RAAS), allowing therapies that target different parts of this pathway to be distinguished. Literature data on RAAS biomarker and blood pressure responses to different classes of therapies were used to refine the physiological actions of ANG II and aldosterone on renin secretion, renal vascular resistance, and sodium reabsorption. The calibrated model was able to accurately reproduce the RAAS biomarker and blood pressure responses to combinations of dual-RAAS agents, as well as RAAS therapies in combination with diuretics or calcium channel blockers. The final model was used to explore the impact of underlying mechanisms of hypertension on the blood pressure response to different classes of antihypertensive agents. Simulations indicate that the underlying etiology of hypertension can impact the magnitude of response to a given class of therapy, making a patient more sensitive to one class and less sensitive others. Given that hypertension is usually the result of multiple mechanisms, rather than a single factor, these findings yield insight into why combination therapy is often required to adequately control blood pressure.

Contrasting response to nutrient manipulation in Arctic mesocosms are reproduced by a minimum microbial food web model

PubMed Central

Larsen, Aud; Egge, Jorun K; Nejstgaard, Jens C; Di Capua, Iole; Thyrhaug, Runar; Bratbak, Gunnar; Thingstad, T Frede

2015-01-01

A minimum mathematical model of the marine pelagic microbial food web has previously shown to be able to reproduce central aspects of observed system response to different bottom-up manipulations in a mesocosm experiment Microbial Ecosystem Dynamics (MEDEA) in Danish waters. In this study, we apply this model to two mesocosm experiments (Polar Aquatic Microbial Ecology (PAME)-I and PAME-II) conducted at the Arctic location Kongsfjorden, Svalbard. The different responses of the microbial community to similar nutrient manipulation in the three mesocosm experiments may be described as diatom-dominated (MEDEA), bacteria-dominated (PAME-I), and flagellated-dominated (PAME-II). When allowing ciliates to be able to feed on small diatoms, the model describing the diatom-dominated MEDEA experiment give a bacteria-dominated response as observed in PAME I in which the diatom community comprised almost exclusively small-sized cells. Introducing a high initial mesozooplankton stock as observed in PAME-II, the model gives a flagellate-dominated response in accordance with the observed response also of this experiment. The ability of the model originally developed for temperate waters to reproduce population dynamics in a 10°C colder Arctic fjord, does not support the existence of important shifts in population balances over this temperature range. Rather, it suggests a quite resilient microbial food web when adapted to in situ temperature. The sensitivity of the model response to its mesozooplankton component suggests, however, that the seasonal vertical migration of Arctic copepods may be a strong forcing factor on Arctic microbial food webs. PMID:26074626

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.

Understanding and quantifying foliar temperature acclimation for Earth System Models

NASA Astrophysics Data System (ADS)

Smith, N. G.; Dukes, J.

2015-12-01

Photosynthesis and respiration on land are the two largest carbon fluxes between the atmosphere and Earth's surface. The parameterization of these processes represent major uncertainties in the terrestrial component of the Earth System Models used to project future climate change. Research has shown that much of this uncertainty is due to the parameterization of the temperature responses of leaf photosynthesis and autotrophic respiration, which are typically based on short-term empirical responses. Here, we show that including longer-term responses to temperature, such as temperature acclimation, can help to reduce this uncertainty and improve model performance, leading to drastic changes in future land-atmosphere carbon feedbacks across multiple models. However, these acclimation formulations have many flaws, including an underrepresentation of many important global flora. In addition, these parameterizations were done using multiple studies that employed differing methodology. As such, we used a consistent methodology to quantify the short- and long-term temperature responses of maximum Rubisco carboxylation (Vcmax), maximum rate of Ribulos-1,5-bisphosphate regeneration (Jmax), and dark respiration (Rd) in multiple species representing each of the plant functional types used in global-scale land surface models. Short-term temperature responses of each process were measured in individuals acclimated for 7 days at one of 5 temperatures (15-35°C). The comparison of short-term curves in plants acclimated to different temperatures were used to evaluate long-term responses. Our analyses indicated that the instantaneous response of each parameter was highly sensitive to the temperature at which they were acclimated. However, we found that this sensitivity was larger in species whose leaves typically experience a greater range of temperatures over the course of their lifespan. These data indicate that models using previous acclimation formulations are likely incorrectly simulating leaf carbon exchange responses to future warming. Therefore, our data, if used to parameterize large-scale models, are likely to provide an even greater improvement in model performance, resulting in more reliable projections of future carbon-clime feedbacks.

A Point-process Response Model for Spike Trains from Single Neurons in Neural Circuits under Optogenetic Stimulation

PubMed Central

Luo, X.; Gee, S.; Sohal, V.; Small, D.

2015-01-01

Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from these experiments present a statistical challenge of modeling a high frequency point process (neuronal spikes) while the input is another high frequency point process (light flashes). We further develop a generalized linear model approach to model the relationships between two point processes, employing additive point-process response functions. The resulting model, Point-process Responses for Optogenetics (PRO), provides explicit nonlinear transformations to link the input point process with the output one. Such response functions may provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation. We validate and compare the PRO model using a real dataset and simulations, and our model yields a superior area-under-the- curve value as high as 93% for predicting every future spike. For our experiment on the recurrent layer V circuit in the prefrontal cortex, the PRO model provides evidence that neurons integrate their inputs in a sophisticated manner. Another use of the model is that it enables understanding how neural circuits are altered under various disease conditions and/or experimental conditions by comparing the PRO parameters. PMID:26411923

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.

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

Scaling effects in the static and dynamic response of graphite-epoxy beam-columns. Ph.D. Thesis - Virginia Polytechnic Inst. and State Univ.

NASA Technical Reports Server (NTRS)

Jackson, Karen E.

1990-01-01

Scale model technology represents one method of investigating the behavior of advanced, weight-efficient composite structures under a variety of loading conditions. It is necessary, however, to understand the limitations involved in testing scale model structures before the technique can be fully utilized. These limitations, or scaling effects, are characterized. in the large deflection response and failure of composite beams. Scale model beams were loaded with an eccentric axial compressive load designed to produce large bending deflections and global failure. A dimensional analysis was performed on the composite beam-column loading configuration to determine a model law governing the system response. An experimental program was developed to validate the model law under both static and dynamic loading conditions. Laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic were tested to examine a diversity of composite response and failure modes. The model beams were loaded under scaled test conditions until catastrophic failure. A large deflection beam solution was developed to compare with the static experimental results and to analyze beam failure. Also, the finite element code DYCAST (DYnamic Crash Analysis of STructure) was used to model both the static and impulsive beam response. Static test results indicate that the unidirectional and cross ply beam responses scale as predicted by the model law, even under severe deformations. In general, failure modes were consistent between scale models within a laminate family; however, a significant scale effect was observed in strength. The scale effect in strength which was evident in the static tests was also observed in the dynamic tests. Scaling of load and strain time histories between the scale model beams and the prototypes was excellent for the unidirectional beams, but inconsistent results were obtained for the angle ply, cross ply, and quasi-isotropic beams. Results show that valuable information can be obtained from testing on scale model composite structures, especially in the linear elastic response region. However, due to scaling effects in the strength behavior of composite laminates, caution must be used in extrapolating data taken from a scale model test when that test involves failure of the structure.

Application of the IRT and TRT Models to a Reading Comprehension Test

ERIC Educational Resources Information Center

Kim, Weon H.

2017-01-01

The purpose of the present study is to apply the item response theory (IRT) and testlet response theory (TRT) models to a reading comprehension test. This study applied the TRT models and the traditional IRT model to a seventh-grade reading comprehension test (n = 8,815) with eight testlets. These three models were compared to determine the best…

Modeling responses of large-river fish populations to global climate change through downscaling and incorporation of predictive uncertainty

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima; Mader, Helmut; Kraml, Julia

2012-01-01

Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.

Global stability for an HIV-1 infection model with Beddington-DeAngelis incidence rate and CTL immune response

NASA Astrophysics Data System (ADS)

Lv, Cuifang; Huang, Lihong; Yuan, Zhaohui

2014-01-01

In this paper, an HIV-1 infection model with Beddington-DeAngelis incidence rate and CTL immune response is investigated. One main feature of this model is that an eclipse stage for the infected cells is included and a portion of these cells is reverted to uninfected cells. We derive the basic reproduction number R1 and the immune response reproduction number R2 for the HIV-1 infection model. By constructing Lyapunov functions, the global stabilities for the equilibria have been analyzed.