Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models

DOE PAGES

Kravitz, Ben; MacMartin, Douglas G.; Rasch, Philip J.; ...

2017-02-17

We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady-state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to thosemore » of step-change simulations, but in this new method the responses for 22 regions can be characterized simultaneously. Moreover, we can estimate the timescale over which the steady-state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.« less

When things don't add up: quantifying impacts of multiple stressors from individual metabolism to ecosystem processing.

PubMed

Galic, Nika; Sullivan, Lauren L; Grimm, Volker; Forbes, Valery E

2018-04-01

Ecosystems are exposed to multiple stressors which can compromise functioning and service delivery. These stressors often co-occur and interact in different ways which are not yet fully understood. Here, we applied a population model representing a freshwater amphipod feeding on leaf litter in forested streams. We simulated impacts of hypothetical stressors, individually and in pairwise combinations that target the individuals' feeding, maintenance, growth and reproduction. Impacts were quantified by examining responses at three levels of biological organisation: individual-level body sizes and cumulative reproduction, population-level abundance and biomass and ecosystem-level leaf litter decomposition. Interactive effects of multiple stressors at the individual level were mostly antagonistic, that is, less negative than expected. Most population- and ecosystem-level responses to multiple stressors were stronger than expected from an additive model, that is, synergistic. Our results suggest that across levels of biological organisation responses to multiple stressors are rarely only additive. We suggest methods for efficiently quantifying impacts of multiple stressors at different levels of biological organisation. © 2018 John Wiley & Sons Ltd/CNRS.

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

PubMed Central

Ratcliff, Roger; Starns, Jeffrey J.

2014-01-01

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

Hierarchical, parallel computing strategies using component object model for process modelling responses of forest plantations to interacting multiple stresses

Treesearch

J. G. Isebrands; G. E. Host; K. Lenz; G. Wu; H. W. Stech

2000-01-01

Process models are powerful research tools for assessing the effects of multiple environmental stresses on forest plantations. These models are driven by interacting environmental variables and often include genetic factors necessary for assessing forest plantation growth over a range of different site, climate, and silvicultural conditions. However, process models are...

Predictive Multiple Model Switching Control with the Self-Organizing Map

NASA Technical Reports Server (NTRS)

Motter, Mark A.

2000-01-01

A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.

Statistical strategies for averaging EC50 from multiple dose-response experiments.

PubMed

Jiang, Xiaoqi; Kopp-Schneider, Annette

2015-11-01

In most dose-response studies, repeated experiments are conducted to determine the EC50 value for a chemical, requiring averaging EC50 estimates from a series of experiments. Two statistical strategies, the mixed-effect modeling and the meta-analysis approach, can be applied to estimate average behavior of EC50 values over all experiments by considering the variabilities within and among experiments. We investigated these two strategies in two common cases of multiple dose-response experiments in (a) complete and explicit dose-response relationships are observed in all experiments and in (b) only in a subset of experiments. In case (a), the meta-analysis strategy is a simple and robust method to average EC50 estimates. In case (b), all experimental data sets can be first screened using the dose-response screening plot, which allows visualization and comparison of multiple dose-response experimental results. As long as more than three experiments provide information about complete dose-response relationships, the experiments that cover incomplete relationships can be excluded from the meta-analysis strategy of averaging EC50 estimates. If there are only two experiments containing complete dose-response information, the mixed-effects model approach is suggested. We subsequently provided a web application for non-statisticians to implement the proposed meta-analysis strategy of averaging EC50 estimates from multiple dose-response experiments.

A model for incomplete longitudinal multivariate ordinal data.

PubMed

Liu, Li C

2008-12-30

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

An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking.

PubMed

Zhu, Wei; Wang, Wei; Yuan, Gannan

2016-06-01

In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).

Conflict effects without conflict in anterior cingulate cortex: multiple response effects and context specific representations

PubMed Central

Brown, Joshua W.

2009-01-01

The error likelihood computational model of anterior cingulate cortex (ACC) (Brown & Braver, 2005) has successfully predicted error likelihood effects, risk prediction effects, and how individual differences in conflict and error likelihood effects vary with trait differences in risk aversion. The same computational model now makes a further prediction that apparent conflict effects in ACC may result in part from an increasing number of simultaneously active responses, regardless of whether or not the cued responses are mutually incompatible. In Experiment 1, the model prediction was tested with a modification of the Eriksen flanker task, in which some task conditions require two otherwise mutually incompatible responses to be generated simultaneously. In that case, the two response processes are no longer in conflict with each other. The results showed small but significant medial PFC effects in the incongruent vs. congruent contrast, despite the absence of response conflict, consistent with model predictions. This is the multiple response effect. Nonetheless, actual response conflict led to greater ACC activation, suggesting that conflict effects are specific to particular task contexts. In Experiment 2, results from a change signal task suggested that the context dependence of conflict signals does not depend on error likelihood effects. Instead, inputs to ACC may reflect complex and task specific representations of motor acts, such as bimanual responses. Overall, the results suggest the existence of a richer set of motor signals monitored by medial PFC and are consistent with distinct effects of multiple responses, conflict, and error likelihood in medial PFC. PMID:19375509

Development of a Finite Element Model of the Human Shoulder to Investigate the Mechanical Responses and Injuries in Side Impact

NASA Astrophysics Data System (ADS)

Iwamoto, Masami; Miki, Kazuo; Yang, King H.

Previous studies in both fields of automotive safety and orthopedic surgery have hypothesized that immobilization of the shoulder caused by the shoulder injury could be related to multiple rib fractures, which are frequently life threatening. Therefore, for more effective occupant protection, it is important to understand the relationship between shoulder injury and multiple rib fractures in side impact. The purpose of this study is to develop a finite element model of the human shoulder in order to understand this relationship. The shoulder model included three bones (the humerus, scapula and clavicle) and major ligaments and muscles around the shoulder. The model also included approaches to represent bone fractures and joint dislocations. The relationships between shoulder injury and immobilization of the shoulder are discussed using model responses for lateral shoulder impact. It is also discussed how the injury can be related to multiple rib fractures.

Making assessments while taking repeated risks: a pattern of multiple response pathways.

PubMed

Pleskac, Timothy J; Wershbale, Avishai

2014-02-01

Beyond simply a decision process, repeated risky decisions also require a number of cognitive processes including learning, search and exploration, and attention. In this article, we examine how multiple response pathways develop over repeated risky decisions. Using the Balloon Analogue Risk Task (BART) as a case study, we show that 2 different response pathways emerge over the course of the task. The assessment pathway is a slower, more controlled pathway where participants deliberate over taking a risk. The 2nd pathway is a faster, more automatic process where no deliberation occurs. Results imply the slower assessment pathway is taken as choice conflict increases and that the faster automatic response is a learned response. Based on these results, we modify an existing formal cognitive model of decision making during the BART to account for these dual response pathways. The slower more deliberative response process is modeled with a sequential sampling process where evidence is accumulated to a threshold, while the other response is given automatically. We show that adolescents with conduct disorder and substance use disorder symptoms not only evaluate risks differently during the BART but also differ in the rate at which they develop the more automatic response. More broadly, our results suggest cognitive models of judgment decision making need to transition from treating observed decisions as the result of a single response pathway to the result of multiple response pathways that change and develop over time.

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

PubMed Central

Sigman, Mariano; Cecchi, Guillermo A.

2018-01-01

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

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.

A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

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

Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If themore » detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.« less

A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

DOE PAGES

Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

2017-06-13

An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If themore » detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.« less

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

ERIC Educational Resources Information Center

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

The Multiple-Choice Model: Some Solutions for Estimation of Parameters in the Presence of Omitted Responses

ERIC Educational Resources Information Center

Abad, Francisco J.; Olea, Julio; Ponsoda, Vicente

2009-01-01

This article deals with some of the problems that have hindered the application of Samejima's and Thissen and Steinberg's multiple-choice models: (a) parameter estimation difficulties owing to the large number of parameters involved, (b) parameter identifiability problems in the Thissen and Steinberg model, and (c) their treatment of omitted…

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.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-01-01

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

The e-MSWS-12: improving the multiple sclerosis walking scale using item response theory.

PubMed

Engelhard, Matthew M; Schmidt, Karen M; Engel, Casey E; Brenton, J Nicholas; Patek, Stephen D; Goldman, Myla D

2016-12-01

The Multiple Sclerosis Walking Scale (MSWS-12) is the predominant patient-reported measure of multiple sclerosis (MS) -elated walking ability, yet it had not been analyzed using item response theory (IRT), the emerging standard for patient-reported outcome (PRO) validation. This study aims to reduce MSWS-12 measurement error and facilitate computerized adaptive testing by creating an IRT model of the MSWS-12 and distributing it online. MSWS-12 responses from 284 subjects with MS were collected by mail and used to fit and compare several IRT models. Following model selection and assessment, subpopulations based on age and sex were tested for differential item functioning (DIF). Model comparison favored a one-dimensional graded response model (GRM). This model met fit criteria and explained 87 % of response variance. The performance of each MSWS-12 item was characterized using category response curves (CRCs) and item information. IRT-based MSWS-12 scores correlated with traditional MSWS-12 scores (r = 0.99) and timed 25-foot walk (T25FW) speed (r =  -0.70). Item 2 showed DIF based on age (χ 2  = 19.02, df = 5, p < 0.01), and Item 11 showed DIF based on sex (χ 2  = 13.76, df = 5, p = 0.02). MSWS-12 measurement error depends on walking ability, but could be lowered by improving or replacing items with low information or DIF. The e-MSWS-12 includes IRT-based scoring, error checking, and an estimated T25FW derived from MSWS-12 responses. It is available at https://ms-irt.shinyapps.io/e-MSWS-12 .

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.

The Performance of IRT Model Selection Methods with Mixed-Format Tests

ERIC Educational Resources Information Center

Whittaker, Tiffany A.; Chang, Wanchen; Dodd, Barbara G.

2012-01-01

When tests consist of multiple-choice and constructed-response items, researchers are confronted with the question of which item response theory (IRT) model combination will appropriately represent the data collected from these mixed-format tests. This simulation study examined the performance of six model selection criteria, including the…

Infrasound-array-element frequency response: in-situ measurement and modeling

NASA Astrophysics Data System (ADS)

Gabrielson, T.

2011-12-01

Most array elements at the infrasound stations of the International Monitoring System use some variant of a multiple-inlet pipe system for wind-noise suppression. These pipe systems have a significant impact on the overall frequency response of the element. The spatial distribution of acoustic inlets introduces a response dependence that is a function of frequency and of vertical and horizontal arrival angle; the system of inlets, pipes, and summing junctions further shapes that response as the signal is ducted to the transducer. In-situ measurements, using a co-located reference microphone, can determine the overall frequency response and diagnose problems with the system. As of July 2011, the in-situ frequency responses for 25 individual elements at 6 operational stations (I10, I53, I55, I56, I57, and I99) have been measured. In support of these measurements, a fully thermo-viscous model for the acoustics of these multiple-inlet pipe systems has been developed. In addition to measurements at operational stations, comparative analyses have been done on experimental systems: a multiple-inlet radial-pipe system with varying inlet hole size; a one-quarter scale model of a 70-meter rosette system; and vertical directionality of a small rosette system using aircraft flyovers. [Funded by the US Army Space and Missile Defense Command

Cognitive Diagnostic Models for Tests with Multiple-Choice and Constructed-Response Items

ERIC Educational Resources Information Center

Kuo, Bor-Chen; Chen, Chun-Hua; Yang, Chih-Wei; Mok, Magdalena Mo Ching

2016-01-01

Traditionally, teachers evaluate students' abilities via their total test scores. Recently, cognitive diagnostic models (CDMs) have begun to provide information about the presence or absence of students' skills or misconceptions. Nevertheless, CDMs are typically applied to tests with multiple-choice (MC) items, which provide less diagnostic…

Impulsive response of an automatic transmission system with multiple clearances: Formulation, simulation and experiment

NASA Astrophysics Data System (ADS)

Crowther, Ashley R.; Singh, Rajendra; Zhang, Nong; Chapman, Chris

2007-10-01

Impulsive responses in geared systems with multiple clearances are studied when the mean torque excitation and system load change abruptly, with application to a vehicle driveline with an automatic transmission. First, torsional lumped-mass models of the planetary and differential gear sets are formulated using matrix elements. The model is then reduced to address tractable nonlinear problems while successfully retaining the main modes of interest. Second, numerical simulations for the nonlinear model are performed for transient conditions and a typical driving situation that induces an impulsive behaviour simulated. However, initial conditions and excitation and load profiles have to be carefully defined before the model can be numerically solved. It is shown that the impacts within the planetary or differential gears may occur under combinations of engine, braking and vehicle load transients. Our analysis shows that the shaping of the engine transient by the torque converter before reaching the clearance locations is more critical. Third, a free vibration experiment is developed for an analogous driveline with multiple clearances and three experiments that excite different response regimes have been carried out. Good correlations validate the proposed methodology.

mEBT: multiple-matching Evidence-based Translator of Murine Genomic Responses for Human Immunity Studies.

PubMed

Tae, Donghyun; Seok, Junhee

2018-05-29

In this paper, we introduce multiple-matching Evidence-based Translator (mEBT) to discover genomic responses from murine expression data for human immune studies, which are significant in the given condition of mice and likely have similar responses in the corresponding condition of human. mEBT is evaluated over multiple data sets and shows improved inter-species agreement. mEBT is expected to be useful for research groups who use murine models to study human immunity. http://cdal.korea.ac.kr/mebt/. jseok14@korea.ac.kr. Supplementary data are available at Bioinformatics online.

Modeling hydrologic responses to deforestation/forestation and climate change at multiple scales in the Southern US and China

Treesearch

Ge Sun; Steven McNulty; Jianbiao Lu; James Vose; Devendra Amayta; Guoyi Zhou; Zhiqiang Zhang

2006-01-01

Watershed management and restoration practices require a clear understanding of the basic eco-hydrologic processes and ecosystem responses to disturbances at multiple scales (Bruijnzeel, 2004; Scott et al., 2005). Worldwide century-long forest hydrologic research has documented that deforestation and forestation (i.e. reforestation and afforestation) can have variable...

Single-Trial Analysis of V1 Responses Suggests Two Transmission States

NASA Technical Reports Server (NTRS)

Shah, A. S.; Knuth, K. H.; Truccolo, W. A.; Mehta, A. D.; McGinnis, T.; OConnell, N.; Ding, M.; Bressler, S. L.; Schroeder, C. E.

2002-01-01

Sensory processing in the visual, auditory, and somatosensory systems is often studied by recording electrical activity in response to a stimulus of interest. Typically, multiple trial responses to the stimulus are averaged to isolate the stereotypic response from noise. However, averaging ignores dynamic variability in the neuronal response, which is potentially critical to understanding stimulus-processing schemes. Thus, we developed the multiple component, Event-Related Potential (mcERP) model. This model asserts that multiple components, defined as stereotypic waveforms, comprise the stimulus-evoked response and that these components may vary in amplitude and latency from trial to trial. Application of this model to data recorded simultaneously from all six laminae of V1 in an awake, behaving monkey performing a visual discrimination yielded three components. The first component localized to granular V1, the second was located in supragranular V1, and the final component displayed a multi-laminar distribution. These modeling results, which take into account single-trial response dynamics, illustrated that the initial activation of VI occurs in the granular layer followed by activation in the supragranular layers. This finding is expected because the average response in those layers demonstrates the same progression and because anatomical evidence suggests that the feedforward input in V1 enters the granular layer and progresses to supragranular layers. In addition to these findings, the granular component of the model displayed several interesting trial-to-trial characteristics including (1) a bimodal latency distribution, (2) a latency-related variation in response amplitude, (3) a latency correlation with the supragranular component, and (4) an amplitude and latency association with the multi-laminar component. Direct analyses of the single-trial data were consistent with these model predictions. These findings suggest that V1 has at least 2 transmission states, which may be modulated by various effects such as attention, dynamics in local EEG rhythm, or variation in sensory inputs.

An improved null model for assessing the net effects of multiple stressors on communities.

PubMed

Thompson, Patrick L; MacLennan, Megan M; Vinebrooke, Rolf D

2018-01-01

Ecological stressors (i.e., environmental factors outside their normal range of variation) can mediate each other through their interactions, leading to unexpected combined effects on communities. Determining whether the net effect of stressors is ecologically surprising requires comparing their cumulative impact to a null model that represents the linear combination of their individual effects (i.e., an additive expectation). However, we show that standard additive and multiplicative null models that base their predictions on the effects of single stressors on community properties (e.g., species richness or biomass) do not provide this linear expectation, leading to incorrect interpretations of antagonistic and synergistic responses by communities. We present an alternative, the compositional null model, which instead bases its predictions on the effects of stressors on individual species, and then aggregates them to the community level. Simulations demonstrate the improved ability of the compositional null model to accurately provide a linear expectation of the net effect of stressors. We simulate the response of communities to paired stressors that affect species in a purely additive fashion and compare the relative abilities of the compositional null model and two standard community property null models (additive and multiplicative) to predict these linear changes in species richness and community biomass across different combinations (both positive, negative, or opposite) and intensities of stressors. The compositional model predicts the linear effects of multiple stressors under almost all scenarios, allowing for proper classification of net effects, whereas the standard null models do not. Our findings suggest that current estimates of the prevalence of ecological surprises on communities based on community property null models are unreliable, and should be improved by integrating the responses of individual species to the community level as does our compositional null model. © 2017 John Wiley & Sons Ltd.

Multiscale modeling of mucosal immune responses

PubMed Central

2015-01-01

Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787

Multiscale modeling of mucosal immune responses.

PubMed

Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

2015-01-01

Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.

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.

Modeling the poroelastic response to megathrust earthquakes: A look at the 2012 Mw 7.6 Costa Rican event

NASA Astrophysics Data System (ADS)

McCormack, Kimberly A.; Hesse, Marc A.

2018-04-01

We model the subsurface hydrologic response to the 7.6 Mw subduction zone earthquake that occurred on the plate interface beneath the Nicoya peninsula in Costa Rica on September 5, 2012. The regional-scale poroelastic model of the overlying plate integrates seismologic, geodetic and hydrologic data sets to predict the post-seismic poroelastic response. A representative two-dimensional model shows that thrust earthquakes with a slip width less than a third of their depth produce complex multi-lobed pressure perturbations in the shallow subsurface. This leads to multiple poroelastic relaxation timescales that may overlap with the longer viscoelastic timescales. In the three-dimensional model, the complex slip distribution of 2012 Nicoya event and its small width to depth ratio lead to a pore pressure distribution comprising multiple trench parallel ridges of high and low pressure. This leads to complex groundwater flow patterns, non-monotonic variations in predicted well water levels, and poroelastic relaxation on multiple time scales. The model also predicts significant tectonically driven submarine groundwater discharge off-shore. In the weeks following the earthquake, the predicted net submarine groundwater discharge in the study area increases, creating a 100 fold increase in net discharge relative to topography-driven flow over the first 30 days. Our model suggests the hydrological response on land is more complex than typically acknowledged in tectonic studies. This may complicate the interpretation of transient post-seismic surface deformations. Combined tectonic-hydrological observation networks have the potential to reduce such ambiguities.

ACIRF user's guide: Theory and examples

NASA Astrophysics Data System (ADS)

Dana, Roger A.

1989-12-01

Design and evaluation of radio frequency systems that must operate through ionospheric disturbances resulting from high altitude nuclear detonations requires an accurate channel model. This model must include the effects of high gain antennas that may be used to receive the signals. Such a model can then be used to construct realizations of the received signal for use in digital simulations of trans-ionospheric links or for use in hardware channel simulators. The FORTRAN channel model ACIRF (Antenna Channel Impulse Response Function) generates random realizations of the impulse response function at the outputs of multiple antennas. This user's guide describes the FORTRAN program ACIRF (version 2.0) that generates realizations of channel impulse response functions at the outputs of multiple antennas with arbitrary beamwidths, pointing angles, and relatives positions. This channel model is valid under strong scattering conditions when Rayleigh fading statistics apply. Both frozen-in and turbulent models for the temporal fluctuations are included in this version of ACIRF. The theory of the channel model is described and several examples are given.

Mouse and Guinea Pig Models of Tuberculosis.

PubMed

Orme, Ian M; Ordway, Diane J

2016-08-01

This article describes the nature of the host response to Mycobacterium tuberculosis in the mouse and guinea pig models of infection. It describes the great wealth of information obtained from the mouse model, reflecting the general availability of immunological reagents, as well as genetic manipulations of the mouse strains themselves. This has led to a good understanding of the nature of the T-cell response to the infection, as well as an appreciation of the complexity of the response involving multiple cytokine- and chemokine-mediated systems. As described here and elsewhere, we have a growing understanding of how multiple CD4-positive T-cell subsets are involved, including regulatory T cells, TH17 cells, as well as the subsequent emergence of effector and central memory T-cell subsets. While, in contrast, our understanding of the host response in the guinea pig model is less advanced, considerable strides have been made in the past decade in terms of defining the basis of the immune response, as well as a better understanding of the immunopathologic process. This model has long been the gold standard for vaccine testing, and more recently is being revisited as a model for testing new drug regimens (bedaquiline being the latest example).

Locally Dependent Latent Trait Model and the Dutch Identity Revisited.

ERIC Educational Resources Information Center

Ip, Edward H.

2002-01-01

Proposes a class of locally dependent latent trait models for responses to psychological and educational tests. Focuses on models based on a family of conditional distributions, or kernel, that describes joint multiple item responses as a function of student latent trait, not assuming conditional independence. Also proposes an EM algorithm for…

Generating Multiple Imputations for Matrix Sampling Data Analyzed with Item Response Models.

ERIC Educational Resources Information Center

Thomas, Neal; Gan, Nianci

1997-01-01

Describes and assesses missing data methods currently used to analyze data from matrix sampling designs implemented by the National Assessment of Educational Progress. Several improved methods are developed, and these models are evaluated using an EM algorithm to obtain maximum likelihood estimates followed by multiple imputation of complete data…

Teaching Children with Autism to Discriminate the Reinforced and Nonreinforced Responses of Others: Implications for Observational Learning

ERIC Educational Resources Information Center

DeQuinzio, Jaime Ann; Taylor, Bridget A.

2015-01-01

We taught 4 participants with autism to discriminate between the reinforced and nonreinforced responses of an adult model and evaluated the effectiveness of this intervention using a multiple baseline design. During baseline, participants were simply exposed to adult models' correct and incorrect responses and the respective consequences of each.…

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

Item Response Theory with Covariates (IRT-C): Assessing Item Recovery and Differential Item Functioning for the Three-Parameter Logistic Model

ERIC Educational Resources Information Center

Tay, Louis; Huang, Qiming; Vermunt, Jeroen K.

2016-01-01

In large-scale testing, the use of multigroup approaches is limited for assessing differential item functioning (DIF) across multiple variables as DIF is examined for each variable separately. In contrast, the item response theory with covariate (IRT-C) procedure can be used to examine DIF across multiple variables (covariates) simultaneously. To…

Expression of Multiple Stress Response Genes by Escherichia Coli Under Modeled Reduced Gravity

NASA Astrophysics Data System (ADS)

Vukanti, Raja; Leff, Laura G.

2012-09-01

Bacteria, in response to changes in their environment, quickly regulate gene expression; hence, transcriptional profiling has been widely used to characterize bacterial responses to various environmental conditions. In this study, we used clinorotation to grow bacteria under low-sedimentation, -shear, and -turbulence conditions (referred to as modeled reduced gravity, MRG, below) which profoundly impacts bacteria including causing elevated resistance to multiple environmental stresses. To explore potential mechanisms behind the multiple stress resistance response to MRG, we assessed expression levels of E. coli genes, using reverse transcription followed by real-time-PCR, involved in specific stress and general stress responses under MRG and normal gravity (NG) in nutritionally rich and minimal media, and during exponential and stationary phases of growth. In addition, growth rates as well as physico-chemical parameters of culture media were examined. Over-expression of stress response genes (csiD, cstA, katE, otsA, treA) occurred under MRG compared to NG controls, but only during the later stages of growth in rich medium demonstrating that bacterial response to MRG varies with growth-medium and -phase. At stationary phase in rich medium under MRG and NG, E. coli had similar growth rates (based on rRNA-leader abundance) and yields (cell mass and numbers); this coupled, with observations of simultaneous induction of starvation response genes (csiD and cstA) suggests the multiple stress resistance phenotype under MRG could be attributable to microzones of nutrient unavailability around cells. Overall, in rich medium, the response resembled the general stress response (GSR) that E. coli develops during stationary phase of growth. Along these same lines, induction of genes coding for GSR was reversed by improving nutritional conditions under MRG. The reversal of GSR under MRG suggests that the multiple stress response exhibited is not specific to MRG but may result from nutrient limitation experienced by bacteria after incubation in nutrient-rich media under these conditions.

Analysis of bacterial migration. 2: Studies with multiple attractant gradients

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

Strauss, I.; Frymier, P.D.; Hahn, C.M.

1995-02-01

Many motile bacteria exhibit chemotaxis, the ability to bias their random motion toward or away from increasing concentrations of chemical substances which benefit or inhibit their survival, respectively. Since bacteria encounter numerous chemical concentration gradients simultaneously in natural surroundings, it is necessary to know quantitatively how a bacterial population responds in the presence of more than one chemical stimulus to develop predictive mathematical models describing bacterial migration in natural systems. This work evaluates three hypothetical models describing the integration of chemical signals from multiple stimuli: high sensitivity, maximum signal, and simple additivity. An expression for the tumbling probability for individualmore » stimuli is modified according to the proposed models and incorporated into the cell balance equation for a 1-D attractant gradient. Random motility and chemotactic sensitivity coefficients, required input parameters for the model, are measured for single stimulus responses. Theoretical predictions with the three signal integration models are compared to the net chemotactic response of Escherichia coli to co- and antidirectional gradients of D-fucose and [alpha]-methylaspartate in the stopped-flow diffusion chamber assay. Results eliminate the high-sensitivity model and favor the simple additivity over the maximum signal. None of the simple models, however, accurately predict the observed behavior, suggesting a more complex model with more steps in the signal processing mechanism is required to predict responses to multiple stimuli.« less

Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

PubMed

Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

2017-01-31

Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.

Final state interactions and inclusive nuclear collisions

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Dubey, Rajendra R.

1993-01-01

A scattering formalism is developed in a multiple scattering model to describe inclusive momentum distributions for high-energy projectiles. The effects of final state interactions on response functions and momentum distributions are investigated. Calculations for high-energy protons that include shell model response functions are compared with experiments.

The effects of climate downscaling technique and observational data set on modeled ecological responses

Treesearch

Afshin Pourmokhtarian; Charles T. Driscoll; John L. Campbell; Katharine Hayhoe; Anne M. K. Stoner

2016-01-01

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training...

Covariates of the Rating Process in Hierarchical Models for Multiple Ratings of Test Items

ERIC Educational Resources Information Center

Mariano, Louis T.; Junker, Brian W.

2007-01-01

When constructed response test items are scored by more than one rater, the repeated ratings allow for the consideration of individual rater bias and variability in estimating student proficiency. Several hierarchical models based on item response theory have been introduced to model such effects. In this article, the authors demonstrate how these…

Least-squares deconvolution of evoked potentials and sequence optimization for multiple stimuli under low-jitter conditions.

PubMed

Bardy, Fabrice; Dillon, Harvey; Van Dun, Bram

2014-04-01

Rapid presentation of stimuli in an evoked response paradigm can lead to overlap of multiple responses and consequently difficulties interpreting waveform morphology. This paper presents a deconvolution method allowing overlapping multiple responses to be disentangled. The deconvolution technique uses a least-squared error approach. A methodology is proposed to optimize the stimulus sequence associated with the deconvolution technique under low-jitter conditions. It controls the condition number of the matrices involved in recovering the responses. Simulations were performed using the proposed deconvolution technique. Multiple overlapping responses can be recovered perfectly in noiseless conditions. In the presence of noise, the amount of error introduced by the technique can be controlled a priori by the condition number of the matrix associated with the used stimulus sequence. The simulation results indicate the need for a minimum amount of jitter, as well as a sufficient number of overlap combinations to obtain optimum results. An aperiodic model is recommended to improve reconstruction. We propose a deconvolution technique allowing multiple overlapping responses to be extracted and a method of choosing the stimulus sequence optimal for response recovery. This technique may allow audiologists, psychologists, and electrophysiologists to optimize their experimental designs involving rapidly presented stimuli, and to recover evoked overlapping responses. Copyright © 2013 International Federation of Clinical Neurophysiology. All rights reserved.

Multiple Component Event-Related Potential (mcERP) Estimation

NASA Technical Reports Server (NTRS)

Knuth, K. H.; Clanton, S. T.; Shah, A. S.; Truccolo, W. A.; Ding, M.; Bressler, S. L.; Trejo, L. J.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

We show how model-based estimation of the neural sources responsible for transient neuroelectric signals can be improved by the analysis of single trial data. Previously, we showed that a multiple component event-related potential (mcERP) algorithm can extract the responses of individual sources from recordings of a mixture of multiple, possibly interacting, neural ensembles. McERP also estimated single-trial amplitudes and onset latencies, thus allowing more accurate estimation of ongoing neural activity during an experimental trial. The mcERP algorithm is related to informax independent component analysis (ICA); however, the underlying signal model is more physiologically realistic in that a component is modeled as a stereotypic waveshape varying both in amplitude and onset latency from trial to trial. The result is a model that reflects quantities of interest to the neuroscientist. Here we demonstrate that the mcERP algorithm provides more accurate results than more traditional methods such as factor analysis and the more recent ICA. Whereas factor analysis assumes the sources are orthogonal and ICA assumes the sources are statistically independent, the mcERP algorithm makes no such assumptions thus allowing investigators to examine interactions among components by estimating the properties of single-trial responses.

Multilevel Higher-Order Item Response Theory Models

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2014-01-01

In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

Experimental design and multiple response optimization. Using the desirability function in analytical methods development.

PubMed

Candioti, Luciana Vera; De Zan, María M; Cámara, María S; Goicoechea, Héctor C

2014-06-01

A review about the application of response surface methodology (RSM) when several responses have to be simultaneously optimized in the field of analytical methods development is presented. Several critical issues like response transformation, multiple response optimization and modeling with least squares and artificial neural networks are discussed. Most recent analytical applications are presented in the context of analytLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function. Copyright © 2014 Elsevier B.V. All rights reserved.

Species co-occurrence analysis predicts management outcomes for multiple threats.

PubMed

Tulloch, Ayesha I T; Chadès, Iadine; Lindenmayer, David B

2018-03-01

Mitigating the impacts of global anthropogenic change on species is conservation's greatest challenge. Forecasting the effects of actions to mitigate threats is hampered by incomplete information on species' responses. We develop an approach to predict community restructuring under threat management, which combines models of responses to threats with network analyses of species co-occurrence. We discover that contributions by species to network co-occurrence predict their recovery under reduction of multiple threats. Highly connected species are likely to benefit more from threat management than poorly connected species. Importantly, we show that information from a few species on co-occurrence and expected responses to alternative threat management actions can be used to train a response model for an entire community. We use a unique management dataset for a threatened bird community to validate our predictions and, in doing so, demonstrate positive feedbacks in occurrence and co-occurrence resulting from shared threat management responses during ecosystem recovery.

Maximizing the Information and Validity of a Linear Composite in the Factor Analysis Model for Continuous Item Responses

ERIC Educational Resources Information Center

Ferrando, Pere J.

2008-01-01

This paper develops results and procedures for obtaining linear composites of factor scores that maximize: (a) test information, and (b) validity with respect to external variables in the multiple factor analysis (FA) model. I treat FA as a multidimensional item response theory model, and use Ackerman's multidimensional information approach based…

Analysis Test of Understanding of Vectors with the Three-Parameter Logistic Model of Item Response Theory and Item Response Curves Technique

ERIC Educational Resources Information Center

Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

2016-01-01

This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming…

Multiple Model Adaptive Attitude Control of LEO Satellite with Angular Velocity Constraints

NASA Astrophysics Data System (ADS)

Shahrooei, Abolfazl; Kazemi, Mohammad Hosein

2018-04-01

In this paper, the multiple model adaptive control is utilized to improve the transient response of attitude control system for a rigid spacecraft. An adaptive output feedback control law is proposed for attitude control under angular velocity constraints and its almost global asymptotic stability is proved. The multiple model adaptive control approach is employed to counteract large uncertainty in parameter space of the inertia matrix. The nonlinear dynamics of a low earth orbit satellite is simulated and the proposed control algorithm is implemented. The reported results show the effectiveness of the suggested scheme.

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.

Models for Scoring Missing Responses to Multiple-Choice Items. Program Statistics Research Technical Report No. 94-1.

ERIC Educational Resources Information Center

Longford, Nicholas T.

This study is a critical evaluation of the roles for coding and scoring of missing responses to multiple-choice items in educational tests. The focus is on tests in which the test-takers have little or no motivation; in such tests omitting and not reaching (as classified by the currently adopted operational rules) is quite frequent. Data from the…

Excitatory and Inhibitory Interactions in Localized Populations of Model Neurons

PubMed Central

Wilson, Hugh R.; Cowan, Jack D.

1972-01-01

Coupled nonlinear differential equations are derived for the dynamics of spatially localized populations containing both excitatory and inhibitory model neurons. Phase plane methods and numerical solutions are then used to investigate population responses to various types of stimuli. The results obtained show simple and multiple hysteresis phenomena and limit cycle activity. The latter is particularly interesting since the frequency of the limit cycle oscillation is found to be a monotonic function of stimulus intensity. Finally, it is proved that the existence of limit cycle dynamics in response to one class of stimuli implies the existence of multiple stable states and hysteresis in response to a different class of stimuli. The relation between these findings and a number of experiments is discussed. PMID:4332108

A multiple-point geostatistical approach to quantifying uncertainty for flow and transport simulation in geologically complex environments

NASA Astrophysics Data System (ADS)

Cronkite-Ratcliff, C.; Phelps, G. A.; Boucher, A.

2011-12-01

In many geologic settings, the pathways of groundwater flow are controlled by geologic heterogeneities which have complex geometries. Models of these geologic heterogeneities, and consequently, their effects on the simulated pathways of groundwater flow, are characterized by uncertainty. Multiple-point geostatistics, which uses a training image to represent complex geometric descriptions of geologic heterogeneity, provides a stochastic approach to the analysis of geologic uncertainty. Incorporating multiple-point geostatistics into numerical models provides a way to extend this analysis to the effects of geologic uncertainty on the results of flow simulations. We present two case studies to demonstrate the application of multiple-point geostatistics to numerical flow simulation in complex geologic settings with both static and dynamic conditioning data. Both cases involve the development of a training image from a complex geometric description of the geologic environment. Geologic heterogeneity is modeled stochastically by generating multiple equally-probable realizations, all consistent with the training image. Numerical flow simulation for each stochastic realization provides the basis for analyzing the effects of geologic uncertainty on simulated hydraulic response. The first case study is a hypothetical geologic scenario developed using data from the alluvial deposits in Yucca Flat, Nevada. The SNESIM algorithm is used to stochastically model geologic heterogeneity conditioned to the mapped surface geology as well as vertical drill-hole data. Numerical simulation of groundwater flow and contaminant transport through geologic models produces a distribution of hydraulic responses and contaminant concentration results. From this distribution of results, the probability of exceeding a given contaminant concentration threshold can be used as an indicator of uncertainty about the location of the contaminant plume boundary. The second case study considers a characteristic lava-flow aquifer system in Pahute Mesa, Nevada. A 3D training image is developed by using object-based simulation of parametric shapes to represent the key morphologic features of rhyolite lava flows embedded within ash-flow tuffs. In addition to vertical drill-hole data, transient pressure head data from aquifer tests can be used to constrain the stochastic model outcomes. The use of both static and dynamic conditioning data allows the identification of potential geologic structures that control hydraulic response. These case studies demonstrate the flexibility of the multiple-point geostatistics approach for considering multiple types of data and for developing sophisticated models of geologic heterogeneities that can be incorporated into numerical flow simulations.

Equilibrium muscle cross-bridge behavior. Theoretical considerations.

PubMed Central

Schoenberg, M

1985-01-01

We have developed a model for the equilibrium attachment and detachment of myosin cross-bridges to actin that takes into account the possibility that a given cross-bridge can bind to one of a number of actin monomers, as seems likely, rather than to a site on only a single actin monomer, as is often assumed. The behavior of this multiple site model in response to constant velocity, as well as instantaneous stretches, was studied and the influence of system parameters on the force response explored. It was found that in the multiple site model the detachment rate constant has considerably greater influence on the mechanical response than the attachment rate constant. It is shown that one can obtain information about the detachment rate constants either by examining the relationship between the apparent stiffness and duration of stretch for constant velocity stretches or by examining the force-decay rate constants following an instantaneous stretch. The main effect of the attachment rate constant is to scale the mechanical response by influencing the number of attached cross-bridges. The significance of the modeling for the interpretation of experimental results is discussed. PMID:4041539

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

Myeloma Cell Dynamics in Response to Treatment Supports a Model of Hierarchical Differentiation and Clonal Evolution.

PubMed

Tang, Min; Zhao, Rui; van de Velde, Helgi; Tross, Jennifer G; Mitsiades, Constantine; Viselli, Suzanne; Neuwirth, Rachel; Esseltine, Dixie-Lee; Anderson, Kenneth; Ghobrial, Irene M; San Miguel, Jesús F; Richardson, Paul G; Tomasson, Michael H; Michor, Franziska

2016-08-15

Since the pioneering work of Salmon and Durie, quantitative measures of tumor burden in multiple myeloma have been used to make clinical predictions and model tumor growth. However, such quantitative analyses have not yet been performed on large datasets from trials using modern chemotherapy regimens. We analyzed a large set of tumor response data from three randomized controlled trials of bortezomib-based chemotherapy regimens (total sample size n = 1,469 patients) to establish and validate a novel mathematical model of multiple myeloma cell dynamics. Treatment dynamics in newly diagnosed patients were most consistent with a model postulating two tumor cell subpopulations, "progenitor cells" and "differentiated cells." Differential treatment responses were observed with significant tumoricidal effects on differentiated cells and less clear effects on progenitor cells. We validated this model using a second trial of newly diagnosed patients and a third trial of refractory patients. When applying our model to data of relapsed patients, we found that a hybrid model incorporating both a differentiation hierarchy and clonal evolution best explains the response patterns. The clinical data, together with mathematical modeling, suggest that bortezomib-based therapy exerts a selection pressure on myeloma cells that can shape the disease phenotype, thereby generating further inter-patient variability. This model may be a useful tool for improving our understanding of disease biology and the response to chemotherapy regimens. Clin Cancer Res; 22(16); 4206-14. ©2016 AACR. ©2016 American Association for Cancer Research.

Distinguishing Signatures of Multipathway Conformational Transitions

NASA Astrophysics Data System (ADS)

Pierse, Christopher A.; Dudko, Olga K.

2017-02-01

The folding and binding of biomolecules into functional conformations are thought to be commonly mediated by multiple pathways rather than a unique route. Yet even in experiments where one can "see" individual conformational transitions, their stochastic nature generally precludes one from determining whether the transitions occurred through one or multiple pathways. We establish model-free, observable signatures in the response of macromolecules to force that unambiguously identify multiple pathways—even when the pathways themselves cannot be resolved. The unified analytical description reveals that, through multiple pathways, the response of molecules to external forces can be shaped in diverse ways, resulting in a rich design space for a tailored biological function already at the single-molecule level.

Multiple emulsions as effective platforms for controlled anti-cancer drug delivery.

PubMed

Dluska, Ewa; Markowska-Radomska, Agnieszka; Metera, Agata; Tudek, Barbara; Kosicki, Konrad

2017-09-01

Developing pH-responsive multiple emulsion platforms for effective glioblastoma multiforme therapy with reduced toxicity, a drug release study and modeling. Cancer cell line: U87 MG, multiple emulsions with pH-responsive biopolymer and encapsulated doxorubicin (DOX); preparation of multiple emulsions in a Couette-Taylor flow biocontactor, in vitro release study of DOX (fluorescence intensity analysis), in vitro cytotoxicity study (alamarBlue cell viability assay) and numerical simulation of DOX release rates. The multiple emulsions offered a high DOX encapsulation efficiency (97.4 ± 1%) and pH modulated release rates of a drug. Multiple emulsions with a low concentration of DOX (0.02 μM) exhibited broadly advanced cell (U87 MG) cytotoxicity than free DOX solution used at the same concentration. Emulsion platforms could be explored for potential delivery of chemotherapeutics in glioblastoma multiforme therapy.

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.

On the use of three hydrological models as hypotheses to investigate the behaviour of a small Mediterranean catchment

NASA Astrophysics Data System (ADS)

Ruiz Pérez, Guiomar; Latron, Jérôme; Llorens, Pilar; Gallart, Francesc; Francés, Félix

2017-04-01

Selecting an adequate hydrological model is the first step to carry out a rainfall-runoff modelling exercise. A hydrological model is a hypothesis of catchment functioning, encompassing a description of dominant hydrological processes and predicting how these processes interact to produce the catchment's response to external forcing. Current research lines emphasize the importance of multiple working hypotheses for hydrological modelling instead of only using a single model. In line with this philosophy, here different hypotheses were considered and analysed to simulate the nonlinear response of a small Mediterranean catchment and to progress in the analysis of its hydrological behaviour. In particular, three hydrological models were considered representing different potential hypotheses: two lumped models called LU3 and LU4, and one distributed model called TETIS. To determine how well each specific model performed and to assess whether a model was more adequate than another, we raised three complementary tests: one based on the analysis of residual errors series, another based on a sensitivity analysis and the last one based on using multiple evaluation criteria associated to the concept of Pareto frontier. This modelling approach, based on multiple working hypotheses, helped to improve our perceptual model of the catchment behaviour and, furthermore, could be used as a guidance to improve the performance of other environmental models.

Multicategorical Spline Model for Item Response Theory.

ERIC Educational Resources Information Center

Abrahamowicz, Michal; Ramsay, James O.

1992-01-01

A nonparametric multicategorical model for multiple-choice data is proposed as an extension of the binary spline model of J. O. Ramsay and M. Abrahamowicz (1989). Results of two Monte Carlo studies illustrate the model, which approximates probability functions by rational splines. (SLD)

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.

A multi-scale assessment of population connectivity in African lions (Panthera leo) in response to landscape change

Treesearch

Samuel A. Cushman; Nicholas B. Elliot; David W. Macdonald; Andrew J. Loveridge

2015-01-01

Habitat loss and fragmentation are among the major drivers of population declines and extinction, particularly in large carnivores. Connectivity models provide practical tools for assessing fragmentation effects and developing mitigation or conservation responses. To be useful to conservation practitioners, connectivity models need to incorporate multiple scales and...

Mixture IRT Model with a Higher-Order Structure for Latent Traits

ERIC Educational Resources Information Center

Huang, Hung-Yu

2017-01-01

Mixture item response theory (IRT) models have been suggested as an efficient method of detecting the different response patterns derived from latent classes when developing a test. In testing situations, multiple latent traits measured by a battery of tests can exhibit a higher-order structure, and mixtures of latent classes may occur on…

The Rho Kinases: Critical Mediators of Multiple Profibrotic Processes and Rational Targets for New Therapies for Pulmonary Fibrosis

PubMed Central

Knipe, Rachel S.; Tager, Andrew M.

2015-01-01

Idiopathic pulmonary fibrosis (IPF) is characterized by progressive lung scarring, short median survival, and limited therapeutic options, creating great need for new pharmacologic therapies. IPF is thought to result from repetitive environmental injury to the lung epithelium, in the context of aberrant host wound healing responses. Tissue responses to injury fundamentally involve reorganization of the actin cytoskeleton of participating cells, including epithelial cells, fibroblasts, endothelial cells, and macrophages. Actin filament assembly and actomyosin contraction are directed by the Rho-associated coiled-coil forming protein kinase (ROCK) family of serine/threonine kinases (ROCK1 and ROCK2). As would therefore be expected, lung ROCK activation has been demonstrated in humans with IPF and in animal models of this disease. ROCK inhibitors can prevent fibrosis in these models, and more importantly, induce the regression of already established fibrosis. Here we review ROCK structure and function, upstream activators and downstream targets of ROCKs in pulmonary fibrosis, contributions of ROCKs to profibrotic cellular responses to lung injury, ROCK inhibitors and their efficacy in animal models of pulmonary fibrosis, and potential toxicities of ROCK inhibitors in humans, as well as involvement of ROCKs in fibrosis in other organs. As we discuss, ROCK activation is required for multiple profibrotic responses, in the lung and multiple other organs, suggesting ROCK participation in fundamental pathways that contribute to the pathogenesis of a broad array of fibrotic diseases. Multiple lines of evidence therefore indicate that ROCK inhibition has great potential to be a powerful therapeutic tool in the treatment of fibrosis, both in the lung and beyond. PMID:25395505

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

A Fast EM Algorithm for Fitting Joint Models of a Binary Response and Multiple Longitudinal Covariates Subject to Detection Limits

PubMed Central

Bernhardt, Paul W.; Zhang, Daowen; Wang, Huixia Judy

2014-01-01

Joint modeling techniques have become a popular strategy for studying the association between a response and one or more longitudinal covariates. Motivated by the GenIMS study, where it is of interest to model the event of survival using censored longitudinal biomarkers, a joint model is proposed for describing the relationship between a binary outcome and multiple longitudinal covariates subject to detection limits. A fast, approximate EM algorithm is developed that reduces the dimension of integration in the E-step of the algorithm to one, regardless of the number of random effects in the joint model. Numerical studies demonstrate that the proposed approximate EM algorithm leads to satisfactory parameter and variance estimates in situations with and without censoring on the longitudinal covariates. The approximate EM algorithm is applied to analyze the GenIMS data set. PMID:25598564

Modelling and simulation of biased agonism dynamics at a G protein-coupled receptor.

PubMed

Bridge, L J; Mead, J; Frattini, E; Winfield, I; Ladds, G

2018-04-07

Theoretical models of G protein-coupled receptor (GPCR) concentration-response relationships often assume an agonist producing a single functional response via a single active state of the receptor. These models have largely been analysed assuming steady-state conditions. There is now much experimental evidence to suggest that many GPCRs can exist in multiple receptor conformations and elicit numerous functional responses, with ligands having the potential to activate different signalling pathways to varying extents-a concept referred to as biased agonism, functional selectivity or pluri-dimensional efficacy. Moreover, recent experimental results indicate a clear possibility for time-dependent bias, whereby an agonist's bias with respect to different pathways may vary dynamically. Efforts towards understanding the implications of temporal bias by characterising and quantifying ligand effects on multiple pathways will clearly be aided by extending current equilibrium binding and biased activation models to include G protein activation dynamics. Here, we present a new model of time-dependent biased agonism, based on ordinary differential equations for multiple cubic ternary complex activation models with G protein cycle dynamics. This model allows simulation and analysis of multi-pathway activation bias dynamics at a single receptor for the first time, at the level of active G protein (α GTP ), towards the analysis of dynamic functional responses. The model is generally applicable to systems with N G G proteins and N* active receptor states. Numerical simulations for N G =N * =2 reveal new insights into the effects of system parameters (including cooperativities, and ligand and receptor concentrations) on bias dynamics, highlighting new phenomena including the dynamic inter-conversion of bias direction. Further, we fit this model to 'wet' experimental data for two competing G proteins (G i and G s ) that become activated upon stimulation of the adenosine A 1 receptor with adenosine derivative compounds. Finally, we show that our model can qualitatively describe the temporal dynamics of this competing G protein activation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

How will climate change affect watershed mercury export in a representative Coastal Plain watershed?

NASA Astrophysics Data System (ADS)

Golden, H. E.; Knightes, C. D.; Conrads, P. A.; Feaster, T.; Davis, G. M.; Benedict, S. T.; Bradley, P. M.

2012-12-01

Future climate change is expected to drive variations in watershed hydrological processes and water quality across a wide range of physiographic provinces, ecosystems, and spatial scales. How such shifts in climatic conditions will impact watershed mercury (Hg) dynamics and hydrologically-driven Hg transport is a significant concern. We simulate the responses of watershed hydrological and total Hg (HgT) fluxes and concentrations to a unified set of past and future climate change projections in a Coastal Plain basin using multiple watershed models. We use two statistically downscaled global precipitation and temperature models, ECHO, a hybrid of the ECHAM4 and HOPE-G models, and the Community Climate System Model (CCSM3) across two thirty-year simulations (1980 to 2010 and 2040 to 2070). We apply three watershed models to quantify and bracket potential changes in hydrologic and HgT fluxes, including the Visualizing Ecosystems for Land Management Assessment Model for Hg (VELMA-Hg), the Grid Based Mercury Model (GBMM), and TOPLOAD, a water quality constituent model linked to TOPMODEL hydrological simulations. We estimate a decrease in average annual HgT fluxes in response to climate change using the ECHO projections and an increase with the CCSM3 projections in the study watershed. Average monthly HgT fluxes increase using both climate change projections between in the late spring (March through May), when HgT concentrations and flow are high. Results suggest that hydrological transport associated with changes in precipitation and temperature is the primary mechanism driving HgT flux response to climate change. Our multiple model/multiple projection approach allows us to bracket the relative response of HgT fluxes to climate change, thereby illustrating the uncertainty associated with the projections. In addition, our approach allows us to examine potential variations in climate change-driven water and HgT export based on different conceptualizations of watershed HgT dynamics and the representative mathematical structures underpinning existing watershed Hg models.

Observation, Identification, and Impact of Multi-Modal Plasma Responses to Applied Magnetic Perturbations

NASA Astrophysics Data System (ADS)

Logan, Nikolas

2015-11-01

Experiments on DIII-D have demonstrated that multiple kink modes with comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n=2, in good agreement with ideal MHD models. In contrast to a single-mode model, the structure of the response measured using poloidally distributed magnetic sensors changes when varying the applied poloidal spectrum. This is most readily evident in that different spectra of applied fields can independently excite inboard and outboard magnetic responses, which are identified as distinct plasma modes by IPEC modeling. The outboard magnetic response is correlated with the plasma pressure and consistent with the long wavelength perturbations of the least stable, pressure driven kinks calculated by DCON and used in IPEC. The models show the structure of the pressure driven modes extends throughout the bad curvature region and into the plasma core. The inboard plasma response is correlated with the edge current profile and requires the inclusion of multiple kink modes with greater stability, including opposite helicity modes, to replicate the experimental observations in the models. IPEC reveals the resulting mode structure to be highly localized in the plasma edge. Scans of the applied spectrum show this response induces the transport that influences the density pump-out, as well as the toroidal rotation drag observed in experiment and modeled using PENT. The classification of these two mode types establishes a new multi-modal paradigm for n=2 plasma response and guides the understanding needed to optimize 3D fields for independent control of stability and transport. Supported by US DOE contract DE-AC02-09CH11466.

Predicting musically induced emotions from physiological inputs: linear and neural network models.

PubMed

Russo, Frank A; Vempala, Naresh N; Sandstrom, Gillian M

2013-01-01

Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of "felt" emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants-heart rate (HR), respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA) dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a non-linear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The non-linear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the non-linear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.

Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli.

PubMed

Aumentado-Armstrong, Tristan; Metzen, Michael G; Sproule, Michael K J; Chacron, Maurice J

2015-10-01

Neurons that respond selectively but in an invariant manner to a given feature of natural stimuli have been observed across species and systems. Such responses emerge in higher brain areas, thereby suggesting that they occur by integrating afferent input. However, the mechanisms by which such integration occurs are poorly understood. Here we show that midbrain electrosensory neurons can respond selectively and in an invariant manner to heterogeneity in behaviorally relevant stimulus waveforms. Such invariant responses were not seen in hindbrain electrosensory neurons providing afferent input to these midbrain neurons, suggesting that response invariance results from nonlinear integration of such input. To test this hypothesis, we built a model based on the Hodgkin-Huxley formalism that received realistic afferent input. We found that multiple combinations of parameter values could give rise to invariant responses matching those seen experimentally. Our model thus shows that there are multiple solutions towards achieving invariant responses and reveals how subthreshold membrane conductances help promote robust and invariant firing in response to heterogeneous stimulus waveforms associated with behaviorally relevant stimuli. We discuss the implications of our findings for the electrosensory and other systems.

Developing AN Emergency Response Model for Offshore Oil Spill Disaster Management Using Spatial Decision Support System (sdss)

NASA Astrophysics Data System (ADS)

Balogun, Abdul-Lateef; Matori, Abdul-Nasir; Wong Toh Kiak, Kelvin

2018-04-01

Environmental resources face severe risks during offshore oil spill disasters and Geographic Information System (GIS) Environmental Sensitivity Index (ESI) maps are increasingly being used as response tools to minimize the huge impacts of these spills. However, ESI maps are generally unable to independently harmonize the diverse preferences of the multiple stakeholders' involved in the response process, causing rancour and delay in response time. This paper's Spatial Decision Support System (SDSS) utilizes the Analytic Hierarchy Process (AHP) model to perform tradeoffs in determining the most significant resources to be secured considering the limited resources and time available to perform the response operation. The AHP approach is used to aggregate the diverse preferences of the stakeholders and reach a consensus. These preferences, represented as priority weights, are incorporated in a GIS platform to generate Environmental sensitivity risk (ESR) maps. The ESR maps provide a common operational platform and consistent situational awareness for the multiple parties involved in the emergency response operation thereby minimizing discord among the response teams and saving the most valuable resources.

Structural-Vibration-Response Data Analysis

NASA Technical Reports Server (NTRS)

Smith, W. R.; Hechenlaible, R. N.; Perez, R. C.

1983-01-01

Computer program developed as structural-vibration-response data analysis tool for use in dynamic testing of Space Shuttle. Program provides fast and efficient time-domain least-squares curve-fitting procedure for reducing transient response data to obtain structural model frequencies and dampings from free-decay records. Procedure simultaneously identifies frequencies, damping values, and participation factors for noisy multiple-response records.

Basilar-membrane interference patterns from multiple internal reflection of cochlear traveling waves.

PubMed

Shera, Christopher A; Cooper, Nigel P

2013-04-01

At low stimulus levels, basilar-membrane (BM) mechanical transfer functions in sensitive cochleae manifest a quasiperiodic rippling pattern in both amplitude and phase. Analysis of the responses of active cochlear models suggests that the rippling is a mechanical interference pattern created by multiple internal reflection within the cochlea. In models, the interference arises when reverse-traveling waves responsible for stimulus-frequency otoacoustic emissions (SFOAEs) reflect off the stapes on their way to the ear canal, launching a secondary forward-traveling wave that combines with the primary wave produced by the stimulus. Frequency-dependent phase differences between the two waves then create the rippling pattern measurable on the BM. Measurements of BM ripples and SFOAEs in individual chinchilla ears demonstrate that the ripples are strongly correlated with the acoustic interference pattern measured in ear-canal pressure, consistent with a common origin involving the generation of SFOAEs. In BM responses to clicks, the ripples appear as temporal fine structure in the response envelope (multiple lobes, waxing and waning). Analysis of the ripple spacing and response phase gradients provides a test for the role of fast- and slow-wave modes of reverse energy propagation within the cochlea. The data indicate that SFOAE delays are consistent with reverse slow-wave propagation but much too long to be explained by fast waves.

A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models

NASA Technical Reports Server (NTRS)

Giunta, Anthony A.; Watson, Layne T.

1998-01-01

Two methods of creating approximation models are compared through the calculation of the modeling accuracy on test problems involving one, five, and ten independent variables. Here, the test problems are representative of the modeling challenges typically encountered in realistic engineering optimization problems. The first approximation model is a quadratic polynomial created using the method of least squares. This type of polynomial model has seen considerable use in recent engineering optimization studies due to its computational simplicity and ease of use. However, quadratic polynomial models may be of limited accuracy when the response data to be modeled have multiple local extrema. The second approximation model employs an interpolation scheme known as kriging developed in the fields of spatial statistics and geostatistics. This class of interpolating model has the flexibility to model response data with multiple local extrema. However, this flexibility is obtained at an increase in computational expense and a decrease in ease of use. The intent of this study is to provide an initial exploration of the accuracy and modeling capabilities of these two approximation methods.

Quantifying and Generalizing Hydrologic Responses to Dam Regulation using a Statistical Modeling Approach

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

McManamay, Ryan A

2014-01-01

Despite the ubiquitous existence of dams within riverscapes, much of our knowledge about dams and their environmental effects remains context-specific. Hydrology, more than any other environmental variable, has been studied in great detail with regard to dam regulation. While much progress has been made in generalizing the hydrologic effects of regulation by large dams, many aspects of hydrology show site-specific fidelity to dam operations, small dams (including diversions), and regional hydrologic regimes. A statistical modeling framework is presented to quantify and generalize hydrologic responses to varying degrees of dam regulation. Specifically, the objectives were to 1) compare the effects ofmore » local versus cumulative dam regulation, 2) determine the importance of different regional hydrologic regimes in influencing hydrologic responses to dams, and 3) evaluate how different regulation contexts lead to error in predicting hydrologic responses to dams. Overall, model performance was poor in quantifying the magnitude of hydrologic responses, but performance was sufficient in classifying hydrologic responses as negative or positive. Responses of some hydrologic indices to dam regulation were highly dependent upon hydrologic class membership and the purpose of the dam. The opposing coefficients between local and cumulative-dam predictors suggested that hydrologic responses to cumulative dam regulation are complex, and predicting the hydrology downstream of individual dams, as opposed to multiple dams, may be more easy accomplished using statistical approaches. Results also suggested that particular contexts, including multipurpose dams, high cumulative regulation by multiple dams, diversions, close proximity to dams, and certain hydrologic classes are all sources of increased error when predicting hydrologic responses to dams. Statistical models, such as the ones presented herein, show promise in their ability to model the effects of dam regulation effects at large spatial scales as to generalize the directionality of hydrologic responses.« less

Global change and terrestrial plant community dynamics

DOE PAGES

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; ...

2016-02-29

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Global change and terrestrial plant community dynamics

PubMed Central

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; Regan, Helen M.

2016-01-01

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change. PMID:26929338

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

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Measurement of Psychological Disorders Using Cognitive Diagnosis Models

ERIC Educational Resources Information Center

Templin, Jonathan L.; Henson, Robert A.

2006-01-01

Cognitive diagnosis models are constrained (multiple classification) latent class models that characterize the relationship of questionnaire responses to a set of dichotomous latent variables. Having emanated from educational measurement, several aspects of such models seem well suited to use in psychological assessment and diagnosis. This article…

Generation of animation sequences of three dimensional models

NASA Technical Reports Server (NTRS)

Poi, Sharon (Inventor); Bell, Brad N. (Inventor)

1990-01-01

The invention is directed toward a method and apparatus for generating an animated sequence through the movement of three-dimensional graphical models. A plurality of pre-defined graphical models are stored and manipulated in response to interactive commands or by means of a pre-defined command file. The models may be combined as part of a hierarchical structure to represent physical systems without need to create a separate model which represents the combined system. System motion is simulated through the introduction of translation, rotation and scaling parameters upon a model within the system. The motion is then transmitted down through the system hierarchy of models in accordance with hierarchical definitions and joint movement limitations. The present invention also calls for a method of editing hierarchical structure in response to interactive commands or a command file such that a model may be included, deleted, copied or moved within multiple system model hierarchies. The present invention also calls for the definition of multiple viewpoints or cameras which may exist as part of a system hierarchy or as an independent camera. The simulated movement of the models and systems is graphically displayed on a monitor and a frame is recorded by means of a video controller. Multiple movement and hierarchy manipulations are then recorded as a sequence of frames which may be played back as an animation sequence on a video cassette recorder.

Modelling multiple cycles of static and dynamic recrystallisation using a fully implicit isotropic material model based on dislocation density

NASA Astrophysics Data System (ADS)

Jansen van Rensburg, Gerhardus J.; Kok, Schalk; Wilke, Daniel N.

2018-03-01

This paper presents the development and numerical implementation of a state variable based thermomechanical material model, intended for use within a fully implicit finite element formulation. Plastic hardening, thermal recovery and multiple cycles of recrystallisation can be tracked for single peak as well as multiple peak recrystallisation response. The numerical implementation of the state variable model extends on a J2 isotropic hypo-elastoplastic modelling framework. The complete numerical implementation is presented as an Abaqus UMAT and linked subroutines. Implementation is discussed with detailed explanation of the derivation and use of various sensitivities, internal state variable management and multiple recrystallisation cycle contributions. A flow chart explaining the proposed numerical implementation is provided as well as verification on the convergence of the material subroutine. The material model is characterised using two high temperature data sets for cobalt and copper. The results of finite element analyses using the material parameter values characterised on the copper data set are also presented.

Applying Multidimensional Item Response Theory Models in Validating Test Dimensionality: An Example of K-12 Large-Scale Science Assessment

ERIC Educational Resources Information Center

Li, Ying; Jiao, Hong; Lissitz, Robert W.

2012-01-01

This study investigated the application of multidimensional item response theory (IRT) models to validate test structure and dimensionality. Multiple content areas or domains within a single subject often exist in large-scale achievement tests. Such areas or domains may cause multidimensionality or local item dependence, which both violate the…

Response to Intervention (RtI) in the Social, Emotional, and Behavioral Domains: Current Challenges and Emerging Possibilities

ERIC Educational Resources Information Center

Saeki, Elina; Jimerson, Shane R.; Earhart, James; Hart, Shelley R.; Renshaw, Tyler; Singh, Renee D.; Stewart, Kaitlyn

2011-01-01

As many schools move toward a three-tier model that incorporates a Response to Intervention (RtI) service delivery model in the social, emotional, and behavioral domains, school psychologists may provide leadership. The decision-making process for filtering students through multiple tiers of support and intervention and examining change is an area…

EVALUATING VIRULENCE OF WATERBORNE AND CLINCIAL AEROMONAS ISOLATES USING GENE EXPRESSION AND MORTALITY IN NEONATAL MICE FOLLOWED BY ASSESSING CELL CULTURE'S ABILITY TO PREDICT VIRULENCE BASED ON TRANSCRIPTIONAL RESPONSE

EPA Science Inventory

The virulence of multiple Aeromonas spp. were assessed using two models, a neonatal mouse assay and a mouse intestinal cell culture. Transcriptional responses to both infection models were assessed using microarrays. After artificial infection with a variety of Aeromonas spp., ...

Study on validation method for femur finite element model under multiple loading conditions

NASA Astrophysics Data System (ADS)

Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu

2018-03-01

Acquisition of accurate and reliable constitutive parameters related to bio-tissue materials was beneficial to improve biological fidelity of a Finite Element (FE) model and predict impact damages more effectively. In this paper, a femur FE model was established under multiple loading conditions with diverse impact positions. Then, based on sequential response surface method and genetic algorithms, the material parameters identification was transformed to a multi-response optimization problem. Finally, the simulation results successfully coincided with force-displacement curves obtained by numerous experiments. Thus, computational accuracy and efficiency of the entire inverse calculation process were enhanced. This method was able to effectively reduce the computation time in the inverse process of material parameters. Meanwhile, the material parameters obtained by the proposed method achieved higher accuracy.

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

PubMed

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

2018-06-01

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

Modeling Incorrect Responses to Multiple-Choice Items with Multilinear Formula Score Theory.

ERIC Educational Resources Information Center

Drasgow, Fritz; And Others

This paper addresses the information revealed in incorrect option selection on multiple choice items. Multilinear Formula Scoring (MFS), a theory providing methods for solving psychological measurement problems of long standing, is first used to estimate option characteristic curves for the Armed Services Vocational Aptitude Battery Arithmetic…

Power Hardware-in-the-Loop Testing of Multiple Photovoltaic Inverters' Volt-Var Control with Real-Time Grid Model

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

Chakraborty, Sudipta; Nelson, Austin; Hoke, Anderson

2016-12-12

Traditional testing methods fall short in evaluating interactions between multiple smart inverters providing advanced grid support functions due to the fact that such interactions largely depend on their placements on the electric distribution systems with impedances between them. Even though significant concerns have been raised by the utilities on the effects of such interactions, little effort has been made to evaluate them. In this paper, power hardware-in-the-loop (PHIL) based testing was utilized to evaluate autonomous volt-var operations of multiple smart photovoltaic (PV) inverters connected to a simple distribution feeder model. The results provided in this paper show that depending onmore » volt-var control (VVC) parameters and grid parameters, interaction between inverters and between the inverter and the grid is possible in some extreme cases with very high VVC slopes, fast response times and large VVC response delays.« less

Thermal Response Of Composite Insulation

NASA Technical Reports Server (NTRS)

Stewart, David A.; Leiser, Daniel B.; Smith, Marnell; Kolodziej, Paul

1988-01-01

Engineering model gives useful predictions. Pair of reports presents theoretical and experimental analyses of thermal responses of multiple-component, lightweight, porous, ceramic insulators. Particular materials examined destined for use in Space Shuttle thermal protection system, test methods and heat-transfer theory useful to chemical, metallurgical, and ceramic engineers needing to calculate transient thermal responses of refractory composites.

Continuous Toxicological Dose-Response Relationships Are Pretty Homogeneous (Society for Risk Analysis Annual Meeting)

EPA Science Inventory

Dose-response relationships for a wide range of in vivo and in vitro continuous datasets are well-described by a four-parameter exponential or Hill model, based on a recent analysis of multiple historical dose-response datasets, mostly with more than five dose groups (Slob and Se...

Analytical approach for modeling and performance analysis of microring resonators as optical filters with multiple output bus waveguides

NASA Astrophysics Data System (ADS)

Lakra, Suchita; Mandal, Sanjoy

2017-06-01

A quadruple micro-optical ring resonator (QMORR) with multiple output bus waveguides is mathematically modeled and analyzed by making use of the delay-line signal processing approach in Z-domain and Mason's gain formula. The performances of QMORR with two output bus waveguides with vertical coupling are analyzed. This proposed structure is capable of providing wider free spectral response from both the output buses with appreciable cross talk. Thus, this configuration could provide increased capacity to insert a large number of communication channels. The simulated frequency response characteristic and its dispersion and group delay characteristics are graphically presented using the MATLAB environment.

Adaptive behaviour and multiple equilibrium states in a predator-prey model.

PubMed

Pimenov, Alexander; Kelly, Thomas C; Korobeinikov, Andrei; O'Callaghan, Michael J A; Rachinskii, Dmitrii

2015-05-01

There is evidence that multiple stable equilibrium states are possible in real-life ecological systems. Phenomenological mathematical models which exhibit such properties can be constructed rather straightforwardly. For instance, for a predator-prey system this result can be achieved through the use of non-monotonic functional response for the predator. However, while formal formulation of such a model is not a problem, the biological justification for such functional responses and models is usually inconclusive. In this note, we explore a conjecture that a multitude of equilibrium states can be caused by an adaptation of animal behaviour to changes of environmental conditions. In order to verify this hypothesis, we consider a simple predator-prey model, which is a straightforward extension of the classic Lotka-Volterra predator-prey model. In this model, we made an intuitively transparent assumption that the prey can change a mode of behaviour in response to the pressure of predation, choosing either "safe" of "risky" (or "business as usual") behaviour. In order to avoid a situation where one of the modes gives an absolute advantage, we introduce the concept of the "cost of a policy" into the model. A simple conceptual two-dimensional predator-prey model, which is minimal with this property, and is not relying on odd functional responses, higher dimensionality or behaviour change for the predator, exhibits two stable co-existing equilibrium states with basins of attraction separated by a separatrix of a saddle point. Copyright © 2015 Elsevier Inc. All rights reserved.

Multiple-Shrinkage Multinomial Probit Models with Applications to Simulating Geographies in Public Use Data.

PubMed

Burgette, Lane F; Reiter, Jerome P

2013-06-01

Multinomial outcomes with many levels can be challenging to model. Information typically accrues slowly with increasing sample size, yet the parameter space expands rapidly with additional covariates. Shrinking all regression parameters towards zero, as often done in models of continuous or binary response variables, is unsatisfactory, since setting parameters equal to zero in multinomial models does not necessarily imply "no effect." We propose an approach to modeling multinomial outcomes with many levels based on a Bayesian multinomial probit (MNP) model and a multiple shrinkage prior distribution for the regression parameters. The prior distribution encourages the MNP regression parameters to shrink toward a number of learned locations, thereby substantially reducing the dimension of the parameter space. Using simulated data, we compare the predictive performance of this model against two other recently-proposed methods for big multinomial models. The results suggest that the fully Bayesian, multiple shrinkage approach can outperform these other methods. We apply the multiple shrinkage MNP to simulating replacement values for areal identifiers, e.g., census tract indicators, in order to protect data confidentiality in public use datasets.

Computer modeling of fan-exit-splitter spacing effects on F100 response to distortion

NASA Technical Reports Server (NTRS)

Shaw, M.; Murdoch, R. W.

1982-01-01

The distortion response of the F100(3) engine was effected by the fan exit splitter configuration. The sensitivity for a proximate splitter fan is calculated to be slightly greater than a remote splitter configuration with identical airfoils. Predicted response was based upon a multiple segment parallel compressor Model modified to include a bypass ratio representation that effects the performance characteristics of the last rotor and intermediate case struts. The predicted distortion response required an accurate definition of row pre- and post-stall undistorted operation.

Maximum Marginal Likelihood Estimation of a Monotonic Polynomial Generalized Partial Credit Model with Applications to Multiple Group Analysis.

PubMed

Falk, Carl F; Cai, Li

2016-06-01

We present a semi-parametric approach to estimating item response functions (IRF) useful when the true IRF does not strictly follow commonly used functions. Our approach replaces the linear predictor of the generalized partial credit model with a monotonic polynomial. The model includes the regular generalized partial credit model at the lowest order polynomial. Our approach extends Liang's (A semi-parametric approach to estimate IRFs, Unpublished doctoral dissertation, 2007) method for dichotomous item responses to the case of polytomous data. Furthermore, item parameter estimation is implemented with maximum marginal likelihood using the Bock-Aitkin EM algorithm, thereby facilitating multiple group analyses useful in operational settings. Our approach is demonstrated on both educational and psychological data. We present simulation results comparing our approach to more standard IRF estimation approaches and other non-parametric and semi-parametric alternatives.

An efficient approach to ARMA modeling of biological systems with multiple inputs and delays

NASA Technical Reports Server (NTRS)

Perrott, M. H.; Cohen, R. J.

1996-01-01

This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.

Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

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

Moges, Edom; Demissie, Yonas; Li, Hong-Yi

2016-04-01

In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integratemore » expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.« less

Do microbial processes regulate the stability of a coral atoll's enclosed pelagic ecosystem?

EPA Science Inventory

Complex marine ecosystems contain multiple feedback cycles that can cause unexpected responses to perturbations. To better predict these responses, complicated models are increasingly being developed to enable the study of feedback cycles. However, the sparseness of ecological da...

A multiple pointing-mount control strategy for space platforms

NASA Technical Reports Server (NTRS)

Johnson, C. D.

1992-01-01

A new disturbance-adaptive control strategy for multiple pointing-mount space platforms is proposed and illustrated by consideration of a simplified 3-link dynamic model of a multiple pointing-mount space platform. Simulation results demonstrate the effectiveness of the new platform control strategy. The simulation results also reveal a system 'destabilization phenomena' that can occur if the set of individual platform-mounted experiment controllers are 'too responsive.'

Wafer hotspot prevention using etch aware OPC correction

NASA Astrophysics Data System (ADS)

Hamouda, Ayman; Power, Dave; Salama, Mohamed; Chen, Ao

2016-03-01

As technology development advances into deep-sub-wavelength nodes, multiple patterning is becoming more essential to achieve the technology shrink requirements. Recently, Optical Proximity Correction (OPC) technology has proposed simultaneous correction of multiple mask-patterns to enable multiple patterning awareness during OPC correction. This is essential to prevent inter-layer hot-spots during the final pattern transfer. In state-of-art literature, multi-layer awareness is achieved using simultaneous resist-contour simulations to predict and correct for hot-spots during mask generation. However, this approach assumes a uniform etch shrink response for all patterns independent of their proximity, which isn't sufficient for the full prevention of inter-exposure hot-spot, for example different color space violations post etch or via coverage/enclosure post etch. In this paper, we explain the need to include the etch component during multiple patterning OPC. We also introduce a novel approach for Etch-aware simultaneous Multiple-patterning OPC, where we calibrate and verify a lumped model that includes the combined resist and etch responses. Adding this extra simulation condition during OPC is suitable for full chip processing from a computation intensity point of view. Also, using this model during OPC to predict and correct inter-exposures hot-spots is similar to previously proposed multiple-patterning OPC, yet our proposed approach more accurately corrects post-etch defects too.

The Climate Response to Stratospheric Aerosol Geoengineering Can Be Tailored Using Multiple Injection Locations

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

MacMartin, Douglas G.; Kravitz, Ben; Tilmes, Simone

The climate response to geoengineering with stratospheric aerosols has the potential to be designed to achieve some chosen objectives. By injecting different amounts of SO2 at multiple different latitudes, the spatial pattern of aerosol optical depth (AOD) can be partially controlled. We use simulations from the fully-coupled whole-atmosphere chemistry-climate model CESM1(WACCM), to demonstrate that three spatial degrees of freedom of AOD can be achieved by appropriately combining injection at different locations: an approximately spatially-uniform AOD distribution, the relative difference in AOD between Northern and Southern hemispheres, and the relative AOD in high versus low latitudes. For forcing levels that yieldmore » 1–2°C cooling, the AOD and surface temperature response are sufficiently linear in this model so that many climate effects can be predicted from single-latitude injection simulations. Optimized injection at multiple locations is predicted to improve compensation of CO2-forced climate change, relative to a case using only equatorial aerosol injection. The additional degrees of freedom can be used, for example, to balance interhemispheric temperature differences and the equator to pole temperature difference in addition to the global mean temperature; this is projected in this model to reduce the mean-square error in temperature compensation by 30%.« less

Statistical methods for incomplete data: Some results on model misspecification.

PubMed

McIsaac, Michael; Cook, R J

2017-02-01

Inverse probability weighted estimating equations and multiple imputation are two of the most studied frameworks for dealing with incomplete data in clinical and epidemiological research. We examine the limiting behaviour of estimators arising from inverse probability weighted estimating equations, augmented inverse probability weighted estimating equations and multiple imputation when the requisite auxiliary models are misspecified. We compute limiting values for settings involving binary responses and covariates and illustrate the effects of model misspecification using simulations based on data from a breast cancer clinical trial. We demonstrate that, even when both auxiliary models are misspecified, the asymptotic biases of double-robust augmented inverse probability weighted estimators are often smaller than the asymptotic biases of estimators arising from complete-case analyses, inverse probability weighting or multiple imputation. We further demonstrate that use of inverse probability weighting or multiple imputation with slightly misspecified auxiliary models can actually result in greater asymptotic bias than the use of naïve, complete case analyses. These asymptotic results are shown to be consistent with empirical results from simulation studies.

A Combined IRT and SEM Approach for Individual-Level Assessment in Test-Retest Studies

ERIC Educational Resources Information Center

Ferrando, Pere J.

2015-01-01

The standard two-wave multiple-indicator model (2WMIM) commonly used to analyze test-retest data provides information at both the group and item level. Furthermore, when applied to binary and graded item responses, it is related to well-known item response theory (IRT) models. In this article the IRT-2WMIM relations are used to obtain additional…

A Framework for Linking Population Model Development with Ecological Risk Assessment Objectives.

EPA Science Inventory

The value of models that link organism‐level impacts to the responses of a population in ecological risk assessments (ERAs) has been demonstrated extensively over the past few decades. There is little debate about the utility of these models to translate multiple organism&#...

Pavlovian conditioning of multiple opioid-like responses in mice.

PubMed

Bryant, Camron D; Roberts, Kristofer W; Culbertson, Christopher S; Le, Alan; Evans, Christopher J; Fanselow, Michael S

2009-07-01

Conditional responses in rodents such as locomotion have been reported for drugs of abuse and similar to the placebo response in humans, may be associated with the expectation of reward. We examined several conditional opioid-like responses and the influence of drug expectation on conditioned place preference and concomitant conditional locomotion. Male C57BL/6J mice were conditioned with the selective mu opioid receptor agonist fentanyl (0.2mg/kg, i.p.) in a novel context and subsequently given a vehicle injection. In separate experiments, locomotor activity, Straub tail, hot plate sensitivity, and conditioned place preference (CPP) were measured. Mice exhibited multiple conditional opioid-like responses including conditional hyperlocomotion, a conditional pattern of opioid-like locomotion, Straub tail, analgesia, and place preference. Modulating drug expectation via administration of fentanyl to "demonstrator" mice in the home cage did not affect the expression of conditioned place preference or the concomitant locomotor activity in "observer" mice. In summary, Pavlovian conditioning of an opioid in a novel context induced multiple conditional opioid-like behaviors and provides a model for studying the neurobiological mechanisms of the placebo response in mice.

Diagnostic Opportunities Using Rasch Measurement in the Context of a Misconceptions-Based Physical Science Assessment

ERIC Educational Resources Information Center

Wind, Stefanie A.; Gale, Jessica D.

2015-01-01

Multiple-choice (MC) items that are constructed such that distractors target known misconceptions for a particular domain provide useful diagnostic information about student misconceptions (Herrmann-Abell & DeBoer, 2011, 2014; Sadler, 1998). Item response theory models can be used to examine misconceptions distractor-driven multiple-choice…

A Multidimensional Scaling Approach to Dimensionality Assessment for Measurement Instruments Modeled by Multidimensional Item Response Theory

ERIC Educational Resources Information Center

Toro, Maritsa

2011-01-01

The statistical assessment of dimensionality provides evidence of the underlying constructs measured by a survey or test instrument. This study focuses on educational measurement, specifically tests comprised of items described as multidimensional. That is, items that require examinee proficiency in multiple content areas and/or multiple cognitive…

Modelling DC responses of 3D complex fracture networks

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

Beskardes, Gungor Didem; Weiss, Chester Joseph

Here, the determination of the geometrical properties of fractures plays a critical role in many engineering problems to assess the current hydrological and mechanical states of geological media and to predict their future states. However, numerical modeling of geoelectrical responses in realistic fractured media has been challenging due to the explosive computational cost imposed by the explicit discretizations of fractures at multiple length scales, which often brings about a tradeoff between computational efficiency and geologic realism. Here, we use the hierarchical finite element method to model electrostatic response of realistically complex 3D conductive fracture networks with minimal computational cost.

Modelling DC responses of 3D complex fracture networks

DOE PAGES

Beskardes, Gungor Didem; Weiss, Chester Joseph

2018-03-01

Here, the determination of the geometrical properties of fractures plays a critical role in many engineering problems to assess the current hydrological and mechanical states of geological media and to predict their future states. However, numerical modeling of geoelectrical responses in realistic fractured media has been challenging due to the explosive computational cost imposed by the explicit discretizations of fractures at multiple length scales, which often brings about a tradeoff between computational efficiency and geologic realism. Here, we use the hierarchical finite element method to model electrostatic response of realistically complex 3D conductive fracture networks with minimal computational cost.

Immunopathological Patterns from EAE and Theiler’s Virus Infection: Is Multiple Sclerosis a Homogenous 1-stage or Heterogenous 2-stage Disease?

PubMed Central

Martinez, Nicholas E.; Sato, Fumitaka; Omura, Seiichi; Minagar, Alireza; Alexander, J. Steven; Tsunoda, Ikuo

2012-01-01

Multiple sclerosis (MS) is a disease which can present in different clinical courses. The most common form of MS is the relapsing-remitting (RR) course, which in many cases evolves into secondary progressive (SP) disease. Autoimmune models such as experimental autoimmune encephalomyelitis (EAE) have been developed to represent the various clinical forms of MS. These models along with clinico-pathological evidence obtained from MS patients have allowed us to propose ‘1-stage’ and ‘2-stage’ disease theories to explain the transition in the clinical course of MS from RR to SP. Relapses in MS are associated with pro-inflammatory T helper (Th) 1/Th17 immune responses, while remissions are associated with anti-inflammatory Th2/regulatory T (Treg) immune responses. Based on the ‘1-stage disease’ theory, the transition from RR to SP disease occurs when the inflammatory immune response overwhelms the anti-inflammatory immune response. The ‘2-stage disease’ theory proposes that the transition from RR to SP-MS occurs when the Th2 response or some other responses overwhelm the inflammatory response resulting in the sustained production of anti-myelin antibodies, which cause continuing demyelination, neurodegeneration, and axonal loss. The Theiler’s virus model is also a 2-stage disease, where axonal degeneration precedes demyelination during the first stage, followed by inflammatory demyelination during the second stage. PMID:22633747

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Do large-scale assessments measure students' ability to integrate scientific knowledge?

NASA Astrophysics Data System (ADS)

Lee, Hee-Sun

2010-03-01

Large-scale assessments are used as means to diagnose the current status of student achievement in science and compare students across schools, states, and countries. For efficiency, multiple-choice items and dichotomously-scored open-ended items are pervasively used in large-scale assessments such as Trends in International Math and Science Study (TIMSS). This study investigated how well these items measure secondary school students' ability to integrate scientific knowledge. This study collected responses of 8400 students to 116 multiple-choice and 84 open-ended items and applied an Item Response Theory analysis based on the Rasch Partial Credit Model. Results indicate that most multiple-choice items and dichotomously-scored open-ended items can be used to determine whether students have normative ideas about science topics, but cannot measure whether students integrate multiple pieces of relevant science ideas. Only when the scoring rubric is redesigned to capture subtle nuances of student open-ended responses, open-ended items become a valid and reliable tool to assess students' knowledge integration ability.

A frequency domain global parameter estimation method for multiple reference frequency response measurements

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

A method of using the matrix Auto-Regressive Moving Average (ARMA) model in the Laplace domain for multiple-reference global parameter identification is presented. This method is particularly applicable to the area of modal analysis where high modal density exists. The method is also applicable when multiple reference frequency response functions are used to characterise linear systems. In order to facilitate the mathematical solution, the Forsythe orthogonal polynomial is used to reduce the ill-conditioning of the formulated equations and to decouple the normal matrix into two reduced matrix blocks. A Complex Mode Indicator Function (CMIF) is introduced, which can be used to determine the proper order of the rational polynomials.

Multiple piezo-patch energy harvesters integrated to a thin plate with AC-DC conversion: analytical modeling and numerical validation

NASA Astrophysics Data System (ADS)

Aghakhani, Amirreza; Basdogan, Ipek; Erturk, Alper

2016-04-01

Plate-like components are widely used in numerous automotive, marine, and aerospace applications where they can be employed as host structures for vibration based energy harvesting. Piezoelectric patch harvesters can be easily attached to these structures to convert the vibrational energy to the electrical energy. Power output investigations of these harvesters require accurate models for energy harvesting performance evaluation and optimization. Equivalent circuit modeling of the cantilever-based vibration energy harvesters for estimation of electrical response has been proposed in recent years. However, equivalent circuit formulation and analytical modeling of multiple piezo-patch energy harvesters integrated to thin plates including nonlinear circuits has not been studied. In this study, equivalent circuit model of multiple parallel piezoelectric patch harvesters together with a resistive load is built in electronic circuit simulation software SPICE and voltage frequency response functions (FRFs) are validated using the analytical distributedparameter model. Analytical formulation of the piezoelectric patches in parallel configuration for the DC voltage output is derived while the patches are connected to a standard AC-DC circuit. The analytic model is based on the equivalent load impedance approach for piezoelectric capacitance and AC-DC circuit elements. The analytic results are validated numerically via SPICE simulations. Finally, DC power outputs of the harvesters are computed and compared with the peak power amplitudes in the AC output case.

Characteristics pertaining to a stiffness cross-coupled Jeffcott model

NASA Technical Reports Server (NTRS)

Spanyer, K. L.

1985-01-01

Rotordynamic studies of complex systems utilizing multiple degree-of-freedom analysis have been performed to understand response, loads, and stability. In order to understand the fundamental nature of rotordynamic response, the Jeffcott rotor model has received wide attention. The purpose of this paper is to provide a generic rotordynamic analysis of a stiffness cross-coupled Jeffcott rotor model to illustrate characteristics of a second order stiffness-coupled linear system. The particular characteristics investigated were forced response, force vector diagrams, response orbits, and stability. Numerical results were achieved through a fourth order Runge-Kutta method for solving differential equations and the Routh Hurwitz stability criterion. The numerical results were verified to an exact mathematical solution for the steady state response.

The source of dual-task limitations: Serial or parallel processing of multiple response selections?

PubMed Central

Marois, René

2014-01-01

Although it is generally recognized that the concurrent performance of two tasks incurs costs, the sources of these dual-task costs remain controversial. The serial bottleneck model suggests that serial postponement of task performance in dual-task conditions results from a central stage of response selection that can only process one task at a time. Cognitive-control models, by contrast, propose that multiple response selections can proceed in parallel, but that serial processing of task performance is predominantly adopted because its processing efficiency is higher than that of parallel processing. In the present study, we empirically tested this proposition by examining whether parallel processing would occur when it was more efficient and financially rewarded. The results indicated that even when parallel processing was more efficient and was incentivized by financial reward, participants still failed to process tasks in parallel. We conclude that central information processing is limited by a serial bottleneck. PMID:23864266

On the nonlinear dynamics of trolling-mode AFM: Analytical solution using multiple time scales method

NASA Astrophysics Data System (ADS)

Sajjadi, Mohammadreza; Pishkenari, Hossein Nejat; Vossoughi, Gholamreza

2018-06-01

Trolling mode atomic force microscopy (TR-AFM) has resolved many imaging problems by a considerable reduction of the liquid-resonator interaction forces in liquid environments. The present study develops a nonlinear model of the meniscus force exerted to the nanoneedle of TR-AFM and presents an analytical solution to the distributed-parameter model of TR-AFM resonator utilizing multiple time scales (MTS) method. Based on the developed analytical solution, the frequency-response curves of the resonator operation in air and liquid (for different penetration length of the nanoneedle) are obtained. The closed-form analytical solution and the frequency-response curves are validated by the comparison with both the finite element solution of the main partial differential equations and the experimental observations. The effect of excitation angle of the resonator on horizontal oscillation of the probe tip and the effect of different parameters on the frequency-response of the system are investigated.

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

Online Testing: The Dog Sat on My Keyboard.

ERIC Educational Resources Information Center

White, Jacci

This paper will highlight some advantages and disadvantages of several online models for student assessment. These models will include: live exams, multiple choice tests, essay exams, and student projects. In addition, real student responses and "problems" will be used as prompts to improve models of authentic online assessment in mathematics.…

A Framework for Linking Population Model Development with Ecological Risk Assessment Objectives

EPA Science Inventory

The value of models that link organism-level impacts to the responses of a population in ecological risk assessments (ERA) has been demonstrated extensively over the past few decades. There is little debate about the utility of these models to translate multiple organism-level en...

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

BAYESIAN METHODS FOR REGIONAL-SCALE EUTROPHICATION MODELS. (R830887)

EPA Science Inventory

We demonstrate a Bayesian classification and regression tree (CART) approach to link multiple environmental stressors to biological responses and quantify uncertainty in model predictions. Such an approach can: (1) report prediction uncertainty, (2) be consistent with the amou...

Empirical Bayes Approaches to Multivariate Fuzzy Partitions.

ERIC Educational Resources Information Center

Woodbury, Max A.; Manton, Kenneth G.

1991-01-01

An empirical Bayes-maximum likelihood estimation procedure is presented for the application of fuzzy partition models in describing high dimensional discrete response data. The model describes individuals in terms of partial membership in multiple latent categories that represent bounded discrete spaces. (SLD)

Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1

PubMed Central

Ryu, Stephen I.; Shenoy, Krishna V.; Cunningham, John P.; Churchland, Mark M.

2016-01-01

Cortical firing rates frequently display elaborate and heterogeneous temporal structure. One often wishes to compute quantitative summaries of such structure—a basic example is the frequency spectrum—and compare with model-based predictions. The advent of large-scale population recordings affords the opportunity to do so in new ways, with the hope of distinguishing between potential explanations for why responses vary with time. We introduce a method that assesses a basic but previously unexplored form of population-level structure: when data contain responses across multiple neurons, conditions, and times, they are naturally expressed as a third-order tensor. We examined tensor structure for multiple datasets from primary visual cortex (V1) and primary motor cortex (M1). All V1 datasets were ‘simplest’ (there were relatively few degrees of freedom) along the neuron mode, while all M1 datasets were simplest along the condition mode. These differences could not be inferred from surface-level response features. Formal considerations suggest why tensor structure might differ across modes. For idealized linear models, structure is simplest across the neuron mode when responses reflect external variables, and simplest across the condition mode when responses reflect population dynamics. This same pattern was present for existing models that seek to explain motor cortex responses. Critically, only dynamical models displayed tensor structure that agreed with the empirical M1 data. These results illustrate that tensor structure is a basic feature of the data. For M1 the tensor structure was compatible with only a subset of existing models. PMID:27814353

Nonlinear computations shaping temporal processing of precortical vision.

PubMed

Butts, Daniel A; Cui, Yuwei; Casti, Alexander R R

2016-09-01

Computations performed by the visual pathway are constructed by neural circuits distributed over multiple stages of processing, and thus it is challenging to determine how different stages contribute on the basis of recordings from single areas. In the current article, we address this problem in the lateral geniculate nucleus (LGN), using experiments combined with nonlinear modeling capable of isolating various circuit contributions. We recorded cat LGN neurons presented with temporally modulated spots of various sizes, which drove temporally precise LGN responses. We utilized simultaneously recorded S-potentials, corresponding to the primary retinal ganglion cell (RGC) input to each LGN cell, to distinguish the computations underlying temporal precision in the retina from those in the LGN. Nonlinear models with excitatory and delayed suppressive terms were sufficient to explain temporal precision in the LGN, and we found that models of the S-potentials were nearly identical, although with a lower threshold. To determine whether additional influences shaped the response at the level of the LGN, we extended this model to use the S-potential input in combination with stimulus-driven terms to predict the LGN response. We found that the S-potential input "explained away" the major excitatory and delayed suppressive terms responsible for temporal patterning of LGN spike trains but revealed additional contributions, largely PULL suppression, to the LGN response. Using this novel combination of recordings and modeling, we were thus able to dissect multiple circuit contributions to LGN temporal responses across retina and LGN, and set the foundation for targeted study of each stage. Copyright © 2016 the American Physiological Society.

An adaptive two-stage dose-response design method for establishing proof of concept.

PubMed

Franchetti, Yoko; Anderson, Stewart J; Sampson, Allan R

2013-01-01

We propose an adaptive two-stage dose-response design where a prespecified adaptation rule is used to add and/or drop treatment arms between the stages. We extend the multiple comparison procedures-modeling (MCP-Mod) approach into a two-stage design. In each stage, we use the same set of candidate dose-response models and test for a dose-response relationship or proof of concept (PoC) via model-associated statistics. The stage-wise test results are then combined to establish "global" PoC using a conditional error function. Our simulation studies showed good and more robust power in our design method compared to conventional and fixed designs.

Quantitative Models for Ecosystem Assessment in Narragansett Bay: Response to Nutrient Loading and Other Stressors

EPA Science Inventory

Multiple drivers, including nutrient loading and climate change, affect the Narragansett Bay ecosystem. Managers are interested in understanding the timing and magnitude of these effects, as well as ecosystem responses to restoration actions, such as the capacity and potential fo...

Towards personalized therapy for multiple sclerosis: prediction of individual treatment response.

PubMed

Kalincik, Tomas; Manouchehrinia, Ali; Sobisek, Lukas; Jokubaitis, Vilija; Spelman, Tim; Horakova, Dana; Havrdova, Eva; Trojano, Maria; Izquierdo, Guillermo; Lugaresi, Alessandra; Girard, Marc; Prat, Alexandre; Duquette, Pierre; Grammond, Pierre; Sola, Patrizia; Hupperts, Raymond; Grand'Maison, Francois; Pucci, Eugenio; Boz, Cavit; Alroughani, Raed; Van Pesch, Vincent; Lechner-Scott, Jeannette; Terzi, Murat; Bergamaschi, Roberto; Iuliano, Gerardo; Granella, Franco; Spitaleri, Daniele; Shaygannejad, Vahid; Oreja-Guevara, Celia; Slee, Mark; Ampapa, Radek; Verheul, Freek; McCombe, Pamela; Olascoaga, Javier; Amato, Maria Pia; Vucic, Steve; Hodgkinson, Suzanne; Ramo-Tello, Cristina; Flechter, Shlomo; Cristiano, Edgardo; Rozsa, Csilla; Moore, Fraser; Luis Sanchez-Menoyo, Jose; Laura Saladino, Maria; Barnett, Michael; Hillert, Jan; Butzkueven, Helmut

2017-09-01

Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of disability regression was predominantly associated with pre-baseline disability, therapy and relapse activity. Relapse incidence was associated with pretreatment relapse activity, age and relapsing disease course, with the strength of these associations varying among therapies. Accuracy and internal validity (n = 1196) of the resulting predictive models was high (>80%) for relapse incidence during the first year and for disability outcomes, moderate for relapse incidence in Years 2-4 and for the change in the cumulative disease burden, and low for conversion to secondary progressive disease and treatment discontinuation. External validation showed similar results, demonstrating high external validity for disability and relapse outcomes, moderate external validity for cumulative disease burden and low external validity for conversion to secondary progressive disease and treatment discontinuation. We conclude that demographic, clinical and paraclinical information helps predict individual response to disease-modifying therapies at the time of their commencement. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Adjudicating between face-coding models with individual-face fMRI responses

PubMed Central

Kriegeskorte, Nikolaus

2017-01-01

The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging. PMID:28746335

Anti-inflammatory and analgesic activity of novel oral aspirin-loaded nanoemulsion and nano multiple emulsion formulations generated using ultrasound cavitation.

PubMed

Tang, Siah Ying; Sivakumar, Manickam; Ng, Angela Min-Hwei; Shridharan, Parthasarathy

2012-07-01

The present study investigated the anti-inflammatory and analgesic activities of novel aspirin oil-in-water (O/W) nanoemulsion and water-in-oil-in-water (W/O/W) nano multiple emulsion formulations generated using ultrasound cavitation techniques. The anti-inflammatory activities of nanoemulsion and nano multiple emulsion were determined using the λ-carrageenan-induced paw edema model. The analgesic activities of both nanoformulations were determined using acetic acid-induced writhing response and hot plate assay. For comparison, the effect of pretreatment with blank nanoemulsion and reference aspirin suspension were also studied for their anti-inflammatory and antinociceptive activities. The results showed that oral administration of nanoemulsion and nano multiple emulsion containing aspirin (60 mg/kg) significantly reduced paw edema induced by λ-carrageenan injection. Both nanoformulations decreased the number of abdominal constriction in acetic acid-induced writhing model. Pretreatment with nanoformulations led to a significant increase in reaction time in hot plate assay. Nanoemulsion demonstrated an enhanced anti-inflammatory and analgesic effects compared to reference suspension while nano multiple emulsion exhibited a mild inhibitory effects in the three experimental animal model tests. The results obtained for nano multiple emulsion were relatively lower than reference. However, administration of blank nanoemulsion did not alter the nociceptive response significantly though it showed slight anti-inflammatory effect. These experimental studies suggest that nanoemulsion and nano multiple emulsion produced a pronounced anti-inflammatory and analgesic effects in rats and may be candidates as new nanocarriers for pharmacological NSAIDs in the treatment of inflammatory disorders and alleviating pains. Copyright © 2012 Elsevier B.V. All rights reserved.

Using FUN3D for Aeroelastic, Sonic Boom, and AeroPropulsoServoElastic (APSE) Analyses of a Supersonic Configuration

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Sanetrik, Mark D.; Chwalowski, Pawel; Connolly, Joseph; Kopasakis, George

2016-01-01

An overview of recent applications of the FUN3D CFD code to computational aeroelastic, sonic boom, and aeropropulsoservoelasticity (APSE) analyses of a low-boom supersonic configuration is presented. The overview includes details of the computational models developed including multiple unstructured CFD grids suitable for aeroelastic and sonic boom analyses. In addition, aeroelastic Reduced-Order Models (ROMs) are generated and used to rapidly compute the aeroelastic response and utter boundaries at multiple flight conditions.

Proof of concept and dose estimation with binary responses under model uncertainty.

PubMed

Klingenberg, B

2009-01-30

This article suggests a unified framework for testing Proof of Concept (PoC) and estimating a target dose for the benefit of a more comprehensive, robust and powerful analysis in phase II or similar clinical trials. From a pre-specified set of candidate models, we choose the ones that best describe the observed dose-response. To decide which models, if any, significantly pick up a dose effect, we construct the permutation distribution of the minimum P-value over the candidate set. This allows us to find critical values and multiplicity adjusted P-values that control the familywise error rate of declaring any spurious effect in the candidate set as significant. Model averaging is then used to estimate a target dose. Popular single or multiple contrast tests for PoC, such as the Cochran-Armitage, Dunnett or Williams tests, are only optimal for specific dose-response shapes and do not provide target dose estimates with confidence limits. A thorough evaluation and comparison of our approach to these tests reveal that its power is as good or better in detecting a dose-response under various shapes with many more additional benefits: It incorporates model uncertainty in PoC decisions and target dose estimation, yields confidence intervals for target dose estimates and extends to more complicated data structures. We illustrate our method with the analysis of a Phase II clinical trial. Copyright (c) 2008 John Wiley & Sons, Ltd.

Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

PubMed

Patel, Kevin R; Tobyne, Sean; Porter, Daria; Bireley, John Daniel; Smith, Victoria; Klawiter, Eric

2018-06-01

Increased synchrony within neuroanatomical networks is often observed in neurophysiologic studies of human brain disease. Most often, this phenomenon is ascribed to a compensatory process in the face of injury, though evidence supporting such accounts is limited. Given the known dependence of resting-state functional connectivity (rsFC) on underlying structural connectivity (SC), we examine an alternative hypothesis: that topographical changes in SC, specifically particular patterns of disconnection, contribute to increased network rsFC. We obtain measures of rsFC using fMRI and SC using probabilistic tractography in 50 healthy and 28 multiple sclerosis subjects. Using a computational model of neuronal dynamics, we simulate BOLD using healthy subject SC to couple regions. We find that altering the model by introducing structural disconnection patterns observed in those multiple sclerosis subjects with high network rsFC generates simulations with high rsFC as well, suggesting that disconnection itself plays a role in producing high network functional connectivity. We then examine SC data in individuals. In multiple sclerosis subjects with high network rsFC, we find a preferential disconnection between the relevant network and wider system. We examine the significance of such network isolation by introducing random disconnection into the model. As observed empirically, simulated network rsFC increases with removal of connections bridging a community with the remainder of the brain. We thus show that structural disconnection known to occur in multiple sclerosis contributes to network rsFC changes in multiple sclerosis and further that community isolation is responsible for elevated network functional connectivity.

Thyroid cancer following scalp irradiation: a reanalysis accounting for uncertainty in dosimetry.

PubMed

Schafer, D W; Lubin, J H; Ron, E; Stovall, M; Carroll, R J

2001-09-01

In the 1940s and 1950s, over 20,000 children in Israel were treated for tinea capitis (scalp ringworm) by irradiation to induce epilation. Follow-up studies showed that the radiation exposure was associated with the development of malignant thyroid neoplasms. Despite this clear evidence of an effect, the magnitude of the dose-response relationship is much less clear because of probable errors in individual estimates of dose to the thyroid gland. Such errors have the potential to bias dose-response estimation, a potential that was not widely appreciated at the time of the original analyses. We revisit this issue, describing in detail how errors in dosimetry might occur, and we develop a new dose-response model that takes the uncertainties of the dosimetry into account. Our model for the uncertainty in dosimetry is a complex and new variant of the classical multiplicative Berkson error model, having components of classical multiplicative measurement error as well as missing data. Analysis of the tinea capitis data suggests that measurement error in the dosimetry has only a negligible effect on dose-response estimation and inference as well as on the modifying effect of age at exposure.

Analyzing multicomponent receptive fields from neural responses to natural stimuli

PubMed Central

Rowekamp, Ryan; Sharpee, Tatyana O

2011-01-01

The challenge of building increasingly better models of neural responses to natural stimuli is to accurately estimate the multiple stimulus features that may jointly affect the neural spike probability. The selectivity for combinations of features is thought to be crucial for achieving classical properties of neural responses such as contrast invariance. The joint search for these multiple stimulus features is difficult because estimating spike probability as a multidimensional function of stimulus projections onto candidate relevant dimensions is subject to the curse of dimensionality. An attractive alternative is to search for relevant dimensions sequentially, as in projection pursuit regression. Here we demonstrate using analytic arguments and simulations of model cells that different types of sequential search strategies exhibit systematic biases when used with natural stimuli. Simulations show that joint optimization is feasible for up to three dimensions with current algorithms. When applied to the responses of V1 neurons to natural scenes, models based on three jointly optimized dimensions had better predictive power in a majority of cases compared to dimensions optimized sequentially, with different sequential methods yielding comparable results. Thus, although the curse of dimensionality remains, at least several relevant dimensions can be estimated by joint information maximization. PMID:21780916

Multiple Vaccinations: Friend or Foe

PubMed Central

Church, Sarah E.; Jensen, Shawn M.; Twitty, Chris; Bahjat, Keith; Hu, Hong-Ming; Urba, Walter J.; Fox, Bernard A.

2013-01-01

Few immunotherapists would accept the concept of a single vaccination inducing a therapeutic anti-cancer immune response in a patient with advanced cancer. But what is the evidence to support the “more-is-better” approach of multiple vaccinations? Since we are unaware of trials comparing the effect of a single vaccine versus multiple vaccinations on patient outcome, we considered that an anti-cancer immune response might provide a surrogate measure of the effectiveness of vaccination strategies. Since few large trials include immunological monitoring, the majority of information is gleaned from smaller trials in which an evaluation of immune responses to vaccine or tumor, before and at one or more times following the first vaccine was performed. In some studies there is convincing evidence that repeated administration of a specific vaccine can augment the immune response to antigens contained in the vaccine. In other settings multiple vaccinations can significantly reduce the immune response to one or more targets. Results from three large adjuvant vaccine studies support the potential detrimental effect of multiple vaccinations as clinical outcomes in the control arms were significantly better than that for treatment groups. Recent research has provided insights into mechanisms that are likely responsible for the reduced responses in the studies noted above, but supporting evidence from clinical specimens is generally lacking. Interpretation of these results is further complicated by the possibility that the dominant immune response may evolve to recognize epitopes not present in the vaccine. Nonetheless, the FDA-approval of the first therapeutic cancer vaccine and recent developments from preclinical models and clinical trials provide a substantial basis for optimism and a critical evaluation of cancer vaccine strategies. PMID:21952289

Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture

NASA Astrophysics Data System (ADS)

Sierra, Carlos A.; Trumbore, Susan E.; Davidson, Eric A.; Vicca, Sara; Janssens, I.

2015-03-01

The sensitivity of soil organic matter decomposition to global environmental change is a topic of prominent relevance for the global carbon cycle. Decomposition depends on multiple factors that are being altered simultaneously as a result of global environmental change; therefore, it is important to study the sensitivity of the rates of soil organic matter decomposition with respect to multiple and interacting drivers. In this manuscript, we present an analysis of the potential response of decomposition rates to simultaneous changes in temperature and moisture. To address this problem, we first present a theoretical framework to study the sensitivity of soil organic matter decomposition when multiple driving factors change simultaneously. We then apply this framework to models and data at different levels of abstraction: (1) to a mechanistic model that addresses the limitation of enzyme activity by simultaneous effects of temperature and soil water content, the latter controlling substrate supply and oxygen concentration for microbial activity; (2) to different mathematical functions used to represent temperature and moisture effects on decomposition in biogeochemical models. To contrast model predictions at these two levels of organization, we compiled different data sets of observed responses in field and laboratory studies. Then we applied our conceptual framework to: (3) observations of heterotrophic respiration at the ecosystem level; (4) laboratory experiments looking at the response of heterotrophic respiration to independent changes in moisture and temperature; and (5) ecosystem-level experiments manipulating soil temperature and water content simultaneously.

Multiple Cognitive Control Effects of Error Likelihood and Conflict

PubMed Central

Brown, Joshua W.

2010-01-01

Recent work on cognitive control has suggested a variety of performance monitoring functions of the anterior cingulate cortex, such as errors, conflict, error likelihood, and others. Given the variety of monitoring effects, a corresponding variety of control effects on behavior might be expected. This paper explores whether conflict and error likelihood produce distinct cognitive control effects on behavior, as measured by response time. A change signal task (Brown & Braver, 2005) was modified to include conditions of likely errors due to tardy as well as premature responses, in conditions with and without conflict. The results discriminate between competing hypotheses of independent vs. interacting conflict and error likelihood control effects. Specifically, the results suggest that the likelihood of premature vs. tardy response errors can lead to multiple distinct control effects, which are independent of cognitive control effects driven by response conflict. As a whole, the results point to the existence of multiple distinct cognitive control mechanisms and challenge existing models of cognitive control that incorporate only a single control signal. PMID:19030873

On the interpretation of kernels - Computer simulation of responses to impulse pairs

NASA Technical Reports Server (NTRS)

Hung, G.; Stark, L.; Eykhoff, P.

1983-01-01

A method is presented for the use of a unit impulse response and responses to impulse pairs of variable separation in the calculation of the second-degree kernels of a quadratic system. A quadratic system may be built from simple linear terms of known dynamics and a multiplier. Computer simulation results on quadratic systems with building elements of various time constants indicate reasonably that the larger time constant term before multiplication dominates in the envelope of the off-diagonal kernel curves as these move perpendicular to and away from the main diagonal. The smaller time constant term before multiplication combines with the effect of the time constant after multiplication to dominate in the kernel curves in the direction of the second-degree impulse response, i.e., parallel to the main diagonal. Such types of insight may be helpful in recognizing essential aspects of (second-degree) kernels; they may be used in simplifying the model structure and, perhaps, add to the physical/physiological understanding of the underlying processes.

Integration of Immune Cell Populations, mRNA-Seq, and CpG Methylation to Better Predict Humoral Immunity to Influenza Vaccination: Dependence of mRNA-Seq/CpG Methylation on Immune Cell Populations

PubMed Central

Zimmermann, Michael T.; Kennedy, Richard B.; Grill, Diane E.; Oberg, Ann L.; Goergen, Krista M.; Ovsyannikova, Inna G.; Haralambieva, Iana H.; Poland, Gregory A.

2017-01-01

The development of a humoral immune response to influenza vaccines occurs on a multisystems level. Due to the orchestration required for robust immune responses when multiple genes and their regulatory components across multiple cell types are involved, we examined an influenza vaccination cohort using multiple high-throughput technologies. In this study, we sought a more thorough understanding of how immune cell composition and gene expression relate to each other and contribute to interindividual variation in response to influenza vaccination. We first hypothesized that many of the differentially expressed (DE) genes observed after influenza vaccination result from changes in the composition of participants’ peripheral blood mononuclear cells (PBMCs), which were assessed using flow cytometry. We demonstrated that DE genes in our study are correlated with changes in PBMC composition. We gathered DE genes from 128 other publically available PBMC-based vaccine studies and identified that an average of 57% correlated with specific cell subset levels in our study (permutation used to control false discovery), suggesting that the associations we have identified are likely general features of PBMC-based transcriptomics. Second, we hypothesized that more robust models of vaccine response could be generated by accounting for the interplay between PBMC composition, gene expression, and gene regulation. We employed machine learning to generate predictive models of B-cell ELISPOT response outcomes and hemagglutination inhibition (HAI) antibody titers. The top HAI and B-cell ELISPOT model achieved an area under the receiver operating curve (AUC) of 0.64 and 0.79, respectively, with linear model coefficients of determination of 0.08 and 0.28. For the B-cell ELISPOT outcomes, CpG methylation had the greatest predictive ability, highlighting potentially novel regulatory features important for immune response. B-cell ELISOT models using only PBMC composition had lower performance (AUC = 0.67), but highlighted well-known mechanisms. Our analysis demonstrated that each of the three data sets (cell composition, mRNA-Seq, and DNA methylation) may provide distinct information for the prediction of humoral immune response outcomes. We believe that these findings are important for the interpretation of current omics-based studies and set the stage for a more thorough understanding of interindividual immune responses to influenza vaccination. PMID:28484452

Immunopharmacological role of the leukotriene receptor antagonists and inhibitors of leukotrienes generating enzymes in multiple sclerosis.

PubMed

Mirshafiey, Abbas; Jadidi-Niaragh, Farhad

2010-06-01

Multiple sclerosis (MS) is a chronic inflammatory disease that involves central nervous system, and is generally associated with demyelination and axonal lesion. The effective factors for initiation of the inflammatory responses have not been known precisely so far. Leukotrienes (LTs) are inflammatory mediators with increased levels in the cerebrospinal fluid of MS patients and in experimental models of multiple sclerosis. Inhibition of LT receptors with specific antagonists can decrease inflammatory responses. In this review article we try to clarify the role of LT receptor antagonists and also inhibitors of enzymes which are involved in LTs generating pathway for treating multiple sclerosis as new targets for MS therapy. Moreover, we suggest that blockage of LT receptors by potent specific antagonists and/or agonists can be as a novel useful method in treatment of MS.

An Empirical Comparison of DDF Detection Methods for Understanding the Causes of DIF in Multiple-Choice Items

ERIC Educational Resources Information Center

Suh, Youngsuk; Talley, Anna E.

2015-01-01

This study compared and illustrated four differential distractor functioning (DDF) detection methods for analyzing multiple-choice items. The log-linear approach, two item response theory-model-based approaches with likelihood ratio tests, and the odds ratio approach were compared to examine the congruence among the four DDF detection methods.…

"Multiplication Is for White People": An Interview with Lisa Delpit

ERIC Educational Resources Information Center

Sokolower, Jody

2012-01-01

In the introduction to her new book, ""Multiplication Is for White People": Raising Expectations for Other People's Children," Lisa Delpit describes her response when Diane Ravitch asked her why she hasn't spoken out against the devastation of public schools in her home state of Louisiana and the efforts to make New Orleans the national model. She…

Multimodal Likelihoods in Educational Assessment: Will the Real Maximum Likelihood Score Please Stand up?

ERIC Educational Resources Information Center

Wothke, Werner; Burket, George; Chen, Li-Sue; Gao, Furong; Shu, Lianghua; Chia, Mike

2011-01-01

It has been known for some time that item response theory (IRT) models may exhibit a likelihood function of a respondent's ability which may have multiple modes, flat modes, or both. These conditions, often associated with guessing of multiple-choice (MC) questions, can introduce uncertainty and bias to ability estimation by maximum likelihood…

Environmental Interactions and Epistasis Are Revealed in the Proteomic Responses to Complex Stimuli

PubMed Central

Samir, Parimal; Rahul; Slaughter, James C.; Link, Andrew J.

2015-01-01

Ultimately, the genotype of a cell and its interaction with the environment determine the cell’s biochemical state. While the cell’s response to a single stimulus has been studied extensively, a conceptual framework to model the effect of multiple environmental stimuli applied concurrently is not as well developed. In this study, we developed the concepts of environmental interactions and epistasis to explain the responses of the S. cerevisiae proteome to simultaneous environmental stimuli. We hypothesize that, as an abstraction, environmental stimuli can be treated as analogous to genetic elements. This would allow modeling of the effects of multiple stimuli using the concepts and tools developed for studying gene interactions. Mirroring gene interactions, our results show that environmental interactions play a critical role in determining the state of the proteome. We show that individual and complex environmental stimuli behave similarly to genetic elements in regulating the cellular responses to stimuli, including the phenomena of dominance and suppression. Interestingly, we observed that the effect of a stimulus on a protein is dominant over other stimuli if the response to the stimulus involves the protein. Using publicly available transcriptomic data, we find that environmental interactions and epistasis regulate transcriptomic responses as well. PMID:26247773

Temporal scale dependent interactions between multiple environmental disturbances in microcosm ecosystems.

PubMed

Garnier, Aurélie; Pennekamp, Frank; Lemoine, Mélissa; Petchey, Owen L

2017-12-01

Global environmental change has negative impacts on ecological systems, impacting the stable provision of functions, goods, and services. Whereas effects of individual environmental changes (e.g. temperature change or change in resource availability) are reasonably well understood, we lack information about if and how multiple changes interact. We examined interactions among four types of environmental disturbance (temperature, nutrient ratio, carbon enrichment, and light) in a fully factorial design using a microbial aquatic ecosystem and observed responses of dissolved oxygen saturation at three temporal scales (resistance, resilience, and return time). We tested whether multiple disturbances combine in a dominant, additive, or interactive fashion, and compared the predictability of dissolved oxygen across scales. Carbon enrichment and shading reduced oxygen concentration in the short term (i.e. resistance); although no other effects or interactions were statistically significant, resistance decreased as the number of disturbances increased. In the medium term, only enrichment accelerated recovery, but none of the other effects (including interactions) were significant. In the long term, enrichment and shading lengthened return times, and we found significant two-way synergistic interactions between disturbances. The best performing model (dominant, additive, or interactive) depended on the temporal scale of response. In the short term (i.e. for resistance), the dominance model predicted resistance of dissolved oxygen best, due to a large effect of carbon enrichment, whereas none of the models could predict the medium term (i.e. resilience). The long-term response was best predicted by models including interactions among disturbances. Our results indicate the importance of accounting for the temporal scale of responses when researching the effects of environmental disturbances on ecosystems. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Culturally Responsive Pedagogy for Teacher Candidates of Color in Teacher Education Programs

ERIC Educational Resources Information Center

Gist, Conra D.

2011-01-01

This dissertation study uses culturally responsive pedagogy as a conceptual framework for exploring how teacher educators structure content, pedagogy, and classroom communities for teacher candidates of color at two model teacher education programs. Using multiple data sources including interviews, focus groups, classroom observations, faculty and…

Quantitative Models Describing Past and Current Nutrient Fluxes and Associated Ecosystem Level Responses in the Narragansett Bay Ecosystem

EPA Science Inventory

Multiple drivers, including nutrient loading and climate change, affect the Narragansett Bay ecosystem in Rhode Island/Massachusetts, USA. Managers are interested in understanding the timing and magnitude of these effects, and ecosystem responses to restoration actions. To provid...

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels

PubMed Central

Hyun, Seung Won; Wong, Weng Kee

2016-01-01

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs. PMID:26565557

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels.

PubMed

Hyun, Seung Won; Wong, Weng Kee

2015-11-01

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs.

Deficiency for endoglin in tumor vasculature weakens the endothelial barrier to metastatic dissemination

PubMed Central

Anderberg, Charlotte; Cunha, Sara I.; Zhai, Zhenhua; Cortez, Eliane; Pardali, Evangelia; Johnson, Jill R.; Franco, Marcela; Páez-Ribes, Marta; Cordiner, Ross; Fuxe, Jonas; Johansson, Bengt R.; Goumans, Marie-José; Casanovas, Oriol; ten Dijke, Peter; Arthur, Helen M.

2013-01-01

Therapy-induced resistance remains a significant hurdle to achieve long-lasting responses and cures in cancer patients. We investigated the long-term consequences of genetically impaired angiogenesis by engineering multiple tumor models deprived of endoglin, a co-receptor for TGF-β in endothelial cells actively engaged in angiogenesis. Tumors from endoglin-deficient mice adapted to the weakened angiogenic response, and refractoriness to diminished endoglin signaling was accompanied by increased metastatic capability. Mechanistic studies in multiple mouse models of cancer revealed that deficiency for endoglin resulted in a tumor vasculature that displayed hallmarks of endothelial-to-mesenchymal transition, a process of previously unknown significance in cancer biology, but shown by us to be associated with a reduced capacity of the vasculature to avert tumor cell intra- and extravasation. Nevertheless, tumors deprived of endoglin exhibited a delayed onset of resistance to anti-VEGF (vascular endothelial growth factor) agents, illustrating the therapeutic utility of combinatorial targeting of multiple angiogenic pathways for the treatment of cancer. PMID:23401487

Detector-Response Correction of Two-Dimensional γ -Ray Spectra from Neutron Capture

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

Rusev, G.; Jandel, M.; Arnold, C. W.

2015-05-28

The neutron-capture reaction produces a large variety of γ-ray cascades with different γ-ray multiplicities. A measured spectral distribution of these cascades for each γ-ray multiplicity is of importance to applications and studies of γ-ray statistical properties. The DANCE array, a 4π ball of 160 BaF 2 detectors, is an ideal tool for measurement of neutron-capture γ-rays. The high granularity of DANCE enables measurements of high-multiplicity γ-ray cascades. The measured two-dimensional spectra (γ-ray energy, γ-ray multiplicity) have to be corrected for the DANCE detector response in order to compare them with predictions of the statistical model or use them in applications.more » The detector-response correction problem becomes more difficult for a 4π detection system than for a single detector. A trial and error approach and an iterative decomposition of γ-ray multiplets, have been successfully applied to the detector-response correction. As a result, applications of the decomposition methods are discussed for two-dimensional γ-ray spectra measured at DANCE from γ-ray sources and from the 10B(n, γ) and 113Cd(n, γ) reactions.« less

A Two-Parameter Latent Trait Model. Methodology Project.

ERIC Educational Resources Information Center

Choppin, Bruce

On well-constructed multiple-choice tests, the most serious threat to measurement is not variation in item discrimination, but the guessing behavior that may be adopted by some students. Ways of ameliorating the effects of guessing are discussed, especially for problems in latent trait models. A new item response model, including an item parameter…

Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art

ERIC Educational Resources Information Center

Rupp, Andre A.; Templin, Jonathan L.

2008-01-01

"Diagnostic classification models" (DCM) are frequently promoted by psychometricians as important modelling alternatives for analyzing response data in situations where multivariate classifications of respondents are made on the basis of multiple postulated latent skills. In this review paper, a definitional boundary of the space of DCM…

IRT-ZIP Modeling for Multivariate Zero-Inflated Count Data

ERIC Educational Resources Information Center

Wang, Lijuan

2010-01-01

This study introduces an item response theory-zero-inflated Poisson (IRT-ZIP) model to investigate psychometric properties of multiple items and predict individuals' latent trait scores for multivariate zero-inflated count data. In the model, two link functions are used to capture two processes of the zero-inflated count data. Item parameters are…

Evaluation of the Multiple Sclerosis Walking Scale-12 (MSWS-12) in a Dutch sample: Application of item response theory.

PubMed

Mokkink, Lidwine Brigitta; Galindo-Garre, Francisca; Uitdehaag, Bernard Mj

2016-12-01

The Multiple Sclerosis Walking Scale-12 (MSWS-12) measures walking ability from the patients' perspective. We examined the quality of the MSWS-12 using an item response theory model, the graded response model (GRM). A total of 625 unique Dutch multiple sclerosis (MS) patients were included. After testing for unidimensionality, monotonicity, and absence of local dependence, a GRM was fit and item characteristics were assessed. Differential item functioning (DIF) for the variables gender, age, duration of MS, type of MS and severity of MS, reliability, total test information, and standard error of the trait level (θ) were investigated. Confirmatory factor analysis showed a unidimensional structure of the 12 items of the scale, explaining 88% of the variance. Item 2 did not fit into the GRM model. Reliability was 0.93. Items 8 and 9 (of the 11 and 12 item version respectively) showed DIF on the variable severity, based on the Expanded Disability Status Scale (EDSS). However, the EDSS is strongly related to the content of both items. Our results confirm the good quality of the MSWS-12. The trait level (θ) scores and item parameters of both the 12- and 11-item versions were highly comparable, although we do not suggest to change the content of the MSWS-12. © The Author(s), 2016.

Identification of radiation responsive genes and transcriptome profiling via complete RNA sequencing in a stable radioresistant U87 glioblastoma model.

PubMed

Doan, Ninh B; Nguyen, Ha S; Alhajala, Hisham S; Jaber, Basem; Al-Gizawiy, Mona M; Ahn, Eun-Young Erin; Mueller, Wade M; Chitambar, Christopher R; Mirza, Shama P; Schmainda, Kathleen M

2018-05-04

The absence of major progress in the treatment of glioblastoma (GBM) is partly attributable to our poor understanding of both GBM tumor biology and the acquirement of treatment resistance in recurrent GBMs. Recurrent GBMs are characterized by their resistance to radiation. In this study, we used an established stable U87 radioresistant GBM model and total RNA sequencing to shed light on global mRNA expression changes following irradiation. We identified many genes, the expressions of which were altered in our radioresistant GBM model, that have never before been reported to be associated with the development of radioresistant GBM and should be concertedly further investigated to understand their roles in radioresistance. These genes were enriched in various biological processes such as inflammatory response, cell migration, positive regulation of epithelial to mesenchymal transition, angiogenesis, apoptosis, positive regulation of T-cell migration, positive regulation of macrophage chemotaxis, T-cell antigen processing and presentation, and microglial cell activation involved in immune response genes. These findings furnish crucial information for elucidating the molecular mechanisms associated with radioresistance in GBM. Therapeutically, with the global alterations of multiple biological pathways observed in irradiated GBM cells, an effective GBM therapy may require a cocktail carrying multiple agents targeting multiple implicated pathways in order to have a chance at making a substantial impact on improving the overall GBM survival.

Assessing the nonlinear response of fine particles to precursor emissions: Development and application of an extended response surface modeling technique v1.0

DOE PAGES

Zhao, B.; Wang, S. X.; Xing, J.; ...

2015-01-30

An innovative extended response surface modeling technique (ERSM v1.0) is developed to characterize the nonlinear response of fine particles (PM₂̣₅) to large and simultaneous changes of multiple precursor emissions from multiple regions and sectors. The ERSM technique is developed based on the conventional response surface modeling (RSM) technique; it first quantifies the relationship between PM₂̣₅ concentrations and the emissions of gaseous precursors from each single region using the conventional RSM technique, and then assesses the effects of inter-regional transport of PM₂̣₅ and its gaseous precursors on PM₂̣₅ concentrations in the target region. We apply this novel technique with a widelymore » used regional chemical transport model (CTM) over the Yangtze River delta (YRD) region of China, and evaluate the response of PM₂̣₅ and its inorganic components to the emissions of 36 pollutant–region–sector combinations. The predicted PM₂̣₅ concentrations agree well with independent CTM simulations; the correlation coefficients are larger than 0.98 and 0.99, and the mean normalized errors (MNEs) are less than 1 and 2% for January and August, respectively. It is also demonstrated that the ERSM technique could reproduce fairly well the response of PM₂̣₅ to continuous changes of precursor emission levels between zero and 150%. Employing this new technique, we identify the major sources contributing to PM₂̣₅ and its inorganic components in the YRD region. The nonlinearity in the response of PM₂̣₅ to emission changes is characterized and the underlying chemical processes are illustrated.« less

Modelling and multi objective optimization of WEDM of commercially Monel super alloy using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Varun, Sajja; Reddy, Kalakada Bhargav Bal; Vardhan Reddy, R. R. Vishnu

2016-09-01

In this research work, development of a multi response optimization technique has been undertaken, using traditional desirability analysis and non-traditional particle swarm optimization techniques (for different customer's priorities) in wire electrical discharge machining (WEDM). Monel 400 has been selected as work material for experimentation. The effect of key process parameters such as pulse on time (TON), pulse off time (TOFF), peak current (IP), wire feed (WF) were on material removal rate (MRR) and surface roughness(SR) in WEDM operation were investigated. Further, the responses such as MRR and SR were modelled empirically through regression analysis. The developed models can be used by the machinists to predict the MRR and SR over a wide range of input parameters. The optimization of multiple responses has been done for satisfying the priorities of multiple users by using Taguchi-desirability function method and particle swarm optimization technique. The analysis of variance (ANOVA) is also applied to investigate the effect of influential parameters. Finally, the confirmation experiments were conducted for the optimal set of machining parameters, and the betterment has been proved.

Photonic Shape Memory Polymer with Stable Multiple Colors

PubMed Central

2017-01-01

A photonic shape memory polymer film that shows large color response (∼155 nm) in a wide temperature range has been fabricated from a semi-interpenetrating network of a cholesteric polymer and poly(benzyl acrylate). The large color response is achieved by mechanical embossing of the photonic film above its broad glass transition temperature. The embossed film, as it recovers to its original shape on heating through the broad thermal transition, exhibits multiple structural colors ranging from blue to orange. The relaxation behavior of the embossed film can be fully described using a Kelvin–Voigt model, which reveals that the influence of temperature on the generation of colors is much stronger than that of time, thereby producing stable multiple colors. PMID:28840717

EXPLAINING FOREST COMPOSITION AND BIOMASS ACROSS MULTIPLE BIOGEOGRAPHIC REGIONS

EPA Science Inventory

Current scientific concerns regarding the impacts of global change include the responses of forest composition and biomass to rapid changes in climate, and forest gap models, have often been used to address this issue. These models reflect the concept that forest composition and...

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.

Adaptive iterative design (AID): a novel approach for evaluating the interactive effects of multiple stressors on aquatic organisms.

PubMed

Glaholt, Stephen P; Chen, Celia Y; Demidenko, Eugene; Bugge, Deenie M; Folt, Carol L; Shaw, Joseph R

2012-08-15

The study of stressor interactions by eco-toxicologists using nonlinear response variables is limited by required amounts of a priori knowledge, complexity of experimental designs, the use of linear models, and the lack of use of optimal designs of nonlinear models to characterize complex interactions. Therefore, we developed AID, an adaptive-iterative design for eco-toxicologist to more accurately and efficiently examine complex multiple stressor interactions. AID incorporates the power of the general linear model and A-optimal criteria with an iterative process that: 1) minimizes the required amount of a priori knowledge, 2) simplifies the experimental design, and 3) quantifies both individual and interactive effects. Once a stable model is determined, the best fit model is identified and the direction and magnitude of stressors, individually and all combinations (including complex interactions) are quantified. To validate AID, we selected five commonly co-occurring components of polluted aquatic systems, three metal stressors (Cd, Zn, As) and two water chemistry parameters (pH, hardness) to be tested using standard acute toxicity tests in which Daphnia mortality is the (nonlinear) response variable. We found after the initial data input of experimental data, although literature values (e.g. EC-values) may also be used, and after only two iterations of AID, our dose response model was stable. The model ln(Cd)*ln(Zn) was determined the best predictor of Daphnia mortality response to the combined effects of Cd, Zn, As, pH, and hardness. This model was then used to accurately identify and quantify the strength of both greater- (e.g. As*Cd) and less-than additive interactions (e.g. Cd*Zn). Interestingly, our study found only binary interactions significant, not higher order interactions. We conclude that AID is more efficient and effective at assessing multiple stressor interactions than current methods. Other applications, including life-history endpoints commonly used by regulators, could benefit from AID's efficiency in assessing water quality criteria. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

A Bayesian Approach to Estimating Coupling Between Neural Components: Evaluation of the Multiple Component, Event-Related Potential (mcERP) Algorithm

NASA Technical Reports Server (NTRS)

Shah, Ankoor S.; Knuth, Kevin H.; Truccolo, Wilson A.; Ding, Ming-Zhou; Bressler, Steven L.; Schroeder, Charles E.; Clancy, Daniel (Technical Monitor)

2002-01-01

Accurate measurement of single-trial responses is key to a definitive use of complex electromagnetic and hemodynamic measurements in the investigation of brain dynamics. We developed the multiple component, Event-Related Potential (mcERP) approach to single-trial response estimation. To improve our resolution of dynamic interactions between neuronal ensembles located in different layers within a cortical region and/or in different cortical regions. The mcERP model assets that multiple components defined as stereotypic waveforms comprise the stimulus-evoked response and that these components may vary in amplitude and latency from trial to trial. Maximum a posteriori (MAP) solutions for the model are obtained by iterating a set of equations derived from the posterior probability. Our first goal was to use the ANTWERP algorithm to analyze interactions (specifically latency and amplitude correlation) between responses in different layers within a cortical region. Thus, we evaluated the model by applying the algorithm to synthetic data containing two correlated local components and one independent far-field component. Three cases were considered: the local components were correlated by an interaction in their single-trial amplitudes, by an interaction in their single-trial latencies, or by an interaction in both amplitude and latency. We then analyzed the accuracy with which the algorithm estimated the component waveshapes and the single-trial parameters as a function of the linearity of each of these relationships. Extensions of these analyses to real data are discussed as well as ongoing work to incorporate more detailed prior information.

Whole tree xylem sap flow responses to multiple environmental variables in a wet tropical forest

Treesearch

J.J. O' Brien; S.F. Oberbauer; D.B. Clark

2004-01-01

In order to quantify and characterize the variance in rain-forest tree physiology, whole tree sap flow responses to local environmental conditions were investigated in 10 species of trees with diverse traits at La Selva Biological Station, Costa Rica. A simple model was developed to predict tree sap flow responses to a synthetic environmental variable generated by a...

Measuring the Effect of Gender on Computer Attitudes among Pre-Service Teachers: A Multiple Indicators, Multiple Causes (MIMIC) Modeling

ERIC Educational Resources Information Center

Teo, Timothy

2010-01-01

Purpose: The purpose of this paper is to examine the effect of gender on pre-service teachers' computer attitudes. Design/methodology/approach: A total of 157 pre-service teachers completed a survey questionnaire measuring their responses to four constructs which explain computer attitude. These were administered during the teaching term where…

Multiple Access Interference Reduction Using Received Response Code Sequence for DS-CDMA UWB System

NASA Astrophysics Data System (ADS)

Toh, Keat Beng; Tachikawa, Shin'ichi

This paper proposes a combination of novel Received Response (RR) sequence at the transmitter and a Matched Filter-RAKE (MF-RAKE) combining scheme receiver system for the Direct Sequence-Code Division Multiple Access Ultra Wideband (DS-CDMA UWB) multipath channel model. This paper also demonstrates the effectiveness of the RR sequence in Multiple Access Interference (MAI) reduction for the DS-CDMA UWB system. It suggests that by using conventional binary code sequence such as the M sequence or the Gold sequence, there is a possibility of generating extra MAI in the UWB system. Therefore, it is quite difficult to collect the energy efficiently although the RAKE reception method is applied at the receiver. The main purpose of the proposed system is to overcome the performance degradation for UWB transmission due to the occurrence of MAI during multiple accessing in the DS-CDMA UWB system. The proposed system improves the system performance by improving the RAKE reception performance using the RR sequence which can reduce the MAI effect significantly. Simulation results verify that significant improvement can be obtained by the proposed system in the UWB multipath channel models.

A Nonparametric Approach for Assessing Goodness-of-Fit of IRT Models in a Mixed Format Test

ERIC Educational Resources Information Center

Liang, Tie; Wells, Craig S.

2015-01-01

Investigating the fit of a parametric model plays a vital role in validating an item response theory (IRT) model. An area that has received little attention is the assessment of multiple IRT models used in a mixed-format test. The present study extends the nonparametric approach, proposed by Douglas and Cohen (2001), to assess model fit of three…

Dynamic fuzzy modeling of storm water infiltration in urban fractured aquifers

USGS Publications Warehouse

Hong, Y.-S.; Rosen, Michael R.; Reeves, R.R.

2002-01-01

In an urban fractured-rock aquifer in the Mt. Eden area of Auckland, New Zealand, disposal of storm water is via "soakholes" drilled directly into the top of the fractured basalt rock. The dynamic response of the groundwater level due to the storm water infiltration shows characteristics of a strongly time-varying system. A dynamic fuzzy modeling approach, which is based on multiple local models that are weighted using fuzzy membership functions, has been developed to identify and predict groundwater level fluctuations caused by storm water infiltration. The dynamic fuzzy model is initialized by the fuzzy clustering algorithm and optimized by the gradient-descent algorithm in order to effectively derive the multiple local models-each of which is associated with a locally valid model that represents the groundwater level state as a response to different intensities of rainfall events. The results have shown that even if the number of fuzzy local models derived is small, the fuzzy modeling approach developed provides good prediction results despite the highly time-varying nature of this urban fractured-rock aquifer system. Further, it allows interpretable representations of the dynamic behavior of the groundwater system due to storm water infiltration.

Modelling the immunological response to a tetravalent dengue vaccine from multiple phase-2 trials in Latin America and South East Asia.

PubMed

Dorigatti, Ilaria; Aguas, Ricardo; Donnelly, Christl A; Guy, Bruno; Coudeville, Laurent; Jackson, Nicholas; Saville, Melanie; Ferguson, Neil M

2015-07-17

The most advanced dengue vaccine candidate is a live-attenuated recombinant vaccine containing the four dengue viruses on the yellow fever vaccine backbone (CYD-TDV) developed by Sanofi Pasteur. Several analyses have been published on the safety and immunogenicity of the CYD-TDV vaccine from single trials but none modelled the heterogeneity observed in the antibody responses elicited by the vaccine. We analyse the immunogenicity data collected in five phase-2 trials of the CYD-TDV vaccine. We provide a descriptive analysis of the aggregated datasets and fit the observed post-vaccination PRNT50 titres against the four dengue (DENV) serotypes using multivariate regression models. We find that the responses to CYD-TDV are principally predicted by the baseline immunological status against DENV, but the trial is also a significant predictor. We find that the CYD-TDV vaccine generates similar titres against all serotypes following the third dose, though DENV4 is immunodominant after the first dose. This study contributes to a better understanding of the immunological responses elicited by CYD-TDV. The recent availability of phase-3 data is a unique opportunity to further investigate the immunogenicity and efficacy of the CYD-TDV vaccine, especially in subjects with different levels of pre-existing immunity against DENV. Modelling multiple immunological outcomes with a single multivariate model offers advantages over traditional approaches, capturing correlations between response variables, and the statistical method adopted in this study can be applied to a variety of infections with interacting strains. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A simple white noise analysis of neuronal light responses.

PubMed

Chichilnisky, E J

2001-05-01

A white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpretable model of light responses even for neurons that display a common form of response nonlinearity that precludes classical linear systems analysis. A theoretical justification of the technique is presented that relies only on elementary linear algebra and statistics. Implementation is described with examples. The technique and the underlying model of neural responses are validated using recordings from retinal ganglion cells, and in principle are applicable to other neurons. Advantages and disadvantages of the technique relative to classical approaches are discussed.

Single and multiple in-season measurements as indicators of at-harvest cotton boll damage caused by verde plant bug (Hemiptera: Miridae).

PubMed

Brewer, Michael J; Armstrong, J Scott; Parker, Roy D

2013-06-01

The ability to monitor verde plant bug, Creontiades signatus Distant (Hemiptera: Miridae), and the progression of cotton, Gossypium hirsutum L., boll responses to feeding and associated cotton boll rot provided opportunity to assess if single in-season measurements had value in evaluating at-harvest damage to bolls and if multiple in-season measurements enhanced their combined use. One in-season verde plant bug density measurement, three in-season plant injury measurements, and two at-harvest damage measurements were taken in 15 cotton fields in South Texas, 2010. Linear regression selected two measurements as potentially useful indicators of at-harvest damage: verde plant bug density (adjusted r2 = 0.68; P = 0.0004) and internal boll injury of the carpel wall (adjusted r2 = 0.72; P = 0.004). Considering use of multiple measurements, a stepwise multiple regression of the four in-season measurements selected a univariate model (verde plant bug density) using a 0.15 selection criterion (adjusted r2 = 0.74; P = 0.0002) and a bivariate model (verde plant bug density-internal boll injury) using a 0.25 selection criterion (adjusted r2 = 0.76; P = 0.0007) as indicators of at-harvest damage. In a validation using cultivar and water regime treatments experiencing low verde plant bug pressure in 2011 and 2012, the bivariate model performed better than models using verde plant bug density or internal boll injury separately. Overall, verde plant bug damaging cotton bolls exemplified the benefits of using multiple in-season measurements in pest monitoring programs, under the challenging situation when at-harvest damage results from a sequence of plant responses initiated by in-season insect feeding.

Density dependence governs when population responses to multiple stressors are magnified or mitigated.

PubMed

Hodgson, Emma E; Essington, Timothy E; Halpern, Benjamin S

2017-10-01

Population endangerment typically arises from multiple, potentially interacting anthropogenic stressors. Extensive research has investigated the consequences of multiple stressors on organisms, frequently focusing on individual life stages. Less is known about population-level consequences of exposure to multiple stressors, especially when exposure varies through life. We provide the first theoretical basis for identifying species at risk of magnified effects from multiple stressors across life history. By applying a population modeling framework, we reveal conditions under which population responses from stressors applied to distinct life stages are either magnified (synergistic) or mitigated. We find that magnification or mitigation critically depends on the shape of density dependence, but not the life stage in which it occurs. Stressors are always magnified when density dependence is linear or concave, and magnified or mitigated when it is convex. Using Bayesian numerical methods, we estimated the shape of density dependence for eight species across diverse taxa, finding support for all three shapes. © 2017 by the Ecological Society of America.

An iterative fullwave simulation approach to multiple scattering in media with randomly distributed microbubbles

NASA Astrophysics Data System (ADS)

Joshi, Aditya; Lindsey, Brooks D.; Dayton, Paul A.; Pinton, Gianmarco; Muller, Marie

2017-05-01

Ultrasound contrast agents (UCA), such as microbubbles, enhance the scattering properties of blood, which is otherwise hypoechoic. The multiple scattering interactions of the acoustic field with UCA are poorly understood due to the complexity of the multiple scattering theories and the nonlinear microbubble response. The majority of bubble models describe the behavior of UCA as single, isolated microbubbles suspended in infinite medium. Multiple scattering models such as the independent scattering approximation can approximate phase velocity and attenuation for low scatterer volume fractions. However, all current models and simulation approaches only describe multiple scattering and nonlinear bubble dynamics separately. Here we present an approach that combines two existing models: (1) a full-wave model that describes nonlinear propagation and scattering interactions in a heterogeneous attenuating medium and (2) a Paul-Sarkar model that describes the nonlinear interactions between an acoustic field and microbubbles. These two models were solved numerically and combined with an iterative approach. The convergence of this combined model was explored in silico for 0.5 × 106 microbubbles ml-1, 1% and 2% bubble concentration by volume. The backscattering predicted by our modeling approach was verified experimentally with water tank measurements performed with a 128-element linear array transducer. An excellent agreement in terms of the fundamental and harmonic acoustic fields is shown. Additionally, our model correctly predicts the phase velocity and attenuation measured using through transmission and predicted by the independent scattering approximation.

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.

PubMed

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-11-26

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

Gamma-ray Output Spectra from 239 Pu Fission

DOE PAGES

Ullmann, John

2015-05-25

The gamma-ray multiplicities, individual gamma-ray energy spectra, and total gamma energy spectra following neutron-induced fission of 239Pu were measured using the DANCE detector at Los Alamos. Corrections for detector response were made using a forward-modeling technique based on propagating sets of gamma rays generated from a paramaterized model through a GEANT model of the DANCE array and adjusting the parameters for best fit to the measured spectra. The results for the gamma-ray spectrum and multiplicity are in general agreement with previous results, but the measured total gamma-ray energy is about 10% higher. We found that a dependence of the gamma-raymore » spectrum on the gamma-ray multplicity was also observed. Finally, global model calculations of the multiplicity and gamma energy distributions are in good agreement with the data, but predict a slightly softer total-energy distribution.« less

Interviewer effects on non-response propensity in longitudinal surveys: a multilevel modelling approach

PubMed Central

Vassallo, Rebecca; Durrant, Gabriele B; Smith, Peter W F; Goldstein, Harvey

2015-01-01

The paper investigates two different multilevel approaches, the multilevel cross-classified and the multiple-membership models, for the analysis of interviewer effects on wave non-response in longitudinal surveys. The models proposed incorporate both interviewer and area effects to account for the non-hierarchical structure, the influence of potentially more than one interviewer across waves and possible confounding of area and interviewer effects arising from the non-random allocation of interviewers across areas. The methods are compared by using a data set: the UK Family and Children Survey. PMID:25598587

Toward improved calibration of watershed models: multisite many objective measures of information

USDA-ARS?s Scientific Manuscript database

This paper presents a computational framework for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. The framework consists of four components: (i) an a-priori characterization of system behavior; (ii) a formal an...

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

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 Odds Ratio Approach for Detecting DDF under the Nested Logit Modeling Framework

ERIC Educational Resources Information Center

Terzi, Ragip; Suh, Youngsuk

2015-01-01

An odds ratio approach (ORA) under the framework of a nested logit model was proposed for evaluating differential distractor functioning (DDF) in multiple-choice items and was compared with an existing ORA developed under the nominal response model. The performances of the two ORAs for detecting DDF were investigated through an extensive…

Curve of Factors Model: A Latent Growth Modeling Approach for Educational Research

ERIC Educational Resources Information Center

Isiordia, Marilu; Ferrer, Emilio

2018-01-01

A first-order latent growth model assesses change in an unobserved construct from a single score and is commonly used across different domains of educational research. However, examining change using a set of multiple response scores (e.g., scale items) affords researchers several methodological benefits not possible when using a single score. A…

Structural Equation Modeling (SEM) for Satisfaction and Dissatisfaction Ratings; Multiple Group Invariance Analysis across Scales with Different Response Format

ERIC Educational Resources Information Center

Mazaheri, Mehrdad; Theuns, Peter

2009-01-01

The current study evaluates three hypothesized models on subjective well-being, comprising life domain ratings (LDR), overall satisfaction with life (OSWL), and overall dissatisfaction with life (ODWL), using structural equation modeling (SEM). A sample of 1,310 volunteering students, randomly assigned to six conditions, rated their overall life…

Probing Lexical Representations: Simultaneous Modeling of Word and Reader Contributions to Multidimensional Lexical Representations

ERIC Educational Resources Information Center

Goodwin, Amanda P.; Gilbert, Jennifer K.; Cho, Sun-Joo; Kearns, Devin M.

2014-01-01

The current study models reader, item, and word contributions to the lexical representations of 39 morphologically complex words for 172 middle school students using a crossed random-effects item response model with multiple outcomes. We report 3 findings. First, results suggest that lexical representations can be characterized by separate but…

HiTEC: a connectionist model of the interaction between perception and action planning.

PubMed

Haazebroek, Pascal; Raffone, Antonino; Hommel, Bernhard

2017-11-01

Increasing evidence suggests that perception and action planning do not represent separable stages of a unidirectional processing sequence, but rather emerging properties of highly interactive processes. To capture these characteristics of the human cognitive system, we have developed a connectionist model of the interaction between perception and action planning: HiTEC, based on the Theory of Event Coding (Hommel et al. in Behav Brain Sci 24:849-937, 2001). The model is characterized by representations at multiple levels and by shared representations and processes. It complements available models of stimulus-response translation by providing a rationale for (1) how situation-specific meanings of motor actions emerge, (2) how and why some aspects of stimulus-response translation occur automatically and (3) how task demands modulate sensorimotor processing. The model is demonstrated to provide a unitary account and simulation of a number of key findings with multiple experimental paradigms on the interaction between perception and action such as the Simon effect, its inversion (Hommel in Psychol Res 55:270-279, 1993), and action-effect learning.

Equivalent circuit model of Ge/Si separate absorption charge multiplication avalanche photodiode

NASA Astrophysics Data System (ADS)

Wang, Wei; Chen, Ting; Yan, Linshu; Bao, Xiaoyuan; Xu, Yuanyuan; Wang, Guang; Wang, Guanyu; Yuan, Jun; Li, Junfeng

2018-03-01

The equivalent circuit model of Ge/Si Separate Absorption Charge Multiplication Avalanche Photodiode (SACM-APD) is proposed. Starting from the carrier rate equations in different regions of device and considering the influences of non-uniform electric field, noise, parasitic effect and some other factors, the equivalent circuit model of SACM-APD device is established, in which the steady-state and transient current voltage characteristics can be described exactly. In addition, the proposed Ge/Si SACM APD equivalent circuit model is embedded in PSpice simulator. The important characteristics of Ge/Si SACM APD such as dark current, frequency response, shot noise are simulated, the simulation results show that the simulation with the proposed model are in good agreement with the experimental results.

Towards Predicting the Response of a Solid Tumour to Chemotherapy and Radiotherapy Treatments: Clinical Insights from a Computational Model

PubMed Central

Powathil, Gibin G.; Adamson, Douglas J. A.; Chaplain, Mark A. J.

2013-01-01

In this paper we use a hybrid multiscale mathematical model that incorporates both individual cell behaviour through the cell-cycle and the effects of the changing microenvironment through oxygen dynamics to study the multiple effects of radiation therapy. The oxygenation status of the cells is considered as one of the important prognostic markers for determining radiation therapy, as hypoxic cells are less radiosensitive. Another factor that critically affects radiation sensitivity is cell-cycle regulation. The effects of radiation therapy are included in the model using a modified linear quadratic model for the radiation damage, incorporating the effects of hypoxia and cell-cycle in determining the cell-cycle phase-specific radiosensitivity. Furthermore, after irradiation, an individual cell's cell-cycle dynamics are intrinsically modified through the activation of pathways responsible for repair mechanisms, often resulting in a delay/arrest in the cell-cycle. The model is then used to study various combinations of multiple doses of cell-cycle dependent chemotherapies and radiation therapy, as radiation may work better by the partial synchronisation of cells in the most radiosensitive phase of the cell-cycle. Moreover, using this multi-scale model, we investigate the optimum sequencing and scheduling of these multi-modality treatments, and the impact of internal and external heterogeneity on the spatio-temporal patterning of the distribution of tumour cells and their response to different treatment schedules. PMID:23874170

Local responses to trauma: symptom, affect, and healing.

PubMed

Hinton, Devon E; Kirmayer, Laurence J

2013-10-01

This article provides an introduction to the thematic issue of Transcultural Psychiatry on local responses to trauma. To illustrate how local responses to trauma may be therapeutic, we consider the multiple dimensions or domains that may be targeted by healing rituals and interventions. We then outline a theoretical model of the generation of trauma-related symptoms and distress. We present the multiplex model of symptom generation which posits multiple cognitive, social, and physiological mechanisms by which various triggers can lead to severe distress among trauma victims in acute episodes, and which may be targeted in treatment. More persistent forms of distress can be explained in terms of the effects of persistent mood states and associated modes of cognitive processing and behavior that render individuals vulnerable to chronic symptoms and acute exacerbations. The beneficial effects of healing rituals and interventions may occur, in part, by inducing positive affective states associated with a flexible mind-set. We conclude by summarizing some of the contributions of the papers in this issue to understanding local therapeutic processes of healing.

Coactivation of response initiation processes with redundant signals.

PubMed

Maslovat, Dana; Hajj, Joëlle; Carlsen, Anthony N

2018-05-14

During reaction time (RT) tasks, participants respond faster to multiple stimuli from different modalities as compared to a single stimulus, a phenomenon known as the redundant signal effect (RSE). Explanations for this effect typically include coactivation arising from the multiple stimuli, which results in enhanced processing of one or more response production stages. The current study compared empirical RT data with the predictions of a model in which initiation-related activation arising from each stimulus is additive. Participants performed a simple wrist extension RT task following either a visual go-signal, an auditory go-signal, or both stimuli with the auditory stimulus delayed between 0 and 125 ms relative to the visual stimulus. Results showed statistical equivalence between the predictions of an additive initiation model and the observed RT data, providing novel evidence that the RSE can be explained via a coactivation of initiation-related processes. It is speculated that activation summation occurs at the thalamus, leading to the observed facilitation of response initiation. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeling and analysis of the TF30-P-3 compressor system with inlet pressure distortion

NASA Technical Reports Server (NTRS)

Mazzawy, R. S.; Banks, G. A.

1976-01-01

Circumferential inlet distortion testing of a TF30-P-3 afterburning turbofan engine was conducted at NASA-Lewis Research Center. Pratt and Whitney Aircraft analyzed the data using its multiple segment parallel compressor model and classical compressor theory. Distortion attenuation analysis resulted in a detailed flow field calculation with good agreement between multiple segment model predictions and the test data. Sensitivity of the engine stall line to circumferential inlet distortion was calculated on the basis of parallel compressor theory to be more severe than indicated by the data. However, the calculated stall site location was in agreement with high response instrumentation measurements.

Modal survey of the space shuttle solid rocket motor using multiple input methods

NASA Technical Reports Server (NTRS)

Brillhart, Ralph; Hunt, David L.; Jensen, Brent M.; Mason, Donald R.

1987-01-01

The ability to accurately characterize propellant in a finite element model is a concern of engineers tasked with studying the dynamic response of the Space Shuttle Solid Rocket Motor (SRM). THe uncertainties arising from propellant characterization through specimem testing led to the decision to perform a model survey and model correlation of a single segment of the Shuttle SRM. Multiple input methods were used to excite and define case/propellant modes of both an inert segment and, later, a live propellant segment. These tests were successful at defining highly damped, flexible modes, several pairs of which occured with frequency spacing of less than two percent.

Predicting cancer rates in astronauts from animal carcinogenesis studies and cellular markers

NASA Technical Reports Server (NTRS)

Williams, J. R.; Zhang, Y.; Zhou, H.; Osman, M.; Cha, D.; Kavet, R.; Cuccinotta, F.; Dicello, J. F.; Dillehay, L. E.

1999-01-01

The radiation space environment includes particles such as protons and multiple species of heavy ions, with much of the exposure to these radiations occurring at extremely low average dose-rates. Limitations in databases needed to predict cancer hazards in human beings from such radiations are significant and currently do not provide confidence that such predictions are acceptably precise or accurate. In this article, we outline the need for animal carcinogenesis data based on a more sophisticated understanding of the dose-response relationship for induction of cancer and correlative cellular endpoints by representative space radiations. We stress the need for a model that can interrelate human and animal carcinogenesis data with cellular mechanisms. Using a broad model for dose-response patterns which we term the "subalpha-alpha-omega (SAO) model", we explore examples in the literature for radiation-induced cancer and for radiation-induced cellular events to illustrate the need for data that define the dose-response patterns more precisely over specific dose ranges, with special attention to low dose, low dose-rate exposure. We present data for multiple endpoints in cells, which vary in their radiosensitivity, that also support the proposed model. We have measured induction of complex chromosome aberrations in multiple cell types by two space radiations, Fe-ions and protons, and compared these to photons delivered at high dose-rate or low dose-rate. Our data demonstrate that at least three factors modulate the relative efficacy of Fe-ions compared to photons: (i) intrinsic radiosensitivity of irradiated cells; (ii) dose-rate; and (iii) another unspecified effect perhaps related to reparability of DNA lesions. These factors can produce respectively up to at least 7-, 6- and 3-fold variability. These data demonstrate the need to understand better the role of intrinsic radiosensitivity and dose-rate effects in mammalian cell response to ionizing radiation. Such understanding is critical in extrapolating databases between cellular response, animal carcinogenesis and human carcinogenesis, and we suggest that the SAO model is a useful tool for such extrapolation.

Climate change and watershed mercury export: a multiple projection and model analysis

EPA Science Inventory

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. We apply an ensemble of watershed models to simulate and assess the responses of hydrological and total Hg (HgT) fluxes and concentrations to two climate change projections in the US Co...

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

EPA Science Inventory

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

A multiple reflection model for the investigation of infrared transmission of a graphene/substrate system

NASA Astrophysics Data System (ADS)

Zhang, Jie; Ding, Lan; Liang, Changneng; Xiao, Yiming; Xu, Wen

2017-11-01

We develop a multiple reflection model (MRM) for the examination of infrared transmission properties of a graphene/substrate system. The incident angle and the multiple reflection beams in the substrate with finite thickness are taken into consideration. The model can be applied to predict the optical responses of graphene/substrate systems or to extract the real part of the optical conductance of graphene from the experimental measurement. As an example, we calculate the relative transmittance of graphene/quartz and graphene/sapphire systems by using MRM and provide an experimental verification in the near-infrared range. The measured results show good agreement with the calculated ones. Our method can be easily extended to accurately and non-invasively identify the layer numbers of other 2D materials, and assess the quality of them.

A Game Theoretical Model for Location of Terror Response Facilities under Capacitated Resources

PubMed Central

Kang, Qi; Xu, Weisheng; Wu, Qidi

2013-01-01

This paper is concerned with the effect of capacity constraints on the locations of terror response facilities. We assume that the state has limited resources, and multiple facilities may be involved in the response until the demand is satisfied consequently. We formulate a leader-follower game model between the state and the terrorist and prove the existence and uniqueness of the Nash equilibrium. An integer linear programming is proposed to obtain the equilibrium results when the facility number is fixed. The problem is demonstrated by a case study of the 19 districts of Shanghai, China. PMID:24459446

Dielectric response in Bloch’s hydrodynamic model of an electron-ion plasma

NASA Astrophysics Data System (ADS)

Ishikawa, K.; Felderhof, B. U.

The linear response of an electron-ion plasma to an applied oscillating electric field is studied within the framework of Bloch’s classical hydrodynamic model. The ions are assumed to be fixed in space and distributed according to a known probability distribution. The linearized equations of motion for electron density and flow velocity are studied with the aid of a multiple scattering analysis and cluster expansion. This allows systematic reduction of the many-ion problem to a composition of few-ion problems, and shows how the longitudinal dielectric response function can in principle be calculated.

In Silico Investigations of the Anti-Catabolic Effects of Pamidronate and Denosumab on Multiple Myeloma-Induced Bone Disease

PubMed Central

Wang, Yan; Lin, Bo

2012-01-01

It is unclear whether the new anti-catabolic agent denosumab represents a viable alternative to the widely used anti-catabolic agent pamidronate in the treatment of Multiple Myeloma (MM)-induced bone disease. This lack of clarity primarily stems from the lack of sufficient clinical investigations, which are costly and time consuming. However, in silico investigations require less time and expense, suggesting that they may be a useful complement to traditional clinical investigations. In this paper, we aim to (i) develop integrated computational models that are suitable for investigating the effects of pamidronate and denosumab on MM-induced bone disease and (ii) evaluate the responses to pamidronate and denosumab treatments using these integrated models. To achieve these goals, pharmacokinetic models of pamidronate and denosumab are first developed and then calibrated and validated using different clinical datasets. Next, the integrated computational models are developed by incorporating the simulated transient concentrations of pamidronate and denosumab and simulations of their actions on the MM-bone compartment into the previously proposed MM-bone model. These integrated models are further calibrated and validated by different clinical datasets so that they are suitable to be applied to investigate the responses to the pamidronate and denosumab treatments. Finally, these responses are evaluated by quantifying the bone volume, bone turnover, and MM-cell density. This evaluation identifies four denosumab regimes that potentially produce an overall improved bone-related response compared with the recommended pamidronate regime. This in silico investigation supports the idea that denosumab represents an appropriate alternative to pamidronate in the treatment of MM-induced bone disease. PMID:23028650

Attention Modulates Spatial Precision in Multiple-Object Tracking.

PubMed

Srivastava, Nisheeth; Vul, Ed

2016-01-01

We present a computational model of multiple-object tracking that makes trial-level predictions about the allocation of visual attention and the effect of this allocation on observers' ability to track multiple objects simultaneously. This model follows the intuition that increased attention to a location increases the spatial resolution of its internal representation. Using a combination of empirical and computational experiments, we demonstrate the existence of a tight coupling between cognitive and perceptual resources in this task: Low-level tracking of objects generates bottom-up predictions of error likelihood, and high-level attention allocation selectively reduces error probabilities in attended locations while increasing it at non-attended locations. Whereas earlier models of multiple-object tracking have predicted the big picture relationship between stimulus complexity and response accuracy, our approach makes accurate predictions of both the macro-scale effect of target number and velocity on tracking difficulty and micro-scale variations in difficulty across individual trials and targets arising from the idiosyncratic within-trial interactions of targets and distractors. Copyright © 2016 Cognitive Science Society, Inc.

Component mode synthesis and large deflection vibration of complex structures. Volume 3: Multiple-mode nonlinear free and forced vibrations of beams using finite element method

NASA Technical Reports Server (NTRS)

Mei, Chuh; Shen, Mo-How

1987-01-01

Multiple-mode nonlinear forced vibration of a beam was analyzed by the finite element method. Inplane (longitudinal) displacement and inertia (IDI) are considered in the formulation. By combining the finite element method and nonlinear theory, more realistic models of structural response are obtained more easily and faster.

Modeling relief demands in an emergency supply chain system under large-scale disasters based on a queuing network.

PubMed

He, Xinhua; Hu, Wenfa

2014-01-01

This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model.

Modeling Relief Demands in an Emergency Supply Chain System under Large-Scale Disasters Based on a Queuing Network

PubMed Central

He, Xinhua

2014-01-01

This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367

Multiple templates-based homology modeling enhances structure quality of AT1 receptor: validation by molecular dynamics and antagonist docking.

PubMed

Sokkar, Pandian; Mohandass, Shylajanaciyar; Ramachandran, Murugesan

2011-07-01

We present a comparative account on 3D-structures of human type-1 receptor (AT1) for angiotensin II (AngII), modeled using three different methodologies. AngII activates a wide spectrum of signaling responses via the AT1 receptor that mediates physiological control of blood pressure and diverse pathological actions in cardiovascular, renal, and other cell types. Availability of 3D-model of AT1 receptor would significantly enhance the development of new drugs for cardiovascular diseases. However, templates of AT1 receptor with low sequence similarity increase the complexity in straightforward homology modeling, and hence there is a need to evaluate different modeling methodologies in order to use the models for sensitive applications such as rational drug design. Three models were generated for AT1 receptor by, (1) homology modeling with bovine rhodopsin as template, (2) homology modeling with multiple templates and (3) threading using I-TASSER web server. Molecular dynamics (MD) simulation (15 ns) of models in explicit membrane-water system, Ramachandran plot analysis and molecular docking with antagonists led to the conclusion that multiple template-based homology modeling outweighs other methodologies for AT1 modeling.

Molecular Insights into the Effects of Media-Drug and Carrier-Drug Interactions on pH-Responsive Drug Carriers.

PubMed

Katiyar, Ratna S; Jha, Prateek K

2018-05-10

We have performed two sets of all atom molecular dynamics (MD) simulations of poly(acrylic acid) (PAA) oligomers, considered as a model pH-responsive drug carrier. In the first set, multiple oligomers of PAA are simulated in model gastric and intestinal fluids, where the degree of deprotonation of PAA oligomers is varied with the medium pH. Since the gastric fluid has a pH substantially lower than that of intestinal fluid, PAA is relatively lesser ionized in gastric fluid and forms aggregates. In the second set, we simulated multiple oligomers of PAA with multiple molecules of a cationic anticancer drug, doxorubicin (DOX), for a range of pH values representative of various physiological conditions. The diffusion coefficient of DOX decreases with an increase in pH due to an increase in the ionic complexation of PAA with DOX, despite a decrease in PAA aggregation. Our findings are in agreement with recent experimental reports on pH-triggered targeting of tumor cells by the PAA-DOX system. Results of these two sets of studies establish that both carrier aggregation and carrier-drug interactions are competing influences that together determine the drug release from pH-responsive polymers.

Multiple response optimization of processing and formulation parameters of Eudragit RL/RS-based matrix tablets for sustained delivery of diclofenac.

PubMed

Elzayat, Ehab M; Abdel-Rahman, Ali A; Ahmed, Sayed M; Alanazi, Fars K; Habib, Walid A; Sakr, Adel

2017-11-01

Multiple response optimization is an efficient technique to develop sustained release formulation while decreasing the number of experiments based on trial and error approach. Diclofenac matrix tablets were optimized to achieve a release profile conforming to USP monograph, matching Voltaren ® SR and withstand formulation variables. The percent of drug released at predetermined multiple time points were the response variables in the design. Statistical models were obtained with relative contour diagrams being overlaid to predict process and formulation parameters expected to produce the target release profile. Tablets were prepared by wet granulation using mixture of equivalent quantities of Eudragit RL/RS at overall polymer concentration of 10-30%w/w and compressed at 5-15KN. Drug release from the optimized formulation E4 (15%w/w, 15KN) was similar to Voltaren, conformed to USP monograph and found to be stable. Substituting lactose with mannitol, reversing the ratio between lactose and microcrystalline cellulose or increasing drug load showed no significant difference in drug release. Using dextromethorphan hydrobromide as a model soluble drug showed burst release due to higher solubility and formation of micro cavities. A numerical optimization technique was employed to develop a stable consistent promising formulation for sustained delivery of diclofenac.

Analytic Support of Emergency Response and Recovery for the Wide-Area Recovery & Resiliency Program (WARRP) Task 1: Medical Countermeasures Response

DTIC Science & Technology

2012-02-23

time Detect and Characterize Event Multiple Materiel No integration between national biosurveillance systems Could receive disparate signals and the...is very limited in its applicability at this time only being deployable in one city and in the process of being implemented in four more Push models

An Explanatory Item Response Theory Approach for a Computer-Based Case Simulation Test

ERIC Educational Resources Information Center

Kahraman, Nilüfer

2014-01-01

Problem: Practitioners working with multiple-choice tests have long utilized Item Response Theory (IRT) models to evaluate the performance of test items for quality assurance. The use of similar applications for performance tests, however, is often encumbered due to the challenges encountered in working with complicated data sets in which local…

A multiple deficit model of reading disability and attention-deficit/hyperactivity disorder: searching for shared cognitive deficits.

PubMed

McGrath, Lauren M; Pennington, Bruce F; Shanahan, Michelle A; Santerre-Lemmon, Laura E; Barnard, Holly D; Willcutt, Erik G; Defries, John C; Olson, Richard K

2011-05-01

This study tests a multiple cognitive deficit model of reading disability (RD), attention-deficit/hyperactivity disorder (ADHD), and their comorbidity. A structural equation model (SEM) of multiple cognitive risk factors and symptom outcome variables was constructed. The model included phonological awareness as a unique predictor of RD and response inhibition as a unique predictor of ADHD. Processing speed, naming speed, and verbal working memory were modeled as potential shared cognitive deficits. Model fit indices from the SEM indicated satisfactory fit. Closer inspection of the path weights revealed that processing speed was the only cognitive variable with significant unique relationships to RD and ADHD dimensions, particularly inattention. Moreover, the significant correlation between reading and inattention was reduced to non-significance when processing speed was included in the model, suggesting that processing speed primarily accounted for the phenotypic correlation (or comorbidity) between reading and inattention. This study illustrates the power of a multiple deficit approach to complex developmental disorders and psychopathologies, particularly for exploring comorbidities. The theoretical role of processing speed in the developmental pathways of RD and ADHD and directions for future research are discussed. © 2010 The Authors. Journal of Child Psychology and Psychiatry © 2010 Association for Child and Adolescent Mental Health.

Experimental characterization and macro-modeling of mechanical strength of multi-sheets and multi-materials spot welds under pure and mixed modes I and II

NASA Astrophysics Data System (ADS)

Chtourou, Rim; Haugou, Gregory; Leconte, Nicolas; Zouari, Bassem; Chaari, Fahmi; Markiewicz, Eric

2015-09-01

Resistance Spot Welding (RSW) of multiple sheets with multiple materials are increasingly realized in the automotive industry. The mechanical strength of such new generation of spot welded assemblies is not that much dealt with. This is true in particular for experiments dedicated to investigate the mechanical strength of spot weld made by multi sheets of different grades, and their macro modeling in structural computations. Indeed, the most published studies are limited to two sheet assemblies. Therefore, in the first part of this work an advanced experimental set-up with a reduced mass is proposed to characterize the quasi-static and dynamic mechanical behavior and rupture of spot weld made by several sheets of different grades. The proposed device is based on Arcan test, the plates contribution in the global response is, thus, reduced. Loading modes I/II are, therefore, combined and well controlled. In the second part a simplified spot weld connector element (macroscopic modeling) is proposed to describe the nonlinear response and rupture of this new generation of spot welded assemblies. The weld connector model involves several parameters to be set. The remaining parameters are finally identified through a reverse engineering approach using mechanical responses of experimental tests presented in the first part of this work.

Hierarchical neurocomputations underlying concurrent sound segregation: connecting periphery to percept.

PubMed

Bidelman, Gavin M; Alain, Claude

2015-02-01

Natural soundscapes often contain multiple sound sources at any given time. Numerous studies have reported that in human observers, the perception and identification of concurrent sounds is paralleled by specific changes in cortical event-related potentials (ERPs). Although these studies provide a window into the cerebral mechanisms governing sound segregation, little is known about the subcortical neural architecture and hierarchy of neurocomputations that lead to this robust perceptual process. Using computational modeling, scalp-recorded brainstem/cortical ERPs, and human psychophysics, we demonstrate that a primary cue for sound segregation, i.e., harmonicity, is encoded at the auditory nerve level within tens of milliseconds after the onset of sound and is maintained, largely untransformed, in phase-locked activity of the rostral brainstem. As then indexed by auditory cortical responses, (in)harmonicity is coded in the signature and magnitude of the cortical object-related negativity (ORN) response (150-200 ms). The salience of the resulting percept is then captured in a discrete, categorical-like coding scheme by a late negativity response (N5; ~500 ms latency), just prior to the elicitation of a behavioral judgment. Subcortical activity correlated with cortical evoked responses such that weaker phase-locked brainstem responses (lower neural harmonicity) generated larger ORN amplitude, reflecting the cortical registration of multiple sound objects. Studying multiple brain indices simultaneously helps illuminate the mechanisms and time-course of neural processing underlying concurrent sound segregation and may lead to further development and refinement of physiologically driven models of auditory scene analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

ERIC Educational Resources Information Center

Misak, Paul; Cleaveland, J. Mark

2011-01-01

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

Do Recognition and Priming Index a Unitary Knowledge Base? Comment on Shanks et al. (2003)

ERIC Educational Resources Information Center

Runger, Dennis; Nagy, Gabriel; Frensch, Peter A.

2009-01-01

Whether sequence learning entails a single or multiple memory systems is a moot issue. Recently, D. R. Shanks, L. Wilkinson, and S. Channon advanced a single-system model that predicts a perfect correlation between true (i.e., error free) response time priming and recognition. The Shanks model is contrasted with a dual-process model that…

Human Immunity and the Design of Multi-Component, Single Target Vaccines

PubMed Central

Saul, Allan; Fay, Michael P.

2007-01-01

Background Inclusion of multiple immunogens to target a single organism is a strategy being pursued for many experimental vaccines, especially where it is difficult to generate a strongly protective response from a single immunogen. Although there are many human vaccines that contain multiple defined immunogens, in almost every case each component targets a different pathogen. As a consequence, there is little practical experience for deciding where the increased complexity of vaccines with multiple defined immunogens vaccines targeting single pathogens will be justifiable. Methodology/Principal Findings A mathematical model, with immunogenicity parameters derived from a database of human responses to established vaccines, was used to predict the increase in the efficacy and the proportion of the population protected resulting from addition of further immunogens. The gains depended on the relative protection and the range of responses in the population to each immunogen and also to the correlation of the responses between immunogens. In most scenarios modeled, the gain in overall efficacy obtained by adding more immunogens was comparable to gains obtained from a single immunogen through the use of better formulations or adjuvants. Multi-component single target vaccines were more effective at decreasing the proportion of poor responders than increasing the overall efficacy of the vaccine in a population. Conclusions/Significance Inclusion of limited number of antigens in a vaccine aimed at targeting a single organism will increase efficacy, but the gains are relatively modest and for a practical vaccine there are constraints that are likely to limit multi-component single target vaccines to a small number of key antigens. The model predicts that this type of vaccine will be most useful where the critical issue is the reduction in proportion of poor responders. PMID:17786221

Causal Loop Analysis of coastal geomorphological systems

NASA Astrophysics Data System (ADS)

Payo, Andres; Hall, Jim W.; French, Jon; Sutherland, James; van Maanen, Barend; Nicholls, Robert J.; Reeve, Dominic E.

2016-03-01

As geomorphologists embrace ever more sophisticated theoretical frameworks that shift from simple notions of evolution towards single steady equilibria to recognise the possibility of multiple response pathways and outcomes, morphodynamic modellers are facing the problem of how to keep track of an ever-greater number of system feedbacks. Within coastal geomorphology, capturing these feedbacks is critically important, especially as the focus of activity shifts from reductionist models founded on sediment transport fundamentals to more synthesist ones intended to resolve emergent behaviours at decadal to centennial scales. This paper addresses the challenge of mapping the feedback structure of processes controlling geomorphic system behaviour with reference to illustrative applications of Causal Loop Analysis at two study cases: (1) the erosion-accretion behaviour of graded (mixed) sediment beds, and (2) the local alongshore sediment fluxes of sand-rich shorelines. These case study examples are chosen on account of their central role in the quantitative modelling of geomorphological futures and as they illustrate different types of causation. Causal loop diagrams, a form of directed graph, are used to distil the feedback structure to reveal, in advance of more quantitative modelling, multi-response pathways and multiple outcomes. In the case of graded sediment bed, up to three different outcomes (no response, and two disequilibrium states) can be derived from a simple qualitative stability analysis. For the sand-rich local shoreline behaviour case, two fundamentally different responses of the shoreline (diffusive and anti-diffusive), triggered by small changes of the shoreline cross-shore position, can be inferred purely through analysis of the causal pathways. Explicit depiction of feedback-structure diagrams is beneficial when developing numerical models to explore coastal morphological futures. By explicitly mapping the feedbacks included and neglected within a model, the modeller can readily assess if critical feedback loops are included.

Training and generalization of affective behavior displayed by youth with autism.

PubMed Central

Gena, A; Krantz, P J; McClannahan, L E; Poulson, C L

1996-01-01

The purpose of this study was to teach contextually appropriate affective behavior to 4 youths with autism. Treatment consisted of modeling, prompting, and reinforcement introduced in a multiple baseline design across response categories of affective behavior. During treatment, verbal praise and tokens were delivered contingent on appropriate affective responding during training trials. Modeling and verbal prompting were used as correction procedures. Each youth received treatment in either three or four response categories. Treatment systematically increased responding within the response categories for all 4 participants, with effects being specific to the affective response categories under treatment. Treatment effects occurred across untrained scenarios, therapists, time, and settings, suggesting that generalization had occurred. PMID:8926222

Modelling and Optimization of Polycaprolactone Ultrafine-Fibres Electrospinning Process Using Response Surface Methodology

PubMed Central

Ruys, Andrew J.

2018-01-01

Electrospun fibres have gained broad interest in biomedical applications, including tissue engineering scaffolds, due to their potential in mimicking extracellular matrix and producing structures favourable for cell and tissue growth. The development of scaffolds often involves multivariate production parameters and multiple output characteristics to define product quality. In this study on electrospinning of polycaprolactone (PCL), response surface methodology (RSM) was applied to investigate the determining parameters and find optimal settings to achieve the desired properties of fibrous scaffold for acetabular labrum implant. The results showed that solution concentration influenced fibre diameter, while elastic modulus was determined by solution concentration, flow rate, temperature, collector rotation speed, and interaction between concentration and temperature. Relationships between these variables and outputs were modelled, followed by an optimization procedure. Using the optimized setting (solution concentration of 10% w/v, flow rate of 4.5 mL/h, temperature of 45 °C, and collector rotation speed of 1500 RPM), a target elastic modulus of 25 MPa could be achieved at a minimum possible fibre diameter (1.39 ± 0.20 µm). This work demonstrated that multivariate factors of production parameters and multiple responses can be investigated, modelled, and optimized using RSM. PMID:29562614

On the correlation between phase-locking modes and Vibrational Resonance in a neuronal model

NASA Astrophysics Data System (ADS)

Morfu, S.; Bordet, M.

2018-02-01

We numerically and experimentally investigate the underlying mechanism leading to multiple resonances in the FitzHugh-Nagumo model driven by a bichromatic excitation. Using a FitzHugh-Nagumo circuit, we first analyze the number of spikes triggered by the system in response to a single sinusoidal wave forcing. We build an encoding diagram where different phase-locking modes are identified according to the amplitude and frequency of the sinusoidal excitation. Next, we consider the bichromatic driving which consists in a low frequency sinusoidal wave perturbed by an additive high frequency signal. Beside the classical Vibrational Resonance phenomenon, we show in real experiments that multiple resonances can be reached by an appropriate setting of the perturbation parameters. We clearly establish a correlation between these resonances and the encoding diagram of the low frequency signal free FitzHugh-Nagumo model. We show with realistic parameters that sharp transitions of the encoding diagram allow to predict the main resonances. Our experiments are confirmed by numerical simulations of the system response.

Fitness Costs and Diversity of the Cytotoxic T Lymphocyte (CTL) Response Determine the Rate of CTL Escape during Acute and Chronic Phases of HIV Infection▿†

PubMed Central

Ganusov, Vitaly V.; Goonetilleke, Nilu; Liu, Michael K. P.; Ferrari, Guido; Shaw, George M.; McMichael, Andrew J.; Borrow, Persephone; Korber, Bette T.; Perelson, Alan S.

2011-01-01

HIV-1 often evades cytotoxic T cell (CTL) responses by generating variants that are not recognized by CTLs. We used single-genome amplification and sequencing of complete HIV genomes to identify longitudinal changes in the transmitted/founder virus from the establishment of infection to the viral set point at 1 year after the infection. We found that the rate of viral escape from CTL responses in a given patient decreases dramatically from acute infection to the viral set point. Using a novel mathematical model that tracks the dynamics of viral escape at multiple epitopes, we show that a number of factors could potentially contribute to a slower escape in the chronic phase of infection, such as a decreased magnitude of epitope-specific CTL responses, an increased fitness cost of escape mutations, or an increased diversity of the CTL response. In the model, an increase in the number of epitope-specific CTL responses can reduce the rate of viral escape from a given epitope-specific CTL response, particularly if CD8+ T cells compete for killing of infected cells or control virus replication nonlytically. Our mathematical framework of viral escape from multiple CTL responses can be used to predict the breadth and magnitude of HIV-specific CTL responses that need to be induced by vaccination to reduce (or even prevent) viral escape following HIV infection. PMID:21835793

Fitness costs and diversity of the cytotoxic T lymphocyte (CTL) response determine the rate of CTL escape during acute and chronic phases of HIV infection.

PubMed

Ganusov, Vitaly V; Goonetilleke, Nilu; Liu, Michael K P; Ferrari, Guido; Shaw, George M; McMichael, Andrew J; Borrow, Persephone; Korber, Bette T; Perelson, Alan S

2011-10-01

HIV-1 often evades cytotoxic T cell (CTL) responses by generating variants that are not recognized by CTLs. We used single-genome amplification and sequencing of complete HIV genomes to identify longitudinal changes in the transmitted/founder virus from the establishment of infection to the viral set point at 1 year after the infection. We found that the rate of viral escape from CTL responses in a given patient decreases dramatically from acute infection to the viral set point. Using a novel mathematical model that tracks the dynamics of viral escape at multiple epitopes, we show that a number of factors could potentially contribute to a slower escape in the chronic phase of infection, such as a decreased magnitude of epitope-specific CTL responses, an increased fitness cost of escape mutations, or an increased diversity of the CTL response. In the model, an increase in the number of epitope-specific CTL responses can reduce the rate of viral escape from a given epitope-specific CTL response, particularly if CD8+ T cells compete for killing of infected cells or control virus replication nonlytically. Our mathematical framework of viral escape from multiple CTL responses can be used to predict the breadth and magnitude of HIV-specific CTL responses that need to be induced by vaccination to reduce (or even prevent) viral escape following HIV infection.

Exploring the Intrinsic Motivation of Hedonic Information Systems Acceptance: Integrating Hedonic Theory and Flow with TAM

NASA Astrophysics Data System (ADS)

Wang, Zhihuan

Research on Information Systems (IS) acceptance is substantially focused on extrinsic motivation in workplaces, little is known about the underlying intrinsic motivations of Hedonic IS (HIS) acceptance. This paper proposes a hybrid HIS acceptance model which takes the unique characteristics of HIS and multiple identities of a HIS user into consideration by interacting Hedonic theory, Flow theory with Technology Acceptance Model (TAM). The model was empirically tested by a field survey. The result indicates that emotional responses, imaginal responses, and flow experience are three main contributions of HIS acceptance.

Responses to single photons in visual cells of Limulus

PubMed Central

Borsellino, A.; Fuortes, M. G. F.

1968-01-01

1. A system proposed in a previous article as a model of responses of visual cells has been analysed with the purpose of predicting the features of responses to single absorbed photons. 2. As a result of this analysis, the stochastic variability of responses has been expressed as a function of the amplification of the system. 3. The theoretical predictions have been compared to the results obtained by recording electrical responses of visual cells of Limulus to flashes delivering only few photons. 4. Experimental responses to single photons have been tentatively identified and it was shown that the stochastic variability of these responses is similar to that predicted for a model with a multiplication factor of at least twenty-five. 5. These results lead to the conclusion that the processes responsible for visual responses incorporate some form of amplification. This conclusion may prove useful for identifying the physical mechanisms underlying the transducer action of visual cells. PMID:5664231

Climate change and health modeling: horses for courses.

PubMed

Ebi, Kristie L; Rocklöv, Joacim

2014-01-01

Mathematical and statistical models are needed to understand the extent to which weather, climate variability, and climate change are affecting current and may affect future health burdens in the context of other risk factors and a range of possible development pathways, and the temporal and spatial patterns of any changes. Such understanding is needed to guide the design and the implementation of adaptation and mitigation measures. Because each model projection captures only a narrow range of possible futures, and because models serve different purposes, multiple models are needed for each health outcome ('horses for courses'). Multiple modeling results can be used to bracket the ranges of when, where, and with what intensity negative health consequences could arise. This commentary explores some climate change and health modeling issues, particularly modeling exposure-response relationships, developing early warning systems, projecting health risks over coming decades, and modeling to inform decision-making. Research needs are also suggested.

Antimicrobial combinations: Bliss independence and Loewe additivity derived from mechanistic multi-hit models

PubMed Central

Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens

2016-01-01

Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials. This article is part of the themed issue ‘Evolutionary ecology of arthropod antimicrobial peptides’. PMID:27160596

Stutter-Step Models of Performance in School

ERIC Educational Resources Information Center

Morgan, Stephen L.; Leenman, Theodore S.; Todd, Jennifer J.; Kentucky; Weeden, Kim A.

2013-01-01

To evaluate a stutter-step model of academic performance in high school, this article adopts a unique measure of the beliefs of 12,591 high school sophomores from the Education Longitudinal Study, 2002-2006. Verbatim responses to questions on occupational plans are coded to capture specific job titles, the listing of multiple jobs, and the listing…

MR Imaging in Monitoring and Predicting Treatment Response in Multiple Sclerosis.

PubMed

Río, Jordi; Auger, Cristina; Rovira, Àlex

2017-05-01

MR imaging is the most sensitive tool for identifying lesions in patients with multiple sclerosis (MS). MR imaging has also acquired an essential role in the detection of complications arising from these treatments and in the assessment and prediction of efficacy. In the future, other radiological measures that have shown prognostic value may be incorporated within the models for predicting treatment response. This article examines the role of MR imaging as a prognostic tool in patients with MS and the recommendations that have been proposed in recent years to monitor patients who are treated with disease-modifying drugs. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

An Item Response Theory Analysis of Palmore's Facts on Aging Quiz (FAQ) Using the Three Parameter Model.

ERIC Educational Resources Information Center

Obiekwe, Jerry C.

Palmore's Facts on Aging Quiz (FAQ) (E. Palmore, 1977) is an instrument that is used to educate, to measure learning, to test knowledge, to measure attitudes toward aging, and in research. A comparative analysis was performed between the FAQ I and its multiple choice version and the FAQ II and its multiple choice version in terms of their item…

Explaining rapid reinfections in multiple-wave influenza outbreaks: Tristan da Cunha 1971 epidemic as a case study

PubMed Central

Camacho, Anton; Ballesteros, Sébastien; Graham, Andrea L.; Carrat, Fabrice; Ratmann, Oliver; Cazelles, Bernard

2011-01-01

Influenza usually spreads through the human population in multiple-wave outbreaks. Successive reinfection of individuals over a short time interval has been explicitly reported during past pandemics. However, the causes of rapid reinfection and the role of reinfection in driving multiple-wave outbreaks remain poorly understood. To investigate these issues, we focus on a two-wave influenza A/H3N2 epidemic that occurred on the remote island of Tristan da Cunha in 1971. Over 59 days, 273 (96%) of 284 islanders experienced at least one attack and 92 (32%) experienced two attacks. We formulate six mathematical models invoking a variety of antigenic and immunological reinfection mechanisms. Using a maximum-likelihood analysis to confront model predictions with the reported incidence time series, we demonstrate that only two mechanisms can be retained: some hosts with either a delayed or deficient humoral immune response to the primary influenza infection were reinfected by the same strain, thus initiating the second epidemic wave. Both mechanisms are supported by previous empirical studies and may arise from a combination of genetic and ecological causes. We advocate that a better understanding and account of heterogeneity in the human immune response are essential to analysis of multiple-wave influenza outbreaks and pandemic planning. PMID:21525058

Single and multiple phenotype QTL analyses of downy mildew resistance in interspecific grapevines.

PubMed

Divilov, Konstantin; Barba, Paola; Cadle-Davidson, Lance; Reisch, Bruce I

2018-05-01

Downy mildew resistance across days post-inoculation, experiments, and years in two interspecific grapevine F 1 families was investigated using linear mixed models and Bayesian networks, and five new QTL were identified. Breeding grapevines for downy mildew disease resistance has traditionally relied on qualitative gene resistance, which can be overcome by pathogen evolution. Analyzing two interspecific F 1 families, both having ancestry derived from Vitis vinifera and wild North American Vitis species, across 2 years and multiple experiments, we found multiple loci associated with downy mildew sporulation and hypersensitive response in both families using a single phenotype model. The loci explained between 7 and 17% of the variance for either phenotype, suggesting a complex genetic architecture for these traits in the two families studied. For two loci, we used RNA-Seq to detect differentially transcribed genes and found that the candidate genes at these loci were likely not NBS-LRR genes. Additionally, using a multiple phenotype Bayesian network analysis, we found effects between the leaf trichome density, hypersensitive response, and sporulation phenotypes. Moderate-high heritabilities were found for all three phenotypes, suggesting that selection for downy mildew resistance is an achievable goal by breeding for either physical- or non-physical-based resistance mechanisms, with the combination of the two possibly providing durable resistance.

A generic individual-based model to simulate morphogenesis, C-N acquisition and population dynamics in contrasting forage legumes.

PubMed

Louarn, Gaëtan; Faverjon, Lucas

2018-04-18

Individual-based models (IBMs) are promising tools to disentangle plant interactions in multi-species grasslands and foster innovative species mixtures. This study describes an IBM dealing with the morphogenesis, growth and C-N acquisition of forage legumes that integrates plastic responses from functional-structural plant models. A generic model was developed to account for herbaceous legume species with contrasting above- and below-ground morphogenetic syndromes and to integrate the responses of plants to light, water and N. Through coupling with a radiative transfer model and a three-dimensional virtual soil, the model allows dynamic resolution of competition for multiple resources at individual plant level within a plant community. The behaviour of the model was assessed on a range of monospecific stands grown along gradients of light, water and N availability. The model proved able to capture the diversity of morphologies encountered among the forage legumes. The main density-dependent features known about even-age plant populations were correctly anticipated. The model predicted (1) the 'reciprocal yield' law relating average plant mass to density, (2) a self-thinning pattern close to that measured for herbaceous species and (3) consistent changes in the size structure of plant populations with time and pedo-climatic conditions. In addition, plastic changes in the partitioning of dry matter, the N acquisition mode and in the architecture of shoots and roots emerged from the integration of plant responses to their local environment. This resulted in taller plants and thinner roots when competition was dominated by light, and shorter plants with relatively more developed root systems when competition was dominated by soil resources. A population dynamic model considering growth and morphogenesis responses to multiple resources heterogeneously distributed in the environment was presented. It should allow scaling plant-plant interactions from individual to community levels without the inconvenience of average plant models.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

PubMed Central

Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

2016-01-01

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

A three-level atomicity model for decentralized workflow management systems

NASA Astrophysics Data System (ADS)

Ben-Shaul, Israel Z.; Heineman, George T.

1996-12-01

A workflow management system (WFMS) employs a workflow manager (WM) to execute and automate the various activities within a workflow. To protect the consistency of data, the WM encapsulates each activity with a transaction; a transaction manager (TM) then guarantees the atomicity of activities. Since workflows often group several activities together, the TM is responsible for guaranteeing the atomicity of these units. There are scalability issues, however, with centralized WFMSs. Decentralized WFMSs provide an architecture for multiple autonomous WFMSs to interoperate, thus accommodating multiple workflows and geographically-dispersed teams. When atomic units are composed of activities spread across multiple WFMSs, however, there is a conflict between global atomicity and local autonomy of each WFMS. This paper describes a decentralized atomicity model that enables workflow administrators to specify the scope of multi-site atomicity based upon the desired semantics of multi-site tasks in the decentralized WFMS. We describe an architecture that realizes our model and execution paradigm.

Integrative Radiation Biology

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

Barcellos-Hoff, Mary Helen

We plan to study tissue-level mechanisms important to human breast radiation carcinogenesis. We propose that the cell biology of irradiated tissues reveals a coordinated multicellular damage response program in which individual cell contributions are primarily directed towards suppression of carcinogenesis and reestablishment of homeostasis. We identified transforming growth factor β1 (TGFβ) as a pivotal signal. Notably, we have discovered that TGFβ suppresses genomic instability by controlling the intrinsic DNA damage response and centrosome integrity. However, TGFβ also mediates disruption of microenvironment interactions, which drive epithelial to mesenchymal transition in irradiated human mammary epithelial cells. This apparent paradox of positive andmore » negative controls by TGFβ is the topic of the present proposal. First, we postulate that these phenotypes manifest differentially following fractionated or chronic exposures; second, that the interactions of multiple cell types in tissues modify the responses evident in this single cell type culture models. The goals are to: 1) study the effect of low dose rate and fractionated radiation exposure in combination with TGFβ on the irradiated phenotype and genomic instability of non-malignant human epithelial cells; and 2) determine whether stromal-epithelial interactions suppress the irradiated phenotype in cell culture and the humanized mammary mouse model. These data will be used to 3) develop a systems biology model that integrates radiation effects across multiple levels of tissue organization and time. Modeling multicellular radiation responses coordinated via extracellular signaling could have a significant impact on the extrapolation of human health risks from high dose to low dose/rate radiation exposure.« less

Improving the analysis of slug tests

USGS Publications Warehouse

McElwee, C.D.

2002-01-01

This paper examines several techniques that have the potential to improve the quality of slug test analysis. These techniques are applicable in the range from low hydraulic conductivities with overdamped responses to high hydraulic conductivities with nonlinear oscillatory responses. Four techniques for improving slug test analysis will be discussed: use of an extended capability nonlinear model, sensitivity analysis, correction for acceleration and velocity effects, and use of multiple slug tests. The four-parameter nonlinear slug test model used in this work is shown to allow accurate analysis of slug tests with widely differing character. The parameter ?? represents a correction to the water column length caused primarily by radius variations in the wellbore and is most useful in matching the oscillation frequency and amplitude. The water column velocity at slug initiation (V0) is an additional model parameter, which would ideally be zero but may not be due to the initiation mechanism. The remaining two model parameters are A (parameter for nonlinear effects) and K (hydraulic conductivity). Sensitivity analysis shows that in general ?? and V0 have the lowest sensitivity and K usually has the highest. However, for very high K values the sensitivity to A may surpass the sensitivity to K. Oscillatory slug tests involve higher accelerations and velocities of the water column; thus, the pressure transducer responses are affected by these factors and the model response must be corrected to allow maximum accuracy for the analysis. The performance of multiple slug tests will allow some statistical measure of the experimental accuracy and of the reliability of the resulting aquifer parameters. ?? 2002 Elsevier Science B.V. All rights reserved.

Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.

PubMed

Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen

2015-05-01

Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.

An Investigation of the Accuracy of Alternative Methods of True Score Estimation in High-Stakes Mixed-Format Examinations.

ERIC Educational Resources Information Center

Klinger, Don A.; Rogers, W. Todd

2003-01-01

The estimation accuracy of procedures based on classical test score theory and item response theory (generalized partial credit model) were compared for examinations consisting of multiple-choice and extended-response items. Analysis of British Columbia Scholarship Examination results found an error rate of about 10 percent for both methods, with…

catcher: A Software Program to Detect Answer Copying in Multiple-Choice Tests Based on Nominal Response Model

ERIC Educational Resources Information Center

Kalender, Ilker

2012-01-01

catcher is a software program designed to compute the [omega] index, a common statistical index for the identification of collusions (cheating) among examinees taking an educational or psychological test. It requires (a) responses and (b) ability estimations of individuals, and (c) item parameters to make computations and outputs the results of…

Using Multiple Indicators of Cognitive State in Logistic Models that Predict Individual Performance in Machine-Mediated Learning Environments.

ERIC Educational Resources Information Center

Hancock, Thomas E.; And Others

1995-01-01

In machine-mediated learning environments, there is a need for more reliable methods of calculating the probability that a learner's response will be correct in future trials. A combination of domain-independent response-state measures of cognition along with two instructional variables for maximum predictive ability are demonstrated. (Author/LRW)

Sustaining innovations in complex healthcare environments: A multiple-case study of rapid response teams

PubMed Central

Stolldorf, Deonni P; Havens, Donna S.; Jones, Cheryl B

2015-01-01

Objectives Rapid response teams are one innovation previously deployed in U.S. hospitals with the goal to improve the quality of care. Sustaining rapid response teams is important to achieve the desired implementation outcomes, reduce the risk of program investments losses, and prevent employee disillusionment and dissatisfaction. This study sought to examine factors that do and do not support the sustainability of Rapid Response Teams. Methods The study was conceptually guided by an adapted version of the Planning Model of Sustainability. A multiple-case study was conducted using a purposive sample of two hospitals with high RRT sustainability scores and two hospitals with low RRT sustainability scores. Data collection methods included: (a) a hospital questionnaire that was completed by a nurse administrator at each hospital; (b) semi-structured interviews with leaders, RRT members, and those activating RRT calls; and, (c) review of internal documents. Quantitative data were analyzed using descriptive statistics; qualitative data were analyzed using content analysis. Results Few descriptive differences were found between hospitals. However, there were notable differences in the operationalization of certain factors between high- and low-sustainability hospitals. Additional sustainability factors other than those captured by the Planning Model of Sustainability were also identified. Conclusions The sustainability of rapid response teams is optimized through effective operationalization of organizational and project design and implementation factors. Two additional factors—individual and team characteristics—should be included in the Planning Model of Sustainability and considered as potential facilitators (or inhibitors) of RRT sustainability. PMID:26756725

Therapeutic treatment with ascorbate rescues mice from heat stroke-induced death by attenuating systemic inflammatory response and hypothalamic neuronal damage.

PubMed

Chang, Chia-Yu; Chen, Jen-Yin; Chen, Sheng-Hsien; Cheng, Tain-Junn; Lin, Mao-Tsun; Hu, Miao-Lin

2016-04-01

The impact of ascorbate on oxidative stress-related diseases is moderate because of its limited oral bioavailability and rapid clearance. However, recent evidence of the clinical benefit of parenteral vitamin C administration has emerged, especially in critical care. Heatstroke is defined as a form of excessive hyperthermia associated with a systemic inflammatory response that results in multiple organ dysfunctions in which central nervous system disorders such as delirium, convulsions, and coma are predominant. The thermoregulatory, immune, coagulation and tissue injury responses of heatstroke closely resemble those observed during sepsis and are likely mediated by similar cellular mechanisms. This study was performed by using the characteristic high lethality rate and sepsis-mimic systemic inflammatory response of a murine model of heat stroke to test our hypothesis that supra-physiological doses of ascorbate may have therapeutic use in critical care. We demonstrated that parenteral administration of ascorbate abrogated the lethality and thermoregulatory dysfunction in murine model of heat stroke by attenuating heat stroke-induced accelerated systemic inflammatory, coagulation responses and the resultant multiple organ injury, especially in hypothalamus. Overall, our findings support the hypothesis and notion that supra-physiological doses of ascorbate may have therapeutic use in critical care. Copyright © 2016. Published by Elsevier Inc.

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.

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions

PubMed Central

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-01-01

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field. DOI: http://dx.doi.org/10.7554/eLife.08411.001 PMID:26609814

From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

PubMed

Naumann, Eva A; Fitzgerald, James E; Dunn, Timothy W; Rihel, Jason; Sompolinsky, Haim; Engert, Florian

2016-11-03

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data. Copyright © 2016 Elsevier Inc. All rights reserved.

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and related model species

PubMed Central

Modise, David M.; Gemeildien, Junaid; Ndimba, Bongani K.; Christoffels, Alan

2018-01-01

Background Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations. Methods In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO), Trait Ontology (TO), Plant Ontology (PO), Growth Ontology (GRO) and Environment Ontology (EO) were used to semantically integrate drought related information. Results Target genes linked to Quantitative Trait Loci (QTLs) controlling yield and stress tolerance in sorghum (Sorghum bicolor (L.) Moench) and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%), salt (32%), cold (20%), heat (8%) and oxidative stress (25%) were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs associated with different traits that are responsive to multiple stresses. Ontology mapping was used to validate the identified genes, while reconstruction of the phylogenetic tree was instrumental to infer the evolutionary relationship of the sorghum orthologs. The results also show specific genes responsible for various interrelated components of drought response mechanism such as drought tolerance, drought avoidance and drought escape. Conclusions We submit that this approach is novel and to our knowledge, has not been used previously in any other research; it enables us to perform cross-species queries for genes that are likely to be associated with multiple stress tolerance, as a means to identify novel targets for engineering stress resistance in sorghum and possibly, in other crop species. PMID:29590108

Multiple fracturing experiments: propellant and borehole considerations

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

Cuderman, J F

1982-01-01

The technology for multiple fracturing of a wellbore, using progressively burning propellants, is being developed to enhance natural gas recovery. Multiple fracturing appears especially attractive for stimulating naturally fractured reservoirs such as Devonian shales where it is expected to effectively intersect existing fractures and connect them to a wellbore. Previous experiments and modeling efforts defined pressure risetimes required for multiple fracturing as a function of borehole diameter, but identified only a weak dependence on peak pressure attained. Typically, from four to eight equally spaced major fractures occur as a function of pressure risetime and in situ stress orientation. The presentmore » experiments address propellant and rock response considerations required to achieve the desired pressure risetimes for reliable multiple fracturing.« less

The North American Regional Climate Change Assessment Program (NARCCAP): Status and results

NASA Astrophysics Data System (ADS)

Arritt, R.

2009-04-01

NARCCAP is an international program that is generating projections of climate change for the U.S., Canada, and northern Mexico at decision-relevant regional scales. NARCCAP uses multiple limited-area regional climate models (RCMs) nested within multiple atmosphere-ocean general circulation models (AOGCMs). The use of multiple regional and global models allows us to investigate the uncertainty in model responses to future emissions (here, the A2 SRES scenario). The project also includes global time-slice experiments at the same discretization (50 km) using the GFDL atmospheric model (AM2.1) and the NCAR atmospheric model (CAM3). Phase I of the experiment uses the regional models nested within reanalysis in order to establish uncertainty attributable to the RCMs themselves. Phase II of the project then nests the RCMs within results from the current and future runs of the AOGCMs to explore the cascade of uncertainty from the global to the regional models. Phase I has been completed and the results to be shown include findings that spectral nudging is beneficial in some regions but not in others. Phase II is nearing completion and some preliminary results will be shown.

Dynamics of a intraguild predation model with generalist or specialist predator.

PubMed

Kang, Yun; Wedekin, Lauren

2013-11-01

Intraguild predation (IGP) is a combination of competition and predation which is the most basic system in food webs that contains three species where two species that are involved in a predator/prey relationship are also competing for a shared resource or prey. We formulate two intraguild predation (IGP: resource, IG prey and IG predator) models: one has generalist predator while the other one has specialist predator. Both models have Holling-Type I functional response between resource-IG prey and resource-IG predator; Holling-Type III functional response between IG prey and IG predator. We provide sufficient conditions of the persistence and extinction of all possible scenarios for these two models, which give us a complete picture on their global dynamics. In addition, we show that both IGP models can have multiple interior equilibria under certain parameters range. These analytical results indicate that IGP model with generalist predator has "top down" regulation by comparing to IGP model with specialist predator. Our analysis and numerical simulations suggest that: (1) Both IGP models can have multiple attractors with complicated dynamical patterns; (2) Only IGP model with specialist predator can have both boundary attractor and interior attractor, i.e., whether the system has the extinction of one species or the coexistence of three species depending on initial conditions; (3) IGP model with generalist predator is prone to have coexistence of three species.

Application of constraint-based satellite mission planning model in forest fire monitoring

NASA Astrophysics Data System (ADS)

Guo, Bingjun; Wang, Hongfei; Wu, Peng

2017-10-01

In this paper, a constraint-based satellite mission planning model is established based on the thought of constraint satisfaction. It includes target, request, observation, satellite, payload and other elements, with constraints linked up. The optimization goal of the model is to make full use of time and resources, and improve the efficiency of target observation. Greedy algorithm is used in the model solving to make observation plan and data transmission plan. Two simulation experiments are designed and carried out, which are routine monitoring of global forest fire and emergency monitoring of forest fires in Australia. The simulation results proved that the model and algorithm perform well. And the model is of good emergency response capability. Efficient and reasonable plan can be worked out to meet users' needs under complex cases of multiple payloads, multiple targets and variable priorities with this model.

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.

Best practice assessment of disease modelling for infectious disease outbreaks.

PubMed

Dembek, Z F; Chekol, T; Wu, A

2018-05-08

During emerging disease outbreaks, public health, emergency management officials and decision-makers increasingly rely on epidemiological models to forecast outbreak progression and determine the best response to health crisis needs. Outbreak response strategies derived from such modelling may include pharmaceutical distribution, immunisation campaigns, social distancing, prophylactic pharmaceuticals, medical care, bed surge, security and other requirements. Infectious disease modelling estimates are unavoidably subject to multiple interpretations, and full understanding of a model's limitations may be lost when provided from the disease modeller to public health practitioner to government policymaker. We review epidemiological models created for diseases which are of greatest concern for public health protection. Such diseases, whether transmitted from person-to-person (Ebola, influenza, smallpox), via direct exposure (anthrax), or food and waterborne exposure (cholera, typhoid) may cause severe illness and death in a large population. We examine disease-specific models to determine best practices characterising infectious disease outbreaks and facilitating emergency response and implementation of public health policy and disease control measures.

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

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

Common Warming Pattern Emerges Irrespective of Forcing Location

NASA Astrophysics Data System (ADS)

Kang, Sarah M.; Park, Kiwoong; Jin, Fei-Fei; Stuecker, Malte F.

2017-10-01

The Earth's climate is changing due to the existence of multiple radiative forcing agents. It is under question whether different forcing agents perturb the global climate in a distinct way. Previous studies have demonstrated the existence of similar climate response patterns in response to aerosol and greenhouse gas (GHG) forcings. In this study, the sensitivity of tropospheric temperature response patterns to surface heating distributions is assessed by forcing an atmospheric general circulation model coupled to an aquaplanet slab ocean with a wide range of possible forcing patterns. We show that a common climate pattern emerges in response to localized forcing at different locations. This pattern, characterized by enhanced warming in the tropical upper troposphere and the polar lower troposphere, resembles the historical trends from observations and models as well as the future projections. Atmospheric dynamics in combination with thermodynamic air-sea coupling are primarily responsible for shaping this pattern. Identifying this common pattern strengthens our confidence in the projected response to GHG and aerosols in complex climate models.

A semi-analytical model of a time reversal cavity for high-amplitude focused ultrasound applications

NASA Astrophysics Data System (ADS)

Robin, J.; Tanter, M.; Pernot, M.

2017-09-01

Time reversal cavities (TRC) have been proposed as an efficient approach for 3D ultrasound therapy. They allow the precise spatio-temporal focusing of high-power ultrasound pulses within a large region of interest with a low number of transducers. Leaky TRCs are usually built by placing a multiple scattering medium, such as a random rod forest, in a reverberating cavity, and the final peak pressure gain of the device only depends on the temporal length of its impulse response. Such multiple scattering in a reverberating cavity is a complex phenomenon, and optimisation of the device’s gain is usually a cumbersome process, mostly empirical, and requiring numerical simulations with extremely long computation times. In this paper, we present a semi-analytical model for the fast optimisation of a TRC. This model decouples ultrasound propagation in an empty cavity and multiple scattering in a multiple scattering medium. It was validated numerically and experimentally using a 2D-TRC and numerically using a 3D-TRC. Finally, the model was used to determine rapidly the optimal parameters of the 3D-TRC which had been confirmed by numerical simulations.

Using the Graded Response Model to Control Spurious Interactions in Moderated Multiple Regression

ERIC Educational Resources Information Center

Morse, Brendan J.; Johanson, George A.; Griffeth, Rodger W.

2012-01-01

Recent simulation research has demonstrated that using simple raw score to operationalize a latent construct can result in inflated Type I error rates for the interaction term of a moderated statistical model when the interaction (or lack thereof) is proposed at the latent variable level. Rescaling the scores using an appropriate item response…

Modeling species’ realized climatic niche space and predicting their response to global warming for several western forest species with small geographic distributions

Treesearch

Marcus V. Warwell; Gerald E. Rehfeldt; Nicholas L. Crookston

2010-01-01

The Random Forests multiple regression tree was used to develop an empirically based bioclimatic model of the presence-absence of species occupying small geographic distributions in western North America. The species assessed were subalpine larch (Larix lyallii), smooth Arizona cypress (Cupressus arizonica ssp. glabra...

Calibrating Item Families and Summarizing the Results Using Family Expected Response Functions

ERIC Educational Resources Information Center

Sinharay, Sandip; Johnson, Matthew S.; Williamson, David M.

2003-01-01

Item families, which are groups of related items, are becoming increasingly popular in complex educational assessments. For example, in automatic item generation (AIG) systems, a test may consist of multiple items generated from each of a number of item models. Item calibration or scoring for such an assessment requires fitting models that can…

Model-based scenario planning to develop climate change adaptation strategies for rare plant populations in grassland reserves

Treesearch

Laura Phillips-Mao; Susan M. Galatowitsch; Stephanie A. Snyder; Robert G. Haight

2016-01-01

Incorporating climate change into conservation decision-making at site and population scales is challenging due to uncertainties associated with localized climate change impacts and population responses to multiple interacting impacts and adaptation strategies. We explore the use of spatially explicit population models to facilitate scenario analysis, a conservation...

Anticipating Mathematics Performance: A Cross-Validation Comparison of AID3 and Regression. AIR 1988 Annual Forum Paper.

ERIC Educational Resources Information Center

Bloom, Allan M.; And Others

In response to the increasing importance of student performance in required classes, research was conducted to compare two prediction procedures, linear modeling using multiple regression and nonlinear modeling using AID3. Performance in the first college math course (College Mathematics, Calculus, or Business Calculus Matrices) was the dependent…

Asymptotic Standard Errors of Observed-Score Equating with Polytomous IRT Models

ERIC Educational Resources Information Center

Andersson, Björn

2016-01-01

In observed-score equipercentile equating, the goal is to make scores on two scales or tests measuring the same construct comparable by matching the percentiles of the respective score distributions. If the tests consist of different items with multiple categories for each item, a suitable model for the responses is a polytomous item response…

Item Estimates under Low-Stakes Conditions: How Should Omits Be Treated?

ERIC Educational Resources Information Center

DeMars, Christine

Using data from a pilot test of science and math from students in 30 high schools, item difficulties were estimated with a one-parameter model (partial-credit model for the multi-point items). Some items were multiple-choice items, and others were constructed-response items (open-ended). Four sets of estimates were obtained: estimates for males…

Computer simulation of multiple pilots flying a modern high performance helicopter

NASA Technical Reports Server (NTRS)

Zipf, Mark E.; Vogt, William G.; Mickle, Marlin H.; Hoelzeman, Ronald G.; Kai, Fei; Mihaloew, James R.

1988-01-01

A computer simulation of a human response pilot mechanism within the flight control loop of a high-performance modern helicopter is presented. A human response mechanism, implemented by a low order, linear transfer function, is used in a decoupled single variable configuration that exploits the dominant vehicle characteristics by associating cockpit controls and instrumentation with specific vehicle dynamics. Low order helicopter models obtained from evaluations of the time and frequency domain responses of a nonlinear simulation model, provided by NASA Lewis Research Center, are presented and considered in the discussion of the pilot development. Pilot responses and reactions to test maneuvers are presented and discussed. Higher level implementation, using the pilot mechanisms, are discussed and considered for their use in a comprehensive control structure.

Multiple elements of the allergic arm of the immune response modulate autoimmune demyelination

PubMed Central

Pedotti, Rosetta; DeVoss, Jason J.; Youssef, Sawsan; Mitchell, Dennis; Wedemeyer, Jochen; Madanat, Rami; Garren, Hideki; Fontoura, Paulo; Tsai, Mindy; Galli, Stephen J.; Sobel, Raymond A.; Steinman, Lawrence

2003-01-01

Analysis of mRNA from multiple sclerosis lesions revealed increased amounts of transcripts for several genes encoding molecules traditionally associated with allergic responses, including prostaglandin D synthase, histamine receptor type 1 (H1R), platelet activating factor receptor, Ig Fc ɛ receptor 1 (FcɛRI), and tryptase. We now demonstrate that, in the animal model of multiple sclerosis, experimental autoimmune encephalomyelitis (EAE), mediated by T helper 1 (Th1) T cells, histamine receptor 1 and 2 (H1R and H2R) are present on inflammatory cells in brain lesions. Th1 cells reactive to myelin proteolipid protein expressed more H1R and less H2R than Th2 cells. Pyrilamine, an H1R antagonist, blocked EAE, and the platelet activating factor receptor antagonist CV6209 reduced the severity of EAE. EAE severity was also decreased in mice with disruption of the genes encoding Ig FcγRIII or both FcγRIII and FcɛRI. Prostaglandin D synthase and tryptase transcripts were elevated in EAE brain. Taken together, these data reveal extensive involvement of elements of the immune response associated with allergy in autoimmune demyelination. The pathogenesis of demyelination must now be viewed as encompassing elements of both Th1 responses and “allergic” responses. PMID:12576552

ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies.

PubMed

Barnes, Samuel R; Ng, Thomas S C; Santa-Maria, Naomi; Montagne, Axel; Zlokovic, Berislav V; Jacobs, Russell E

2015-06-16

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising technique to characterize pathology and evaluate treatment response. However, analysis of DCE-MRI data is complex and benefits from concurrent analysis of multiple kinetic models and parameters. Few software tools are currently available that specifically focuses on DCE-MRI analysis with multiple kinetic models. Here, we developed ROCKETSHIP, an open-source, flexible and modular software for DCE-MRI analysis. ROCKETSHIP incorporates analyses with multiple kinetic models, including data-driven nested model analysis. ROCKETSHIP was implemented using the MATLAB programming language. Robustness of the software to provide reliable fits using multiple kinetic models is demonstrated using simulated data. Simulations also demonstrate the utility of the data-driven nested model analysis. Applicability of ROCKETSHIP for both preclinical and clinical studies is shown using DCE-MRI studies of the human brain and a murine tumor model. A DCE-MRI software suite was implemented and tested using simulations. Its applicability to both preclinical and clinical datasets is shown. ROCKETSHIP was designed to be easily accessible for the beginner, but flexible enough for changes or additions to be made by the advanced user as well. The availability of a flexible analysis tool will aid future studies using DCE-MRI. A public release of ROCKETSHIP is available at https://github.com/petmri/ROCKETSHIP .

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.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models.

PubMed

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S; Wu, Xiaowei; Müller, Rolf

2018-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models

PubMed Central

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S.; Wu, Xiaowei; Müller, Rolf

2017-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. PMID:29749977

Pharmacokinetic-pharmacodynamic modelling of the antihistaminic (H1) effect of bilastine.

PubMed

Jauregizar, Nerea; de la Fuente, Leire; Lucero, Maria Luisa; Sologuren, Ander; Leal, Nerea; Rodríguez, Mónica

2009-01-01

To model the pharmacokinetic and pharmacodynamic relationship of bilastine, a new histamine H(1) receptor antagonist, from single- and multiple-dose studies in healthy adult subjects. The pharmacokinetic model was developed from different single-dose and multiple-dose studies. In the single-dose studies, a total of 183 subjects received oral doses of bilastine 2.5, 5, 10, 20, 50, 100, 120, 160, 200 and 220 mg. In the multiple-dose studies, 127 healthy subjects received bilastine 10, 20, 40, 50, 80, 100, 140 or 200 mg/day as multiple doses during a 4-, 7- or 14-day period. The pharmacokinetic profile of bilastine was investigated using a simultaneous analysis of all concentration-time data by means of nonlinear mixed-effects modelling population pharmacokinetic software NONMEM version 6.1. Plasma concentrations were modelled according to a two-compartment open model with first-order absorption and elimination. For the pharmacodynamic analysis, the inhibitory effect of bilastine (inhibition of histamine-induced wheal and flare) was assessed on a preselected time schedule, and the predicted typical pharmacokinetic profile (based on the pharmacokinetic model previously developed) was used. An indirect response model was developed to describe the pharmacodynamic relationships between flare or wheal areas and bilastine plasma concentrations. Finally, once values of the concentration that produced 50% inhibition (IC(50)) had been estimated for wheal and flare effects, simulations were carried out to predict plasma concentrations for the doses of bilastine 5, 10 and 20 mg at steady state (72-96 hours). A non-compartmental analysis resulted in linear kinetics of bilastine in the dose range studied. Bilastine was characterized by two-compartmental kinetics with a rapid-absorption phase (first-order absorption rate constant = 1.50 h(-1)), plasma peak concentrations were observed at 1 hour following administration and the maximal response was observed at approximately 4 hours or later. Concerning the selected pharmacodynamic model to fit the data (type I indirect response model), this selection is attributable to the presence of inhibitory bilastine plasma concentrations that decrease the input response function, i.e. the production of the skin reaction. This model resulted in the best fit of wheal and flare data. The estimates (with relative standard errors expressed in percentages in parentheses) of the apparent zero-order rate constant for flare or wheal spontaneous appearance (k(in)), the first-order rate constant for flare or wheal disappearance (k(out)) and bilastine IC(50) values were 0.44 ng/mL/h (14.60%), 1.09 h(-1) (15.14%) and 5.15 ng/mL (16.16%), respectively, for wheal inhibition, and 11.10 ng/mL/h (8.48%), 1.03 h(-1) (8.35%) and 1.25 ng/mL (14.56%), respectively, for flare inhibition. The simulation results revealed that bilastine plasma concentrations do not remain over the IC(50) value throughout the inter-dose period for doses of 5 and 10 mg. However, with a dose of 20 mg of bilastine administered every 24 hours, plasma concentrations remained over the IC(50) value during the considered period for the flare effect, and up to 20 hours for the wheal effect. Pharmacokinetic and pharmacodynamic relationships of bilastine were reliably described with the use of an indirect response pharmacodynamic model; this led to an accurate prediction of the pharmacodynamic activity of bilastine.

Using Video Modeling as an Anti-bullying Intervention for Children with Autism Spectrum Disorder.

PubMed

Rex, Catherine; Charlop, Marjorie H; Spector, Vicki

2018-03-07

In the present study, we used a multiple baseline design across participants to assess the efficacy of a video modeling intervention to teach six children with autism spectrum disorder (ASD) to assertively respond to bullying. During baseline, the children made few appropriate responses upon viewing video clips of bullying scenarios. During the video modeling intervention, participants viewed videos of models assertively responding to three types of bullying: physical, verbal bullying, and social exclusion. Results indicated that all six children learned through video modeling to make appropriate assertive responses to bullying scenarios. Four of the six children demonstrated learning in the in situ bullying probes. The results are discussed in terms of an intervention for victims of bullying with ASD.

Visual Attention Model Based on Statistical Properties of Neuron Responses

PubMed Central

Duan, Haibin; Wang, Xiaohua

2015-01-01

Visual attention is a mechanism of the visual system that can select relevant objects from a specific scene. Interactions among neurons in multiple cortical areas are considered to be involved in attentional allocation. However, the characteristics of the encoded features and neuron responses in those attention related cortices are indefinite. Therefore, further investigations carried out in this study aim at demonstrating that unusual regions arousing more attention generally cause particular neuron responses. We suppose that visual saliency is obtained on the basis of neuron responses to contexts in natural scenes. A bottom-up visual attention model is proposed based on the self-information of neuron responses to test and verify the hypothesis. Four different color spaces are adopted and a novel entropy-based combination scheme is designed to make full use of color information. Valuable regions are highlighted while redundant backgrounds are suppressed in the saliency maps obtained by the proposed model. Comparative results reveal that the proposed model outperforms several state-of-the-art models. This study provides insights into the neuron responses based saliency detection and may underlie the neural mechanism of early visual cortices for bottom-up visual attention. PMID:25747859

Relationship between cognitive emotion regulation, social support, resilience and acute stress responses in Chinese soldiers: Exploring multiple mediation model.

PubMed

Cai, Wen-Peng; Pan, Yu; Zhang, Shui-Miao; Wei, Cun; Dong, Wei; Deng, Guang-Hui

2017-10-01

The current study aimed to explore the association of cognitive emotion regulation, social support, resilience and acute stress responses in Chinese soldiers and to understand the multiple mediation effects of social support and resilience on the relationship between cognitive emotion regulation and acute stress responses. A total of 1477 male soldiers completed mental scales, including the cognitive emotion regulation questionnaire-Chinese version, the perceived social support scale, the Chinese version of the Connor-Davidson resilience scale, and the military acute stress scale. As hypothesized, physiological responses, psychological responses, and acute stress were associated with negative-focused cognitive emotion regulation, and negatively associated with positive-focused cognitive emotion regulation, social supports and resilience. Besides, positive-focused cognitive emotion regulation, social support, and resilience were significantly associated with one another, and negative-focused cognitive emotion regulation was negatively associated with social support. Regression analysis and bootstrap analysis showed that social support and resilience had partly mediating effects on negative strategies and acute stress, and fully mediating effects on positive strategies and acute stress. These results thus indicate that military acute stress is significantly associated with cognitive emotion regulation, social support, and resilience, and that social support and resilience have multiple mediation effects on the relationship between cognitive emotion regulation and acute stress responses. Copyright © 2017 Elsevier B.V. All rights reserved.

Neuron’s eye view: Inferring features of complex stimuli from neural responses

PubMed Central

Chen, Xin; Beck, Jeffrey M.

2017-01-01

Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world—contrast and luminance for vision, pitch and intensity for sound—and assemble a stimulus set that systematically varies along these dimensions. Subsequent analysis of neural responses to these stimuli typically focuses on regression models, with experimenter-controlled features as predictors and spike counts or firing rates as responses. Unfortunately, this approach requires knowledge in advance about the relevant features coded by a given population of neurons. For domains as complex as social interaction or natural movement, however, the relevant feature space is poorly understood, and an arbitrary a priori choice of features may give rise to confirmation bias. Here, we present a Bayesian model for exploratory data analysis that is capable of automatically identifying the features present in unstructured stimuli based solely on neuronal responses. Our approach is unique within the class of latent state space models of neural activity in that it assumes that firing rates of neurons are sensitive to multiple discrete time-varying features tied to the stimulus, each of which has Markov (or semi-Markov) dynamics. That is, we are modeling neural activity as driven by multiple simultaneous stimulus features rather than intrinsic neural dynamics. We derive a fast variational Bayesian inference algorithm and show that it correctly recovers hidden features in synthetic data, as well as ground-truth stimulus features in a prototypical neural dataset. To demonstrate the utility of the algorithm, we also apply it to cluster neural responses and demonstrate successful recovery of features corresponding to monkeys and faces in the image set. PMID:28827790

Calibrating the Medical Council of Canada's Qualifying Examination Part I using an integrated item response theory framework: a comparison of models and designs.

PubMed

De Champlain, Andre F; Boulais, Andre-Philippe; Dallas, Andrew

2016-01-01

The aim of this research was to compare different methods of calibrating multiple choice question (MCQ) and clinical decision making (CDM) components for the Medical Council of Canada's Qualifying Examination Part I (MCCQEI) based on item response theory. Our data consisted of test results from 8,213 first time applicants to MCCQEI in spring and fall 2010 and 2011 test administrations. The data set contained several thousand multiple choice items and several hundred CDM cases. Four dichotomous calibrations were run using BILOG-MG 3.0. All 3 mixed item format (dichotomous MCQ responses and polytomous CDM case scores) calibrations were conducted using PARSCALE 4. The 2-PL model had identical numbers of items with chi-square values at or below a Type I error rate of 0.01 (83/3,499 or 0.02). In all 3 polytomous models, whether the MCQs were either anchored or concurrently run with the CDM cases, results suggest very poor fit. All IRT abilities estimated from dichotomous calibration designs correlated very highly with each other. IRT-based pass-fail rates were extremely similar, not only across calibration designs and methods, but also with regard to the actual reported decision to candidates. The largest difference noted in pass rates was 4.78%, which occurred between the mixed format concurrent 2-PL graded response model (pass rate= 80.43%) and the dichotomous anchored 1-PL calibrations (pass rate= 85.21%). Simpler calibration designs with dichotomized items should be implemented. The dichotomous calibrations provided better fit of the item response matrix than more complex, polytomous calibrations.

Anti-synchronization control of BAM memristive neural networks with multiple proportional delays and stochastic perturbations

NASA Astrophysics Data System (ADS)

Wang, Weiping; Yuan, Manman; Luo, Xiong; Liu, Linlin; Zhang, Yao

2018-01-01

Proportional delay is a class of unbounded time-varying delay. A class of bidirectional associative memory (BAM) memristive neural networks with multiple proportional delays is concerned in this paper. First, we propose the model of BAM memristive neural networks with multiple proportional delays and stochastic perturbations. Furthermore, by choosing suitable nonlinear variable transformations, the BAM memristive neural networks with multiple proportional delays can be transformed into the BAM memristive neural networks with constant delays. Based on the drive-response system concept, differential inclusions theory and Lyapunov stability theory, some anti-synchronization criteria are obtained. Finally, the effectiveness of proposed criteria are demonstrated through numerical examples.

The Relationship of Item-Level Response Times with Test-Taker and Item Variables in an Operational CAT Environment. LSAC Research Report Series.

ERIC Educational Resources Information Center

Swygert, Kimberly A.

In this study, data from an operational computerized adaptive test (CAT) were examined in order to gather information concerning item response times in a CAT environment. The CAT under study included multiple-choice items measuring verbal, quantitative, and analytical reasoning. The analyses included the fitting of regression models describing the…

Proceedings of the 2006 Toxicology and Risk Assessment Conference: Applying Mode of Action in Risk Assessment

DTIC Science & Technology

2006-07-01

physiologically-based pharmacokinetic modeling of interactions and multiple route exposure assessment; and integrating relative potency factors with response...defaults, while at the other end is the use of extensive chemical-specific data in physiologically based pharmacokinetic (PBPK) modeling or even...for internal dosimetry as well as an in depth prospective on the use and limitations of physiologically based pharmacokinetic (PBPK) models in

Spontaneous onset and transplant models of the Vk*MYC mouse show immunological sequelae comparable to human multiple myeloma.

PubMed

Cooke, Rachel E; Gherardin, Nicholas A; Harrison, Simon J; Quach, Hang; Godfrey, Dale I; Prince, Miles; Koldej, Rachel; Ritchie, David S

2016-09-06

The Vk*MYC transgenic and transplant mouse models of multiple myeloma (MM) are well established as a research tool for anti-myeloma drug discovery. However, little is known of the immune response in these models. Understanding the immunological relevance of these models is of increasing importance as immunotherapeutic drugs are developed against MM. We set out to examine how cellular immunity is affected in Vk*MYC mouse models and compare that to the immunology of patients with newly diagnosed and relapsed/refractory MM. We found that there were significant immunological responses in mice developing either spontaneous (transgenic) or transplanted MM as a consequence of the degree of tumor burden. Particularly striking were the profound B cell lymphopenia and the expansion of CD8(+) effector memory T cells within the lymphocyte population that progressively developed with advancing disease burden, mirroring changes seen in human MM. High disease burden was also associated with increased inflammatory cytokine production by T lymphocytes, which is more fitting with relapsed/refractory MM in humans. These findings have important implications for the application of this mouse model in the development of MM immunotherapies. Trial registration LitVacc ANZCTR trial ID ACTRN12613000344796; RevLite ANZCTR trial ID NCT00482261.

An airport community noise-impact assessment model

NASA Technical Reports Server (NTRS)

Deloach, R.

1980-01-01

A computer model was developed to assess the noise impact of an airport on the community which it serves. Assessments are made using the Fractional Impact Method by which a single number describes the community aircraft noise environment in terms of exposed population and multiple event noise level. The model is comprised of three elements: a conventional noise footprint model, a site specific population distribution model, and a dose response transfer function. The footprint model provides the noise distribution for a given aircraft operating scenario. This is combined with the site specific population distribution obtained from a national census data base to yield the number of residents exposed to a given level of noise. The dose response relationship relates noise exposure levels to the percentage of individuals highly annoyed by those levels.

Quantitative Models for the Narragansett Bay Estuary, Rhode Island/Massachusetts, USA

EPA Science Inventory

Multiple drivers, including nutrient loading and climate change, affect the Narragansett Bay ecosystem in Rhode Island/Massachusetts, USA. Managers are interested in understanding the timing and magnitude of these effects, and ecosystem responses to restoration actions. To provid...

Using Gaming To Help Nursing Students Understand Ethics.

ERIC Educational Resources Information Center

Metcalf, Barbara L.; Yankou, Dawn

2003-01-01

An ethics game involves nursing students in defending actions in ethics-based scenarios. Benefits include increased confidence, ability to see multiple perspectives, values clarification, and exposure to decision-making models, professional responsibilities, ethical principles, social expectations, and legal requirements. Difficulties include…

From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild.

PubMed

Asthana, Akshay; Zafeiriou, Stefanos; Tzimiropoulos, Georgios; Cheng, Shiyang; Pantic, Maja

2015-06-01

We propose a face alignment framework that relies on the texture model generated by the responses of discriminatively trained part-based filters. Unlike standard texture models built from pixel intensities or responses generated by generic filters (e.g. Gabor), our framework has two important advantages. First, by virtue of discriminative training, invariance to external variations (like identity, pose, illumination and expression) is achieved. Second, we show that the responses generated by discriminatively trained filters (or patch-experts) are sparse and can be modeled using a very small number of parameters. As a result, the optimization methods based on the proposed texture model can better cope with unseen variations. We illustrate this point by formulating both part-based and holistic approaches for generic face alignment and show that our framework outperforms the state-of-the-art on multiple "wild" databases. The code and dataset annotations are available for research purposes from http://ibug.doc.ic.ac.uk/resources.

Temporal analysis of floodwater volumes in New Orleans after Hurricane Katrina: Chapter 3H in Science and the storms-the USGS response to the hurricanes of 2005

USGS Publications Warehouse

Smith, Jodie; Rowland, James

2007-01-01

Satellite images from multiple sensors and dates were analyzed to measure the extent of flooding caused by Hurricane Katrina in the New Orleans, La., area. The flood polygons were combined with a high-resolution digital elevation model to estimate water depths and volumes in designated areas. The multiple satellite acquisitions enabled monitoring of the floodwater volume and extent through time.

Dynamic Resource Allocation in Disaster Response: Tradeoffs in Wildfire Suppression

PubMed Central

Petrovic, Nada; Alderson, David L.; Carlson, Jean M.

2012-01-01

Challenges associated with the allocation of limited resources to mitigate the impact of natural disasters inspire fundamentally new theoretical questions for dynamic decision making in coupled human and natural systems. Wildfires are one of several types of disaster phenomena, including oil spills and disease epidemics, where (1) the disaster evolves on the same timescale as the response effort, and (2) delays in response can lead to increased disaster severity and thus greater demand for resources. We introduce a minimal stochastic process to represent wildfire progression that nonetheless accurately captures the heavy tailed statistical distribution of fire sizes observed in nature. We then couple this model for fire spread to a series of response models that isolate fundamental tradeoffs both in the strength and timing of response and also in division of limited resources across multiple competing suppression efforts. Using this framework, we compute optimal strategies for decision making scenarios that arise in fire response policy. PMID:22514605

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

PubMed Central

Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Sakai, Ko; Fukai, Tomoki

2013-01-01

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception. PMID:24324628

Utilizing the PREPaRE Model When Multiple Classrooms Witness a Traumatic Event

ERIC Educational Resources Information Center

Bernard, Lisa J.; Rittle, Carrie; Roberts, Kathy

2011-01-01

This article presents an account of how the Charleston County School District responded to an event by utilizing the PREPaRE model (Brock, et al., 2009). The acronym, PREPaRE, refers to a range of crisis response activities: P (prevent and prepare for psychological trauma), R (reaffirm physical health and perceptions of security and safety), E…

Computerized Classification Testing under the One-Parameter Logistic Response Model with Ability-Based Guessing

ERIC Educational Resources Information Center

Wang, Wen-Chung; Huang, Sheng-Yun

2011-01-01

The one-parameter logistic model with ability-based guessing (1PL-AG) has been recently developed to account for effect of ability on guessing behavior in multiple-choice items. In this study, the authors developed algorithms for computerized classification testing under the 1PL-AG and conducted a series of simulations to evaluate their…

Identification of measurement differences between English and Spanish language versions of the Mini-Mental State Examination. Detecting differential item functioning using MIMIC modeling.

PubMed

Jones, Richard N

2006-11-01

Knowledge of the extent to which measurement of adult cognitive functioning differs between Spanish and English language administrations of the Mini-Mental State Examination (MMSE) is critical for inclusive, representative, and valid research of older adults in the United States. We sought to demonstrate the use of an item response theory (IRT) based structural equation model, that is, the MIMIC model (multiple indicators, multiple causes), to evaluate MMSE responses for evidence of differential item functioning (DIF) attributable to language of administration. We studied participants in a dementia case registry study (n = 1546), 42% of whom were examined with the Spanish language MMSE. Twelve of 21 items were identified as having significant uniform DIF. The 4 most discrepant included orientation to season, orientation to state, repeat phrase, and follow command. DIF accounted for two-thirds of the observed difference in underlying level of cognitive functioning between Spanish- and English-language administration groups. Failing to account for measurement differences may lead to spurious inferences regarding language group differences in level of underlying level of cognitive functioning. The MIMIC model can be used to detect and adjust for such measurement differences in substantive research.

Expression Profile of BCL-2, BCL-XL, and MCL-1 Predicts Pharmacological Response to the BCL-2 Selective Antagonist Venetoclax in Multiple Myeloma Models.

PubMed

Punnoose, Elizabeth A; Leverson, Joel D; Peale, Franklin; Boghaert, Erwin R; Belmont, Lisa D; Tan, Nguyen; Young, Amy; Mitten, Michael; Ingalla, Ellen; Darbonne, Walter C; Oleksijew, Anatol; Tapang, Paul; Yue, Peng; Oeh, Jason; Lee, Leslie; Maiga, Sophie; Fairbrother, Wayne J; Amiot, Martine; Souers, Andrew J; Sampath, Deepak

2016-05-01

BCL-2 family proteins dictate survival of human multiple myeloma cells, making them attractive drug targets. Indeed, multiple myeloma cells are sensitive to antagonists that selectively target prosurvival proteins such as BCL-2/BCL-XL (ABT-737 and ABT-263/navitoclax) or BCL-2 only (ABT-199/GDC-0199/venetoclax). Resistance to these three drugs is mediated by expression of MCL-1. However, given the selectivity profile of venetoclax it is unclear whether coexpression of BCL-XL also affects antitumor responses to venetoclax in multiple myeloma. In multiple myeloma cell lines (n = 21), BCL-2 is expressed but sensitivity to venetoclax correlated with high BCL-2 and low BCL-XL or MCL-1 expression. Multiple myeloma cells that coexpress BCL-2 and BCL-XL were resistant to venetoclax but sensitive to a BCL-XL-selective inhibitor (A-1155463). Multiple myeloma xenograft models that coexpressed BCL-XL or MCL-1 with BCL-2 were also resistant to venetoclax. Resistance to venetoclax was mitigated by cotreatment with bortezomib in xenografts that coexpressed BCL-2 and MCL-1 due to upregulation of NOXA, a proapoptotic factor that neutralizes MCL-1. In contrast, xenografts that expressed BCL-XL, MCL-1, and BCL-2 were more sensitive to the combination of bortezomib with a BCL-XL selective inhibitor (A-1331852) but not with venetoclax cotreatment when compared with monotherapies. IHC of multiple myeloma patient bone marrow biopsies and aspirates (n = 95) revealed high levels of BCL-2 and BCL-XL in 62% and 43% of evaluable samples, respectively, while 34% were characterized as BCL-2(High)/BCL-XL (Low) In addition to MCL-1, our data suggest that BCL-XL may also be a potential resistance factor to venetoclax monotherapy and in combination with bortezomib. Mol Cancer Ther; 15(5); 1132-44. ©2016 AACR. ©2016 American Association for Cancer Research.

Development of Web tools to predict axillary lymph node metastasis and pathological response to neoadjuvant chemotherapy in breast cancer patients.

PubMed

Sugimoto, Masahiro; Takada, Masahiro; Toi, Masakazu

2014-12-09

Nomograms are a standard computational tool to predict the likelihood of an outcome using multiple available patient features. We have developed a more powerful data mining methodology, to predict axillary lymph node (AxLN) metastasis and response to neoadjuvant chemotherapy (NAC) in primary breast cancer patients. We developed websites to use these tools. The tools calculate the probability of AxLN metastasis (AxLN model) and pathological complete response to NAC (NAC model). As a calculation algorithm, we employed a decision tree-based prediction model known as the alternative decision tree (ADTree), which is an analog development of if-then type decision trees. An ensemble technique was used to combine multiple ADTree predictions, resulting in higher generalization abilities and robustness against missing values. The AxLN model was developed with training datasets (n=148) and test datasets (n=143), and validated using an independent cohort (n=174), yielding an area under the receiver operating characteristic curve (AUC) of 0.768. The NAC model was developed and validated with n=150 and n=173 datasets from a randomized controlled trial, yielding an AUC of 0.787. AxLN and NAC models require users to input up to 17 and 16 variables, respectively. These include pathological features, including human epidermal growth factor receptor 2 (HER2) status and imaging findings. Each input variable has an option of "unknown," to facilitate prediction for cases with missing values. The websites developed facilitate the use of these tools, and serve as a database for accumulating new datasets.

2D and 3D separate and joint inversion of airborne ZTEM and ground AMT data: Synthetic model studies

NASA Astrophysics Data System (ADS)

Sasaki, Yutaka; Yi, Myeong-Jong; Choi, Jihyang

2014-05-01

The ZTEM (Z-axis Tipper Electromagnetic) method measures naturally occurring audio-frequency magnetic fields and obtains the tipper function that defines the relationship among the three components of the magnetic field. Since the anomalous tipper responses are caused by the presence of lateral resistivity variations, the ZTEM survey is most suited for detecting and delineating conductive bodies extending to considerable depths, such as graphitic dykes encountered in the exploration of unconformity type uranium deposit. Our simulations shows that inversion of ZTEM data can detect reasonably well multiple conductive dykes placed 1 km apart. One important issue regarding ZTEM inversion is the effect of the initial model, because homogeneous half-space and (1D) layered structures produce no responses. For the 2D model with multiple conductive dykes, the inversion results were useful for locating the dykes even when the initial model was not close to the true background resistivity. For general 3D structures, however, the resolution of the conductive bodies can be reduced considerably depending on the initial model. This is because the tipper magnitudes from 3D conductors are smaller due to boundary charges than the 2D responses. To alleviate this disadvantage of ZTEM surveys, we combined ZTEM and audio-frequency magnetotelluric (AMT) data. Inversion of sparse AMT data was shown to be effective in providing a good initial model for ZTEM inversion. Moreover, simultaneously inverting both data sets led to better results than the sequential approach by enabling to identify structural features that were difficult to resolve from the individual data sets.

Multiple Consecutive Infections Might Explain the Lack of Protection by BCG

PubMed Central

Cardona, Pere-Joan; Vilaplana, Cristina

2014-01-01

Although contacts between tuberculosis patients may result in multiple consecutive infections (MCI), no experimental animal models consider this fact when used in basic studies. Moreover, the current TB vaccine (BCG) has demonstrated a limited protection in humans. In this study we evaluate the effect of tuberculosis MCI by way of a simple mathematical analysis using data from the low dose aerosol murine experimental model. The results show that a higher number of, or shorter intervals between, multiple consecutive infections reduce the protective effect of BCG. This is due to both the increase in bacillary load at the stationary level of the infection, and the protective immune response induced by the infection itself. This factor must therefore be taken into account when designing new prophylactic strategies as candidate vaccines for the replacement of BCG. PMID:24740286

Multiple consecutive infections might explain the lack of protection by BCG.

PubMed

Cardona, Pere-Joan; Vilaplana, Cristina

2014-01-01

Although contacts between tuberculosis patients may result in multiple consecutive infections (MCI), no experimental animal models consider this fact when used in basic studies. Moreover, the current TB vaccine (BCG) has demonstrated a limited protection in humans. In this study we evaluate the effect of tuberculosis MCI by way of a simple mathematical analysis using data from the low dose aerosol murine experimental model. The results show that a higher number of, or shorter intervals between, multiple consecutive infections reduce the protective effect of BCG. This is due to both the increase in bacillary load at the stationary level of the infection, and the protective immune response induced by the infection itself. This factor must therefore be taken into account when designing new prophylactic strategies as candidate vaccines for the replacement of BCG.

Scalable and responsive event processing in the cloud

PubMed Central

Suresh, Visalakshmi; Ezhilchelvan, Paul; Watson, Paul

2013-01-01

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

Comparative functional genomics of salt stress in related model and cultivated plants identifies and overcomes limitations to translational genomics.

PubMed

Sanchez, Diego H; Pieckenstain, Fernando L; Szymanski, Jedrzey; Erban, Alexander; Bromke, Mariusz; Hannah, Matthew A; Kraemer, Ute; Kopka, Joachim; Udvardi, Michael K

2011-02-14

One of the objectives of plant translational genomics is to use knowledge and genes discovered in model species to improve crops. However, the value of translational genomics to plant breeding, especially for complex traits like abiotic stress tolerance, remains uncertain. Using comparative genomics (ionomics, transcriptomics and metabolomics) we analyzed the responses to salinity of three model and three cultivated species of the legume genus Lotus. At physiological and ionomic levels, models responded to salinity in a similar way to crop species, and changes in the concentration of shoot Cl(-) correlated well with tolerance. Metabolic changes were partially conserved, but divergence was observed amongst the genotypes. Transcriptome analysis showed that about 60% of expressed genes were responsive to salt treatment in one or more species, but less than 1% was responsive in all. Therefore, genotype-specific transcriptional and metabolic changes overshadowed conserved responses to salinity and represent an impediment to simple translational genomics. However, 'triangulation' from multiple genotypes enabled the identification of conserved and tolerant-specific responses that may provide durable tolerance across species.

Evolution of mechanical response of sodium montmorillonite interlayer with increasing hydration by molecular dynamics.

PubMed

Schmidt, Steven R; Katti, Dinesh R; Ghosh, Pijush; Katti, Kalpana S

2005-08-16

The mechanical response of the interlayer of hydrated montmorillonite was evaluated using steered molecular dynamics. An atomic model of the sodium montmorillonite was previously constructed. In the current study, the interlayer of the model was hydrated with multiple layers of water. Using steered molecular dynamics, external forces were applied to individual atoms of the clay surface, and the response of the model was studied. The displacement versus applied stress and stress versus strain relationships of various parts of the interlayer were studied. The paper describes the construction of the model, the simulation procedure, and results of the simulations. Some results of the previous work are further interpreted in the light of the current research. The simulations provide quantitative stress deformation relationships as well as an insight into the molecular interactions taking place between the clay surface and interlayer water and cations.

Modeling a Civil Event Case Study for Consequence Management Using the IMPRINT Forces Module

NASA Technical Reports Server (NTRS)

Gacy, Marc; Gosakan, Mala; Eckdahl, Angela; Miller, Jeffrey R.

2012-01-01

A critical challenge in the Consequence Management (CM) domain is the appropriate allocation of necessary and skilled military and civilian personnel and materiel resources in unexpected emergencies. To aid this process we used the Forces module in the Improved Performance Research Integration Tool (IMPRINT). This module enables analysts to enter personnel and equipment capabilities, prioritized schedules and numbers available, along with unexpected emergency requirements in order to assess force response requirements. Using a suspected terrorist threat on a college campus, we developed a test case model which exercised the capabilities of the module, including the scope and scale of operations. The model incorporates data from multiple sources, including daily schedules and frequency of events such as fire calls. Our preliminary results indicate that the model can predict potential decreases in civilian emergency response coverage due to an involved unplanned incident requiring significant portions of police, fire and civil responses teams.

Reassessment of Non-Monosynaptic Excitation from the Motor Cortex to Motoneurons in Single Motor Units of the Human Biceps Brachii

PubMed Central

Nakajima, Tsuyoshi; Tazoe, Toshiki; Sakamoto, Masanori; Endoh, Takashi; Shibuya, Satoshi; Elias, Leonardo A.; Mezzarane, Rinaldo A.; Komiyama, Tomoyoshi; Ohki, Yukari

2017-01-01

Corticospinal excitation is mediated by polysynaptic pathways in several vertebrates, including dexterous monkeys. However, indirect non-monosynaptic excitation has not been clearly observed following transcranial electrical stimulation (TES) or cervicomedullary stimulation (CMS) in humans. The present study evaluated indirect motor pathways in normal human subjects by recording the activities of single motor units (MUs) in the biceps brachii (BB) muscle. The pyramidal tract was stimulated with weak TES, CMS, and transcranial magnetic stimulation (TMS) contralateral to the recording side. During tasks involving weak co-contraction of the BB and hand muscles, all stimulation methods activated MUs with short latencies. Peristimulus time histograms (PSTHs) showed that responses with similar durations were induced by TES (1.9 ± 1.4 ms) and CMS (2.0 ± 1.4 ms), and these responses often showed multiple peaks with the PSTH peak having a long duration (65.3% and 44.9%, respectively). Such long-duration excitatory responses with multiple peaks were rarely observed in the finger muscles following TES or in the BB following stimulation of the Ia fibers. The responses obtained with TES were compared in the same 14 BB MUs during the co-contraction and isolated BB contraction tasks. Eleven and three units, respectively, exhibited activation with multiple peaks during the two tasks. In order to determine the dispersion effects on the axon conduction velocities (CVs) and synaptic noise, a simulation study that was comparable to the TES experiments was performed with a biologically plausible neuromuscular model. When the model included the monosynaptic-pyramidal tract, multiple peaks were obtained in about 34.5% of the motoneurons (MNs). The experimental and simulation results indicated the existence of task-dependent disparate inputs from the pyramidal tract to the MNs of the upper limb. These results suggested that intercalated interneurons are present in the spinal cord and that these interneurons might be equivalent to those identified in animal experiments. PMID:28194103

The development of interior noise and vibration criteria

NASA Technical Reports Server (NTRS)

Leatherwood, J. D.; Clevenson, S. A.; Stephens, D. G.

1990-01-01

A generalized model was developed for estimating passenger discomfort response to combined noise and vibration. This model accounts for broadband noise and vibration spectra and multiple axes of vibration as well as the interactive effects of combined noise and vibration. The model has the unique capability of transforming individual components of noise/vibration environment into subjective comfort units and then combining these comfort units to produce a total index of passenger discomfort and useful sub-indices that typify passenger comfort within the environment. An overview of the model development is presented including the methodology employed, major elements of the model, model applications, and a brief description of a commercially available portable ride comfort meter based directly upon the model algorithms. Also discussed are potential criteria formats that account for the interactive effects of noise and vibration on human discomfort response.

A diversity index for model space selection in the estimation of benchmark and infectious doses via model averaging.

PubMed

Kim, Steven B; Kodell, Ralph L; Moon, Hojin

2014-03-01

In chemical and microbial risk assessments, risk assessors fit dose-response models to high-dose data and extrapolate downward to risk levels in the range of 1-10%. Although multiple dose-response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose-response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA. © 2013 Society for Risk Analysis.

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

Induction of anti-glioma NK cell response following multiple low-dose intracerebral CpG therapy

PubMed Central

Alizadeh, Darya; Zhang, Leying; Brown, Christine E.; Farrukh, Omar; Jensen, Michael C.; Badie, Behnam

2010-01-01

Purpose Stimulation of toll-like receptor-9 (TLR9) by CpG oligodeoxynucleotides (CpG-ODN) has been shown to counteract the immunosuppressive microenvironment and to inhibit tumor growth in glioma models. These studies, however, have used high doses of CpG-ODN which can induce toxicity in a clinical setting. The goal of this study was to evaluate the anti-tumor efficacy of multiple low-dose intratumoral CpG- ODN in a glioma model. Experimental Design Mice bearing four-day old intracranial GL261 gliomas received a single or multiple (two or four) intratumoral injections of CpG-ODN (3 μg) every 4 days. Tumor growth was measured by bioluminescent imaging, brain histology, and animal survival. Flow cytometry and cytotoxicity assays were used to assess anti-glioma immune response. Results Two and four intracranial injections of low-dose CpG-ODN, but not a single injection, eradicated gliomas in 70% of mice. Moreover, surviving animals exhibited durable tumor free remission (> 3 months), and were protected from intracranial rechallenge with GL21 gliomas, demonstrating the capacity for long-term anti-tumor immunity. Although most inflammatory cells appeared to increase, activated NK cells (i.e. NK+CD107a+) were more frequent than CD8+CD107a+ in the brains of rechallenged CpG-ODN-treated animals and demonstrated a stronger in vitro cytotoxicity against GL261 target cells. Leukocyte depletion studies confirmed that NK cells played an important role in the initial CpG-ODN anti-tumor response, but both CD8 and NK cells were equally important in long-term immunity against gliomas. Conclusions These findings suggest that multiple low-dose intratumoral injections of CpG-ODN can eradicate intracranial gliomas possibly through mechanisms involving NK mediated effector function. PMID:20570924

Induction of anti-glioma natural killer cell response following multiple low-dose intracerebral CpG therapy.

PubMed

Alizadeh, Darya; Zhang, Leying; Brown, Christine E; Farrukh, Omar; Jensen, Michael C; Badie, Behnam

2010-07-01

Stimulation of toll-like receptor-9 by CpG oligodeoxynucleotides (CpG-ODN) has been shown to counteract the immunosuppressive microenvironment and to inhibit tumor growth in glioma models. These studies, however, have used high doses of CpG-ODN, which can induce toxicity in a clinical setting. The goal of this study was to evaluate the antitumor efficacy of multiple low-dose intratumoral CpG-ODN in a glioma model. Mice bearing 4-day-old intracranial GL261 gliomas received a single or multiple (two or four) intratumoral injections of CpG-ODN (3 microg) every 4 days. Tumor growth was measured by bioluminescent imaging, brain histology, and animal survival. Flow cytometry and cytotoxicity assays were used to assess anti-glioma immune response. Two and four intracranial injections of low-dose CpG-ODN, but not a single injection, eradicated gliomas in 70% of mice. Moreover, surviving animals exhibited durable tumor-free remission (> 3 months) and were protected from intracranial rechallenge with GL261 gliomas, showing the capacity for long-term antitumor immunity. Although most inflammatory cells seemed to increase, activated natural killer (NK) cells (i.e., NK(+)CD107a(+)) were more frequent than CD8(+)CD107a(+) in the brains of rechallenged CpG-ODN-treated animals and showed a stronger in vitro cytotoxicity against GL261 target cells. Leukocyte depletion studies confirmed that NK cells played an important role in the initial CpG-ODN antitumor response, but both CD8 and NK cells were equally important in long-term immunity against gliomas. These findings suggest that multiple low-dose intratumoral injections of CpG-ODN can eradicate intracranial gliomas possibly through mechanisms involving NK-mediated effector function.

Adaptive testing for multiple traits in a proportional odds model with applications to detect SNP-brain network associations.

PubMed

Kim, Junghi; Pan, Wei

2017-04-01

There has been increasing interest in developing more powerful and flexible statistical tests to detect genetic associations with multiple traits, as arising from neuroimaging genetic studies. Most of existing methods treat a single trait or multiple traits as response while treating an SNP as a predictor coded under an additive inheritance mode. In this paper, we follow an earlier approach in treating an SNP as an ordinal response while treating traits as predictors in a proportional odds model (POM). In this way, it is not only easier to handle mixed types of traits, e.g., some quantitative and some binary, but it is also potentially more robust to the commonly adopted additive inheritance mode. More importantly, we develop an adaptive test in a POM so that it can maintain high power across many possible situations. Compared to the existing methods treating multiple traits as responses, e.g., in a generalized estimating equation (GEE) approach, the proposed method can be applied to a high dimensional setting where the number of phenotypes (p) can be larger than the sample size (n), in addition to a usual small P setting. The promising performance of the proposed method was demonstrated with applications to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data, in which either structural MRI driven phenotypes or resting-state functional MRI (rs-fMRI) derived brain functional connectivity measures were used as phenotypes. The applications led to the identification of several top SNPs of biological interest. Furthermore, simulation studies showed competitive performance of the new method, especially for p>n. © 2017 WILEY PERIODICALS, INC.

The BET bromodomain inhibitor CPI203 improves lenalidomide and dexamethasone activity in in vitro and in vivo models of multiple myeloma by blockade of Ikaros and MYC signaling

PubMed Central

Díaz, Tania; Rodríguez, Vanina; Lozano, Ester; Mena, Mari-Pau; Calderón, Marcos; Rosiñol, Laura; Martínez, Antonio; Tovar, Natalia; Pérez-Galán, Patricia; Bladé, Joan; Roué, Gaël; de Larrea, Carlos Fernández

2017-01-01

Most patients with multiple myeloma treated with current therapies, including immunomodulatory drugs, eventually develop relapsed/refractory disease. Clinical activity of lenalidomide relies on degradation of Ikaros and the consequent reduction in IRF4 expression, both required for myeloma cell survival and involved in the regulation of MYC transcription. Thus, we sought to determine the combinational effect of an MYC-interfering therapy with lenalidomide/dexamethasone. We analyzed the potential therapeutic effect of the combination of the BET bromodomain inhibitor CPI203 with the lenalidomide/dexamethasone regimen in myeloma cell lines. CPI203 exerted a dose-dependent cell growth inhibition in cell lines, indeed in lenalidomide/dexamethasone-resistant cells (median response at 0.5 μM: 65.4%), characterized by G1 cell cycle blockade and a concomitant inhibition of MYC and Ikaros signaling. These effects were potentiated by the addition of lenalidomide/dexamethasone. Results were validated in primary plasma cells from patients with multiple myeloma co-cultured with the mesenchymal stromal cell line stromaNKtert. Consistently, the drug combination evoked a 50% reduction in cell proliferation and correlated with basal Ikaros mRNA expression levels (P=0.04). Finally, in a SCID mouse xenotransplant model of myeloma, addition of CPI203 to lenalidomide/dexamethasone decreased tumor burden, evidenced by a lower glucose uptake and increase in the growth arrest marker GADD45B, with simultaneous downregulation of key transcription factors such as MYC, Ikaros and IRF4. Taken together, our data show that the combination of a BET bromodomain inhibitor with a lenalidomide-based regimen may represent a therapeutic approach to improve the response in relapsed/refractory patients with multiple myeloma, even in cases with suboptimal prior response to immunomodulatory drugs. PMID:28751557

Multilevel linear modelling of the response-contingent learning of young children with significant developmental delays.

PubMed

Raab, Melinda; Dunst, Carl J; Hamby, Deborah W

2018-02-27

The purpose of the study was to isolate the sources of variations in the rates of response-contingent learning among young children with multiple disabilities and significant developmental delays randomly assigned to contrasting types of early childhood intervention. Multilevel, hierarchical linear growth curve modelling was used to analyze four different measures of child response-contingent learning where repeated child learning measures were nested within individual children (Level-1), children were nested within practitioners (Level-2), and practitioners were nested within the contrasting types of intervention (Level-3). Findings showed that sources of variations in rates of child response-contingent learning were associated almost entirely with type of intervention after the variance associated with differences in practitioners nested within groups were accounted for. Rates of child learning were greater among children whose existing behaviour were used as the building blocks for promoting child competence (asset-based practices) compared to children for whom the focus of intervention was promoting child acquisition of missing skills (needs-based practices). The methods of analysis illustrate a practical approach to clustered data analysis and the presentation of results in ways that highlight sources of variations in the rates of response-contingent learning among young children with multiple developmental disabilities and significant developmental delays. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Modeling month-season of birth as a risk factor in mouse models of chronic disease: from multiple sclerosis to autoimmune encephalomyelitis.

PubMed

Reynolds, Jacob D; Case, Laure K; Krementsov, Dimitry N; Raza, Abbas; Bartiss, Rose; Teuscher, Cory

2017-06-01

Month-season of birth (M-SOB) is a risk factor in multiple chronic diseases, including multiple sclerosis (MS), where the lowest and greatest risk of developing MS coincide with the lowest and highest birth rates, respectively. To determine whether M-SOB effects in such chronic diseases as MS can be experimentally modeled, we examined the effect of M-SOB on susceptibility of C57BL/6J mice to experimental autoimmune encephalomyelitis (EAE). As in MS, mice that were born during the M-SOB with the lowest birth rate were less susceptible to EAE than mice born during the M-SOB with the highest birth rate. We also show that the M-SOB effect on EAE susceptibility is associated with differential production of multiple cytokines/chemokines by neuroantigen-specific T cells that are known to play a role in EAE pathogenesis. Taken together, these results support the existence of an M-SOB effect that may reflect seasonally dependent developmental differences in adaptive immune responses to self-antigens independent of external stimuli, including exposure to sunlight and vitamin D. Moreover, our documentation of an M-SOB effect on EAE susceptibility in mice allows for modeling and detailed analysis of mechanisms that underlie the M-SOB effect in not only MS but in numerous other diseases in which M-SOB impacts susceptibility.-Reynolds, J. D., Case, L. K., Krementsov, D. N., Raza, A., Bartiss, R., Teuscher, C. Modeling month-season of birth as a risk factor in mouse models of chronic disease: from multiple sclerosis to autoimmune encephalomyelitis. © FASEB.

3D fluid-structure modelling and vibration analysis for fault diagnosis of Francis turbine using multiple ANN and multiple ANFIS

NASA Astrophysics Data System (ADS)

Saeed, R. A.; Galybin, A. N.; Popov, V.

2013-01-01

This paper discusses condition monitoring and fault diagnosis in Francis turbine based on integration of numerical modelling with several different artificial intelligence (AI) techniques. In this study, a numerical approach for fluid-structure (turbine runner) analysis is presented. The results of numerical analysis provide frequency response functions (FRFs) data sets along x-, y- and z-directions under different operating load and different position and size of faults in the structure. To extract features and reduce the dimensionality of the obtained FRF data, the principal component analysis (PCA) has been applied. Subsequently, the extracted features are formulated and fed into multiple artificial neural networks (ANN) and multiple adaptive neuro-fuzzy inference systems (ANFIS) in order to identify the size and position of the damage in the runner and estimate the turbine operating conditions. The results demonstrated the effectiveness of this approach and provide satisfactory accuracy even when the input data are corrupted with certain level of noise.

Computer Modeling of Thoracic Response to Blast

DTIC Science & Technology

1988-01-01

be solved at reasonable cost. intrathoracic pressure responses for subjects wearing In order to determine if the gas content of the sheep ballistic...spatial and temporal ries were compared with data. Two extreme cases had distribution of the load can be reasonably predicted by the rumen filled with...to the ap- is that sheep have large, multiple stomachs that have a proximate location where intrathoracic pressure meas- considerable air content . It

Maternal inflammation modulates infant immune response patterns to viral lung challenge in a murine model.

PubMed

Gleditsch, Dorothy D; Shornick, Laurie P; Van Steenwinckel, Juliette; Gressens, Pierre; Weisert, Ryan P; Koenig, Joyce M

2014-07-01

Chorioamnionitis, an inflammatory gestational disorder, commonly precedes preterm delivery. Preterm infants may be at particular risk for inflammation-related morbidity related to infection, although the pathogenic mechanisms are unclear. We hypothesized that maternal inflammation modulates immune programming to drive postnatal inflammatory processes. We used a novel combined murine model to treat late gestation dams with low-dose lipopolysaccharide (LPS) and to secondarily challenge exposed neonates or weanlings with Sendai virus (SeV) lung infection. Multiple organs were analyzed to characterize age-specific postnatal immune and inflammatory responses. Maternal LPS treatment enhanced innate immune populations in the lungs, livers, and/or spleens of exposed neonates or weanlings. Secondary lung SeV infection variably affected neutrophil, macrophage, and dendritic cell proportions in multiple organs of exposed pups. Neonatal lung infection induced brain interleukin (IL)-4 expression, although this response was muted in LPS-exposed pups. Adaptive immune cells, including lung, lymph node, and thymic lymphocytes and lung CD4 cells expressing FoxP3, interferon (IFN)-γ, or IL-17, were variably prominent in LPS-exposed pups. Maternal inflammation modifies postnatal immunity and augments systemic inflammatory responses to viral lung infection in an age-specific manner. We speculate that inflammatory modulation of the developing immune system contributes to chronic morbidity and mortality in preterm infants.

Alternative Strategies in Response to Saline Stress in Two Varieties of Portulaca oleracea (Purslane).

PubMed

Mulry, Kristina R; Hanson, Bryan A; Dudle, Dana A

2015-01-01

Purslane (Portulaca oleracea) is a globally-distributed plant with a long history of use in folk medicine and cooking. We have developed purslane as a model system for exploring plant responses to stress. We exposed two varieties of purslane to saline stress with the objective of identifying differences between the varieties in the plasticity of morphological and physiological traits. The varieties responded to saline stress with significantly different changes in the measured traits, which included inter alia biomass, flower counts, proline concentrations and betalain pigment concentrations. The alternative responses of the two varieties consisted of complex, simultaneous changes in multiple traits. In particular, we observed that while both varieties increased production of betalain pigments and proline under saline stress, one variety invested more in betalain pigments while the other invested more in proline. Proline and betalain pigments undoubtedly play multiple roles in plant tissues, but in this case their role as antioxidants deployed to ameliorate saline stress appears to be important. Taken holistically, our results suggest that the two varieties employ different strategies in allocating resources to cope with saline stress. This conclusion establishes purslane as a suitable model system for the study of saline stress and the molecular basis for differential responses.

Alternative Strategies in Response to Saline Stress in Two Varieties of Portulaca oleracea (Purslane)

PubMed Central

Mulry, Kristina R.; Hanson, Bryan A.; Dudle, Dana A.

2015-01-01

Purslane (Portulaca oleracea) is a globally-distributed plant with a long history of use in folk medicine and cooking. We have developed purslane as a model system for exploring plant responses to stress. We exposed two varieties of purslane to saline stress with the objective of identifying differences between the varieties in the plasticity of morphological and physiological traits. The varieties responded to saline stress with significantly different changes in the measured traits, which included inter alia biomass, flower counts, proline concentrations and betalain pigment concentrations. The alternative responses of the two varieties consisted of complex, simultaneous changes in multiple traits. In particular, we observed that while both varieties increased production of betalain pigments and proline under saline stress, one variety invested more in betalain pigments while the other invested more in proline. Proline and betalain pigments undoubtedly play multiple roles in plant tissues, but in this case their role as antioxidants deployed to ameliorate saline stress appears to be important. Taken holistically, our results suggest that the two varieties employ different strategies in allocating resources to cope with saline stress. This conclusion establishes purslane as a suitable model system for the study of saline stress and the molecular basis for differential responses. PMID:26398279

Spectroscopic sensitivity of real-time, rapidly induced phytochemical change in response to damage.

PubMed

Couture, John J; Serbin, Shawn P; Townsend, Philip A

2013-04-01

An ecological consequence of plant-herbivore interactions is the phytochemical induction of defenses in response to insect damage. Here, we used reflectance spectroscopy to characterize the foliar induction profile of cardenolides in Asclepias syriaca in response to damage, tracked in vivo changes and examined the influence of multiple plant traits on cardenolide concentrations. Foliar cardenolide concentrations were measured at specific time points following damage to capture their induction profile. Partial least-squares regression (PLSR) modeling was employed to calibrate cardenolide concentrations to reflectance spectroscopy. In addition, subsets of plants were either repeatedly sampled to track in vivo changes or modified to reduce latex flow to damaged areas. Cardenolide concentrations and the induction profile of A. syriaca were well predicted using models derived from reflectance spectroscopy, and this held true for repeatedly sampled plants. Correlations between cardenolides and other foliar-related variables were weak or not significant. Plant modification for latex reduction inhibited an induced cardenolide response. Our findings show that reflectance spectroscopy can characterize rapid phytochemical changes in vivo. We used reflectance spectroscopy to identify the mechanisms behind the production of plant secondary metabolites, simultaneously characterizing multiple foliar constituents. In this case, cardenolide induction appears to be largely driven by enhanced latex delivery to leaves following damage. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Discrete Event Simulation of Distributed Team Communication

DTIC Science & Technology

2012-03-22

performs, and auditory information that is provided through multiple audio devices with speech response. This paper extends previous discrete event workload...2008, pg. 1) notes that “Architecture modeling furnishes abstrac- tions for use in managing complexities, allowing engineers to visualise the proposed

SYMPOSIUM SESSION PROPOSAL: INCORPORATION OF MODE OF ACTION INTO MECHANISTICALLY-BASED QUANTITATIVE MODELS

EPA Science Inventory

The biological processes by which environmental pollutants induce adverse health effects is most likely regulated by complex interactions dependent upon the route of exposure, dose, kinetics of distribution, and multiple cellular responses. To further complicate deciphering thes...

Nonlinear engine model for idle speed control

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

Livshiz, M.; Sanvido, D.J.; Stiles, S.D.

1994-12-31

This paper describes a nonlinear model of an engine used for the design of idle speed control and prediction in a broad range of idle speeds and operational conditions. Idle speed control systems make use of both spark advance and the idle air actuator to control engine speed for improved response relative to variations in the target idle speed due to load disturbances. The control system at idle can be presented by a multiple input multiple output (MIMO) nonlinear model. Information of nonlinearities helps to improve performance of the system over the whole range of engine speeds. A proposed simplemore » nonlinear model of the engine at idle was applied for design of optimal controllers and predictors for improved steady state, load rejection and transition from and to idle. This paper describes vehicle results of engine speed prediction based on the described model.« less

NASA Langley developments in response calculations needed for failure and life prediction

NASA Technical Reports Server (NTRS)

Housner, Jerrold M.

1993-01-01

NASA Langley developments in response calculations needed for failure and life predictions are discussed. Topics covered include: structural failure analysis in concurrent engineering; accuracy of independent regional modeling demonstrated on classical example; functional interface method accurately joins incompatible finite element models; interface method for insertion of local detail modeling extended to curve pressurized fuselage window panel; interface concept for joining structural regions; motivation for coupled 2D-3D analysis; compression panel with discontinuous stiffener coupled 2D-3D model and axial surface strains at the middle of the hat stiffener; use of adaptive refinement with multiple methods; adaptive mesh refinement; and studies on quantity effect of bow-type initial imperfections on reliability of stiffened panels.

Parallel updating and weighting of multiple spatial maps for visual stability during whole body motion

PubMed Central

Medendorp, W. P.

2015-01-01

It is known that the brain uses multiple reference frames to code spatial information, including eye-centered and body-centered frames. When we move our body in space, these internal representations are no longer in register with external space, unless they are actively updated. Whether the brain updates multiple spatial representations in parallel, or whether it restricts its updating mechanisms to a single reference frame from which other representations are constructed, remains an open question. We developed an optimal integration model to simulate the updating of visual space across body motion in multiple or single reference frames. To test this model, we designed an experiment in which participants had to remember the location of a briefly presented target while being translated sideways. The behavioral responses were in agreement with a model that uses a combination of eye- and body-centered representations, weighted according to the reliability in which the target location is stored and updated in each reference frame. Our findings suggest that the brain simultaneously updates multiple spatial representations across body motion. Because both representations are kept in sync, they can be optimally combined to provide a more precise estimate of visual locations in space than based on single-frame updating mechanisms. PMID:26490289

Modifying the affective behavior of preschoolers with autism using in-vivo or video modeling and reinforcement contingencies.

PubMed

Gena, Angeliki; Couloura, Sophia; Kymissis, Effie

2005-10-01

The purpose of this study was to modify the affective behavior of three preschoolers with autism in home settings and in the context of play activities, and to compare the effects of video modeling to the effects of in-vivo modeling in teaching these children contextually appropriate affective responses. A multiple-baseline design across subjects, with a return to baseline condition, was used to assess the effects of treatment that consisted of reinforcement, video modeling, in-vivo modeling, and prompting. During training trials, reinforcement in the form of verbal praise and tokens was delivered contingent upon appropriate affective responding. Error correction procedures differed for each treatment condition. In the in-vivo modeling condition, the therapist used modeling and verbal prompting. In the video modeling condition, video segments of a peer modeling the correct response and verbal prompting by the therapist were used as corrective procedures. Participants received treatment in three categories of affective behavior--sympathy, appreciation, and disapproval--and were presented with a total of 140 different scenarios. The study demonstrated that both treatments--video modeling and in-vivo modeling--systematically increased appropriate affective responding in all response categories for the three participants. Additionally, treatment effects generalized across responses to untrained scenarios, the child's mother, new therapists, and time.

Community assembly rules affect the diversity of expanding communities.

PubMed

Peng, Zechen; Zhou, Shurong

2014-11-01

Despite centuries of interest in species range limits, few studies have taken a whole community into consideration. Actually, multiple species may simultaneously respond to environmental changes, for example, global warming, leading a series of dynamical communities toward the advancing front. We investigated multiple species range expansions through the analysis of a two-species dispersion model and simulations of multiple species assemblages regulated by neutral and fecundity-survival trade-offs (FSTs), respectively, and found that species assemblages regulated by different mechanisms would initiate different expanding patterns in geographic ranges in response to environmental changes. The neutral model generally predicts a higher biodiversity near the core of an expanding range, and a lower community similarity compared with a FST model. Without considering the evolution of life history traits, an assortment of the reproduction ability happens at the advancing front under FSTs at the expense of a higher death rate or lower competitive ability. These results emphasize the importance of community assembly rules to the biodiversity maintenance of range expanding communities.

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

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

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

DOE PAGES

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake; ...

2017-03-24

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Transient vibration analytical modeling and suppressing for vibration absorber system under impulse excitation

NASA Astrophysics Data System (ADS)

Wang, Xi; Yang, Bintang; Yu, Hu; Gao, Yulong

2017-04-01

The impulse excitation of mechanism causes transient vibration. In order to achieve adaptive transient vibration control, a method which can exactly model the response need to be proposed. This paper presents an analytical model to obtain the response of the primary system attached with dynamic vibration absorber (DVA) under impulse excitation. The impulse excitation which can be divided into single-impulse excitation and multi-impulse excitation is simplified as sinusoidal wave to establish the analytical model. To decouple the differential governing equations, a transform matrix is applied to convert the response from the physical coordinate to model coordinate. Therefore, the analytical response in the physical coordinate can be obtained by inverse transformation. The numerical Runge-Kutta method and experimental tests have demonstrated the effectiveness of the analytical model proposed. The wavelet of the response indicates that the transient vibration consists of components with multiple frequencies, and it shows that the modeling results coincide with the experiments. The optimizing simulations based on genetic algorithm and experimental tests demonstrate that the transient vibration of the primary system can be decreased by changing the stiffness of the DVA. The results presented in this paper are the foundations for us to develop the adaptive transient vibration absorber in the future.

High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability.

PubMed

Majda, Andrew J; Abramov, Rafail; Gershgorin, Boris

2010-01-12

Climate change science focuses on predicting the coarse-grained, planetary-scale, longtime changes in the climate system due to either changes in external forcing or internal variability, such as the impact of increased carbon dioxide. The predictions of climate change science are carried out through comprehensive, computational atmospheric, and oceanic simulation models, which necessarily parameterize physical features such as clouds, sea ice cover, etc. Recently, it has been suggested that there is irreducible imprecision in such climate models that manifests itself as structural instability in climate statistics and which can significantly hamper the skill of computer models for climate change. A systematic approach to deal with this irreducible imprecision is advocated through algorithms based on the Fluctuation Dissipation Theorem (FDT). There are important practical and computational advantages for climate change science when a skillful FDT algorithm is established. The FDT response operator can be utilized directly for multiple climate change scenarios, multiple changes in forcing, and other parameters, such as damping and inverse modelling directly without the need of running the complex climate model in each individual case. The high skill of FDT in predicting climate change, despite structural instability, is developed in an unambiguous fashion using mathematical theory as guidelines in three different test models: a generic class of analytical models mimicking the dynamical core of the computer climate models, reduced stochastic models for low-frequency variability, and models with a significant new type of irreducible imprecision involving many fast, unstable modes.

The Mechanisms of Manual Therapy in the Treatment of Musculoskeletal Pain: A Comprehensive Model

PubMed Central

Bialosky, Joel E; Bishop, Mark D; Price, Don D; Robinson, Michael E; George, Steven Z

2009-01-01

Prior studies suggest manual therapy (MT) as effective in the treatment of musculoskeletal pain; however, the mechanisms through which MT exerts its effects are not established. In this paper we present a comprehensive model to direct future studies in MT. This model provides visualization of potential individual mechanisms of MT that the current literature suggests as pertinent and provides a framework for the consideration of the potential interaction between these individual mechanisms. Specifically, this model suggests that a mechanical force from MT initiates a cascade of neurophysiological responses from the peripheral and central nervous system which are then responsible for the clinical outcomes. This model provides clear direction so that future studies may provide appropriate methodology to account for multiple potential pertinent mechanisms. PMID:19027342

A focus on natural variation for abiotic constraints response in the model species Arabidopsis thaliana.

PubMed

Lefebvre, Valérie; Kiani, Seifollah Poormohammad; Durand-Tardif, Mylène

2009-08-13

Plants are particularly subject to environmental stress, as they cannot move from unfavourable surroundings. As a consequence they have to react in situ. In any case, plants have to sense the stress, then the signal has to be transduced to engage the appropriate response. Stress response is effected by regulating genes, by turning on molecular mechanisms to protect the whole organism and its components and/or to repair damage. Reactions vary depending on the type of stress and its intensity, but some are commonly turned on because some responses to different abiotic stresses are shared. In addition, there are multiple ways for plants to respond to environmental stress, depending on the species and life strategy, but also multiple ways within a species depending on plant variety or ecotype. It is regularly accepted that populations of a single species originating from diverse geographic origins and/or that have been subjected to different selective pressure, have evolved retaining the best alleles for completing their life cycle. Therefore, the study of natural variation in response to abiotic stress, can help unravel key genes and alleles for plants to cope with their unfavourable physical and chemical surroundings. This review is focusing on Arabidopsis thaliana which has been largely adopted by the global scientific community as a model organism. Also, tools and data that facilitate investigation of natural variation and abiotic stress encountered in the wild are set out. Characterization of accessions, QTLs detection and cloning of alleles responsible for variation are presented.

Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection

PubMed Central

Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

2017-01-01

Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung. PMID:28912729

Murine genetically engineered and human xenograft models of chronic lymphocytic leukemia.

PubMed

Chen, Shih-Shih; Chiorazzi, Nicholas

2014-07-01

Chronic lymphocytic leukemia (CLL) is a genetically complex disease, with multiple factors having an impact on onset, progression, and response to therapy. Genetic differences/abnormalities have been found in hematopoietic stem cells from patients, as well as in B lymphocytes of individuals with monoclonal B-cell lymphocytosis who may develop the disease. Furthermore, after the onset of CLL, additional genetic alterations occur over time, often causing disease worsening and altering patient outcomes. Therefore, being able to genetically engineer mouse models that mimic CLL or at least certain aspects of the disease will help us understand disease mechanisms and improve treatments. This notwithstanding, because neither the genetic aberrations responsible for leukemogenesis and progression nor the promoting factors that support these are likely identical in character or influences for all patients, genetically engineered mouse models will only completely mimic CLL when all of these factors are precisely defined. In addition, multiple genetically engineered models may be required because of the heterogeneity in susceptibility genes among patients that can have an effect on genetic and environmental characteristics influencing disease development and outcome. For these reasons, we review the major murine genetically engineered and human xenograft models in use at the present time, aiming to report the advantages and disadvantages of each. Copyright © 2014 Elsevier Inc. All rights reserved.

Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

PubMed

Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

2017-01-01

Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung.

Quantitative Modeling of Microbial Population Responses to Chronic Irradiation Combined with Other Stressors

PubMed Central

Shuryak, Igor; Dadachova, Ekaterina

2016-01-01

Microbial population responses to combined effects of chronic irradiation and other stressors (chemical contaminants, other sub-optimal conditions) are important for ecosystem functioning and bioremediation in radionuclide-contaminated areas. Quantitative mathematical modeling can improve our understanding of these phenomena. To identify general patterns of microbial responses to multiple stressors in radioactive environments, we analyzed three data sets on: (1) bacteria isolated from soil contaminated by nuclear waste at the Hanford site (USA); (2) fungi isolated from the Chernobyl nuclear-power plant (Ukraine) buildings after the accident; (3) yeast subjected to continuous γ-irradiation in the laboratory, where radiation dose rate and cell removal rate were independently varied. We applied generalized linear mixed-effects models to describe the first two data sets, whereas the third data set was amenable to mechanistic modeling using differential equations. Machine learning and information-theoretic approaches were used to select the best-supported formalism(s) among biologically-plausible alternatives. Our analysis suggests the following: (1) Both radionuclides and co-occurring chemical contaminants (e.g. NO2) are important for explaining microbial responses to radioactive contamination. (2) Radionuclides may produce non-monotonic dose responses: stimulation of microbial growth at low concentrations vs. inhibition at higher ones. (3) The extinction-defining critical radiation dose rate is dramatically lowered by additional stressors. (4) Reproduction suppression by radiation can be more important for determining the critical dose rate, than radiation-induced cell mortality. In conclusion, the modeling approaches used here on three diverse data sets provide insight into explaining and predicting multi-stressor effects on microbial communities: (1) the most severe effects (e.g. extinction) on microbial populations may occur when unfavorable environmental conditions (e.g. fluctuations of temperature and/or nutrient levels) coincide with radioactive contamination; (2) an organism’s radioresistance and bioremediation efficiency in rich laboratory media may be insufficient to carry out radionuclide bioremediation in the field—robustness against multiple stressors is needed. PMID:26808049

Influence of the Supramolecular Micro-Assembly of Multiple Emulsions on their Biopharmaceutical Features and In vivo Therapeutic Response.

PubMed

Cilurzo, Felisa; Cristiano, Maria Chiara; Di Marzio, Luisa; Cosco, Donato; Carafa, Maria; Ventura, Cinzia Anna; Fresta, Massimo; Paolino, Donatella

2015-01-01

The ability of some surfactants to self-assemble in a water/oil bi-phase environment thus forming supramolecular structure leading to the formation of w/o/w multiple emulsions was investigated. The w/o/w multiple emulsions obtained by self-assembling (one-step preparation method) were compared with those prepared following the traditional two-step procedure. Methyl-nicotinate was used as a hydrophilic model drug. The formation of the multiple emulsion structure was evidenced by optical microscopy, which showed a mean size of the inner oil droplets of 6 μm and 10 μm for one-step and two-step multiple emulsions, respectively. The in vitrobiopharmaceutical features of the various w/o/w multiple emulsion formulations were evaluated by means of viscosimetry studies, drug release and in vitro percutaneous permeation experiments through human stratum corneum and viable epidermis membranes. The self-assembled multiple emulsions allowed a more gradual percutaneous permeation (a zero-order permeation rate) than the two-step ones. The in vivotopical carrier properties of the two different multiple emulsions were evaluated on healthy human volunteers by using the spectrophotometry of reflectance, an in vivonon invasive method. These multiple emulsion systems were also compared with conventional emulsion formulations. Our findings demonstrated that the multiple emulsions obtained by self-assembling were able to provide a more sustained drug delivery into the skin and hence a longer therapeutic action than two-step multiple emulsions and conventional emulsion formulations. Finally, our findings showed that the supramolecular micro-assembly of multiple emulsions was able to influence not only the biopharmaceutical characteristics but also the potential in vivotherapeutic response.

Moving Beyond Maximum Tolerated Dose for Targeted Oncology Drugs: Use of Clinical Utility Index to Optimize Venetoclax Dosage in Multiple Myeloma Patients.

PubMed

Freise, K J; Jones, A K; Verdugo, M E; Menon, R M; Maciag, P C; Salem, A H

2017-12-01

Exposure-response analyses of venetoclax in combination with bortezomib and dexamethasone in previously treated patients with multiple myeloma (MM) were performed on a phase Ib venetoclax dose-ranging study. Logistic regression models were utilized to determine relationships, identify subpopulations with different responses, and optimize the venetoclax dosage that balanced both efficacy and safety. Bortezomib refractory status and number of prior treatments were identified to impact the efficacy response to venetoclax treatment. Higher venetoclax exposures were estimated to increase the probability of achieving a very good partial response (VGPR) or better through venetoclax doses of 1,200 mg. However, the probability of neutropenia (grade ≥3) was estimated to increase at doses >800 mg. Using a clinical utility index, a venetoclax dosage of 800 mg daily was selected to optimally balance the VGPR or better rates and neutropenia rates in MM patients administered 1-3 prior lines of therapy and nonrefractory to bortezomib. © 2017 American Society for Clinical Pharmacology and Therapeutics.

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

Population pharmacokinetics and exposure-uric acid analyses after single and multiple doses of ABT-639, a calcium channel blocker, in healthy volunteers.

PubMed

An, Guohua; Liu, Wei; Duan, W Rachel; Nothaft, Wolfram; Awni, Walid; Dutta, Sandeep

2015-03-01

ABT-639 is a selective T-type calcium channel blocker with efficacy in a wide range of preclinical models of nociceptive and neuropathic pain. In the current first-in-human (FIH) study, the pharmacokinetics, tolerability, and safety of ABT-639 after single- (up to 170 mg) and multiple doses (up to 160 mg BID) were evaluated in healthy volunteers in a randomized, double-blinded, placebo-controlled manner. ABT-639 demonstrated acceptable safety and pharmacokinetic profiles in human. Results from assessment of the routine laboratory variables showed an unexpected statistically significant and clinically relevant decrease in blood uric acid with the increase in ABT-639 dose, which is possibly due to inhibition in URAT1 transporter. Pharmacokinetic/pharmacodynamic models were constructed to characterize the relationship between ABT-639 exposure and uric acid response. The final model was a mechanism-based indirect response pharmacodynamic model with the stimulation of uric acid elimination by ABT-639. The model estimated K in values in males and females were 10.2 and 7.13 μmol/h, respectively. The model estimated K out was 0.033 1/h. ABT-639 concentration that can produce 50% stimulation in uric acid elimination was estimated to be 8,070 ng/mL. Based on the final model, further simulations were conducted to predict the effect of ABT-639 on uric acid in gout patients. The simulation results indicated that, if the urate-lowering response to ABT-639 in gout patients is similar to that in healthy subjects, ABT-639 BID doses of 140 mg or higher would be expected to provide clinically meaningful lowering of blood uric acid levels below the 380 μmol/L solubility limit of monosodium urate.

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

NASA Technical Reports Server (NTRS)

Koch, Patrick N.

1997-01-01

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

To speak or not to speak - A multiple resource perspective

NASA Technical Reports Server (NTRS)

Tsang, P. S.; Hartzell, E. J.; Rothschild, R. A.

1985-01-01

The desirability of employing speech response in a dynamic dual task situation was discussed from a multiple resource perspective. A secondary task technique was employed to examine the time-sharing performance of five dual tasks with various degrees of resource overlap according to the structure-specific resource model of Wickens (1980). The primary task was a visual/manual tracking task which required spatial processing. The secondary task was either another tracking task or a spatial transformation task with one of four input (visual or auditory) and output (manual or speech) configurations. The results show that the dual task performance was best when the primary tracking task was paired with the visual/speech transformation task. This finding was explained by an interaction of the stimulus-central processing-response compatibility of the transformation task and the degree of resource competition between the time-shared tasks. Implications on the utility of speech response were discussed.

RETRAN analysis of multiple steam generator blow down caused by an auxiliary feedwater steam-line break

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

Feltus, M.A.

1987-01-01

Analysis results for multiple steam generator blow down caused by an auxiliary feedwater steam-line break performed with the RETRAN-02 MOD 003 computer code are presented to demonstrate the capabilities of the RETRAN code to predict system transient response for verifying changes in operational procedures and supporting plant equipment modifications. A typical four-loop Westinghouse pressurized water reactor was modeled using best-estimate versus worst case licensing assumptions. This paper presents analyses performed to evaluate the necessity of implementing an auxiliary feedwater steam-line isolation modification. RETRAN transient analysis can be used to determine core cooling capability response, departure from nucleate boiling ratio (DNBR)more » status, and reactor trip signal actuation times.« less

Computational modeling of cardiovascular response to orthostatic stress

NASA Technical Reports Server (NTRS)

Heldt, Thomas; Shim, Eun B.; Kamm, Roger D.; Mark, Roger G.

2002-01-01

The objective of this study is to develop a model of the cardiovascular system capable of simulating the short-term (< or = 5 min) transient and steady-state hemodynamic responses to head-up tilt and lower body negative pressure. The model consists of a closed-loop lumped-parameter representation of the circulation connected to set-point models of the arterial and cardiopulmonary baroreflexes. Model parameters are largely based on literature values. Model verification was performed by comparing the simulation output under baseline conditions and at different levels of orthostatic stress to sets of population-averaged hemodynamic data reported in the literature. On the basis of experimental evidence, we adjusted some model parameters to simulate experimental data. Orthostatic stress simulations are not statistically different from experimental data (two-sided test of significance with Bonferroni adjustment for multiple comparisons). Transient response characteristics of heart rate to tilt also compare well with reported data. A case study is presented on how the model is intended to be used in the future to investigate the effects of post-spaceflight orthostatic intolerance.

Measuring change for a multidimensional test using a generalized explanatory longitudinal item response model.

PubMed

Cho, Sun-Joo; Athay, Michele; Preacher, Kristopher J

2013-05-01

Even though many educational and psychological tests are known to be multidimensional, little research has been done to address how to measure individual differences in change within an item response theory framework. In this paper, we suggest a generalized explanatory longitudinal item response model to measure individual differences in change. New longitudinal models for multidimensional tests and existing models for unidimensional tests are presented within this framework and implemented with software developed for generalized linear models. In addition to the measurement of change, the longitudinal models we present can also be used to explain individual differences in change scores for person groups (e.g., learning disabled students versus non-learning disabled students) and to model differences in item difficulties across item groups (e.g., number operation, measurement, and representation item groups in a mathematics test). An empirical example illustrates the use of the various models for measuring individual differences in change when there are person groups and multiple skill domains which lead to multidimensionality at a time point. © 2012 The British Psychological Society.

Testing the Structure of Hydrological Models using Genetic Programming

NASA Astrophysics Data System (ADS)

Selle, B.; Muttil, N.

2009-04-01

Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

Strategic priming with multiple antigens can yield memory cell phenotypes optimized for infection with Mycobacterium tuberculosis: A computational study

DOE PAGES

Ziraldo, Cordelia; Gong, Chang; Kirschner, Denise E.; ...

2016-01-06

Lack of an effective vaccine results in 9 million new cases of tuberculosis (TB) every year and 1.8 million deaths worldwide. While many infants are vaccinated at birth with BCG (an attenuated M. bovis), this does not prevent infection or development of TB after childhood. Immune responses necessary for prevention of infection or disease are still unknown, making development of effective vaccines against TB challenging. Several new vaccines are ready for human clinical trials, but these trials are difficult and expensive; especially challenging is determining the appropriate cellular response necessary for protection. The magnitude of an immune response is likelymore » key to generating a successful vaccine. Characteristics such as numbers of central memory (CM) and effector memory (EM) T cells responsive to a diverse set of epitopes are also correlated with protection. Promising vaccines against TB contain mycobacterial subunit antigens (Ag) present during both active and latent infection. We hypothesize that protection against different key immunodominant antigens could require a vaccine that produces different levels of EM and CM for each Ag-specific memory population. We created a computational model to explore EM and CM values, and their ratio, within what we term Memory Design Space. Our model captures events involved in T cell priming within lymph nodes and tracks their circulation through blood to peripheral tissues. We used the model to test whether multiple Ag-specific memory cell populations could be generated with distinct locations within Memory Design Space at a specific time point post vaccination. Boosting can further shift memory populations to memory cell ratios unreachable by initial priming events. By strategically varying antigen load, properties of cellular interactions within the LN, and delivery parameters (e.g., number of boosts) of multi-subunit vaccines, we can generate multiple Ag-specific memory populations that cover a wide range of Memory Design Space. As a result, given a set of desired characteristics for Ag-specific memory populations, we can use our model as a tool to predict vaccine formulations that will generate those populations.« less

Strategic priming with multiple antigens can yield memory cell phenotypes optimized for infection with Mycobacterium tuberculosis: A computational study

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

Ziraldo, Cordelia; Gong, Chang; Kirschner, Denise E.

Lack of an effective vaccine results in 9 million new cases of tuberculosis (TB) every year and 1.8 million deaths worldwide. While many infants are vaccinated at birth with BCG (an attenuated M. bovis), this does not prevent infection or development of TB after childhood. Immune responses necessary for prevention of infection or disease are still unknown, making development of effective vaccines against TB challenging. Several new vaccines are ready for human clinical trials, but these trials are difficult and expensive; especially challenging is determining the appropriate cellular response necessary for protection. The magnitude of an immune response is likelymore » key to generating a successful vaccine. Characteristics such as numbers of central memory (CM) and effector memory (EM) T cells responsive to a diverse set of epitopes are also correlated with protection. Promising vaccines against TB contain mycobacterial subunit antigens (Ag) present during both active and latent infection. We hypothesize that protection against different key immunodominant antigens could require a vaccine that produces different levels of EM and CM for each Ag-specific memory population. We created a computational model to explore EM and CM values, and their ratio, within what we term Memory Design Space. Our model captures events involved in T cell priming within lymph nodes and tracks their circulation through blood to peripheral tissues. We used the model to test whether multiple Ag-specific memory cell populations could be generated with distinct locations within Memory Design Space at a specific time point post vaccination. Boosting can further shift memory populations to memory cell ratios unreachable by initial priming events. By strategically varying antigen load, properties of cellular interactions within the LN, and delivery parameters (e.g., number of boosts) of multi-subunit vaccines, we can generate multiple Ag-specific memory populations that cover a wide range of Memory Design Space. As a result, given a set of desired characteristics for Ag-specific memory populations, we can use our model as a tool to predict vaccine formulations that will generate those populations.« less

Immune responses of B. malayi thioredoxin (TRX) and venom allergen homologue (VAH) chimeric multiple antigen for lymphatic filariasis.

PubMed

Anugraha, Gandhirajan; Jeyaprita, Parasurama Jawaharlal; Madhumathi, Jayaprakasam; Sheeba, Tamilvanan; Kaliraj, Perumal

2013-12-01

Although multiple vaccine strategy for lymphatic filariasis has provided tremendous hope, the choice of antigens used in combination has determined its success in the previous studies. Multiple antigens comprising key vaccine candidates from different life cycle stages would provide a promising strategy if the antigenic combination is chosen by careful screening. In order to analyze one such combination, we have used a chimeric construct carrying the well studied B. malayi antigens thioredoxin (BmTRX) and venom allergen homologue (BmVAH) as a fusion protein (TV) and evaluated its immune responses in mice model. The efficacy of fusion protein vaccine was explored in comparison with the single antigen vaccines and their cocktail. In mice, TV induced significantly high antibody titer of 1,28,000 compared to cocktail vaccine TRX+VAH (50,000) and single antigen vaccine TRX (16,000) or VAH (50,000). Furthermore, TV elicited higher level of cellular proliferative response together with elevated levels of IFN-γ, IL-4 and IL-5 indicating a Th1/Th2 balanced response. The isotype antibody profile showed significantly high level of IgG1 and IgG2b confirming the balanced response elicited by TV. Immunization with TV antigen induced high levels of both humoral and cellular immune responses compared to either cocktail or antigen given alone. The result suggests that TV is highly immunogenic in mice and hence the combination needs to be evaluated for its prophylactic potential.

Community advisor - firewise

Treesearch

Richard D. Reitz

2003-01-01

The old model of individual homeowners and neighborhoods depending solely on government provided fire fighting resources is gone. Recent wildland fires have demonstrated that community firefighting resources are easily outpaced when multiple structures are burning simultaneously. The cure is to move most structure protection responsibility to the homeowner and...

Evaluating Pharmacokinetic and Pharmacodynamic Interactions with Computational Models in Cumulative Risk Assessment

EPA Science Inventory

Simultaneous or sequential exposure to multiple chemicals may cause interactions in the pharmacokinetics (PK) and/or pharmacodynamics (PD) of the individual chemicals. Such interactions can cause modification of the internal or target dose/response of one chemical in the mixture ...

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Channel Model Optimization with Reflection Residual Component for Indoor MIMO-VLC System

NASA Astrophysics Data System (ADS)

Chen, Yong; Li, Tengfei; Liu, Huanlin; Li, Yichao

2017-12-01

A fast channel modeling method is studied to solve the problem of reflection channel gain for multiple input multiple output-visible light communications (MIMO-VLC) in the paper. For reducing the computational complexity when associating with the reflection times, no more than 3 reflections are taken into consideration in VLC. We think that higher order reflection link consists of corresponding many times line of sight link and firstly present reflection residual component to characterize higher reflection (more than 2 reflections). We perform computer simulation results for point-to-point channel impulse response, receiving optical power and receiving signal to noise ratio. Based on theoretical analysis and simulation results, the proposed method can effectively reduce the computational complexity of higher order reflection in channel modeling.

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

PubMed

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

2018-05-14

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

Using Monte Carlo Ray tracing to Understand the Vibrational Response of UN as Measured by Neutron Spectroscopy

NASA Astrophysics Data System (ADS)

Lin, J. Y. Y.; Aczel, A. A.; Abernathy, D. L.; Nagler, S. E.; Buyers, W. J. L.; Granroth, G. E.

2014-03-01

Recently neutron spectroscopy measurements, using the ARCS and SEQUOIA time-of-flight chopper spectrometers, observed an extended series of equally spaced modes in UN that are well described by quantum harmonic oscillator behavior of the N atoms. Additional contributions to the scattering are also observed. Monte Carlo ray tracing simulations with various sample kernels have allowed us to distinguish between the response from the N oscillator scattering, contributions that arise from the U partial phonon density of states (PDOS), and all forms of multiple scattering. These simulations confirm that multiple scattering contributes an ~ Q -independent background to the spectrum at the oscillator mode positions. All three of the aforementioned contributions are necessary to accurately model the experimental data. These simulations were also used to compare the T dependence of the oscillator modes in SEQUOIA data to that predicted by the binary solid model. This work was sponsored by the Scientific User Facilities Division, Office of Basic Energy Sciences, U.S. Department of Energy.

Risk-taking behavior in the presence of nonconvex asset dynamics.

PubMed

Lybbert, Travis J; Barrett, Christopher B

2011-01-01

The growing literature on poverty traps emphasizes the links between multiple equilibria and risk avoidance. However, multiple equilibria may also foster risk-taking behavior by some poor people. We illustrate this idea with a simple analytical model in which people with different wealth and ability endowments make investment and risky activity choices in the presence of known nonconvex asset dynamics. This model underscores a crucial distinction between familiar static concepts of risk aversion and forward-looking dynamic risk responses to nonconvex asset dynamics. Even when unobservable preferences exhibit decreasing absolute risk aversion, observed behavior may suggest that risk aversion actually increases with wealth near perceived dynamic asset thresholds. Although high ability individuals are not immune from poverty traps, they can leverage their capital endowments more effectively than lower ability types and are therefore less likely to take seemingly excessive risks. In general, linkages between behavioral responses and wealth dynamics often seem to run in both directions. Both theoretical and empirical poverty trap research could benefit from making this two-way linkage more explicit.

Modeling contemporary climate profiles of whitebark pine (Pinus albicaulis) and predicting responses to global warming

Treesearch

Marcus V. Warwell; Gerald E. Rehfeldt; Nicholas L. Crookston

2006-01-01

The Random Forests multiple regression tree was used to develop an empirically-based bioclimate model for the distribution of Pinus albicaulis (whitebark pine) in western North America, latitudes 31° to 51° N and longitudes 102° to 125° W. Independent variables included 35 simple expressions of temperature and precipitation and their interactions....

Using Video Self-Modelling to Increase Active Learning Responses during Small-Group Reading Instruction for Primary School Pupils with Social Emotional and Mental Health Difficulties

ERIC Educational Resources Information Center

Young-Pelton, Cheryl A.; Bushman, Samantha L.

2015-01-01

Effectiveness of a video self-modelling (VSM) intervention was examined with primary schoolchildren who attended a full-time special education programme for pupils with social emotional and behavioural difficulties and who exhibited inappropriate behaviour during small-group reading instruction. A randomised multiple-probe baseline design was used…

The Role of Protein Radicals in Chronic Neuroimmune Dysfunction and Neuropathology in Response to a Multiple-Hit Model of Gulf War Exposure

DTIC Science & Technology

2014-10-01

potential neurotoxicants and triggers of inflammation, such as persistent peripheral inflammation and the organophosphate pesticide chlorpyrifos (CPF...War Illness Mouse Model, Chlorpyrifos , LPS, NF-KB p50, microglia, chronic neuroinflammation, serum markers, neuropathology 16. SECURITY...neurotoxicants and triggers of inflammation, such as persistent infections, and the organophosphate pesticide chlorpyrifos (CPF) may interact to

A Comparison of Three IRT Approaches to Examinee Ability Change Modeling in a Single-Group Anchor Test Design

ERIC Educational Resources Information Center

Paek, Insu; Park, Hyun-Jeong; Cai, Li; Chi, Eunlim

2014-01-01

Typically a longitudinal growth modeling based on item response theory (IRT) requires repeated measures data from a single group with the same test design. If operational or item exposure problems are present, the same test may not be employed to collect data for longitudinal analyses and tests at multiple time points are constructed with unique…

Humanizing Outgroups Through Multiple Categorization

PubMed Central

Prati, Francesca; Crisp, Richard J.; Meleady, Rose; Rubini, Monica

2016-01-01

In three studies, we examined the impact of multiple categorization on intergroup dehumanization. Study 1 showed that perceiving members of a rival university along multiple versus simple categorical dimensions enhanced the tendency to attribute human traits to this group. Study 2 showed that multiple versus simple categorization of immigrants increased the attribution of uniquely human emotions to them. This effect was explained by the sequential mediation of increased individuation of the outgroup and reduced outgroup threat. Study 3 replicated this sequential mediation model and introduced a novel way of measuring humanization in which participants generated attributes corresponding to the outgroup in a free response format. Participants generated more uniquely human traits in the multiple versus simple categorization conditions. We discuss the theoretical implications of these findings and consider their role in informing and improving efforts to ameliorate contemporary forms of intergroup discrimination. PMID:26984016

Response Strength in Extreme Multiple Schedules

PubMed Central

McLean, Anthony P; Grace, Randolph C; Nevin, John A

2012-01-01

Four pigeons were trained in a series of two-component multiple schedules. Reinforcers were scheduled with random-interval schedules. The ratio of arranged reinforcer rates in the two components was varied over 4 log units, a much wider range than previously studied. When performance appeared stable, prefeeding tests were conducted to assess resistance to change. Contrary to the generalized matching law, logarithms of response ratios in the two components were not a linear function of log reinforcer ratios, implying a failure of parameter invariance. Over a 2 log unit range, the function appeared linear and indicated undermatching, but in conditions with more extreme reinforcer ratios, approximate matching was observed. A model suggested by McLean (1991), originally for local contrast, predicts these changes in sensitivity to reinforcer ratios somewhat better than models by Herrnstein (1970) and by Williams and Wixted (1986). Prefeeding tests of resistance to change were conducted at each reinforcer ratio, and relative resistance to change was also a nonlinear function of log reinforcer ratios, again contrary to conclusions from previous work. Instead, the function suggests that resistance to change in a component may be determined partly by the rate of reinforcement and partly by the ratio of reinforcers to responses. PMID:22287804

Evolutionary conservation and neuronal mechanisms of auditory perceptual restoration.

PubMed

Petkov, Christopher I; Sutter, Mitchell L

2011-01-01

Auditory perceptual 'restoration' occurs when the auditory system restores an occluded or masked sound of interest. Behavioral work on auditory restoration in humans began over 50 years ago using it to model a noisy environmental scene with competing sounds. It has become clear that not only humans experience auditory restoration: restoration has been broadly conserved in many species. Behavioral studies in humans and animals provide a necessary foundation to link the insights being obtained from human EEG and fMRI to those from animal neurophysiology. The aggregate of data resulting from multiple approaches across species has begun to clarify the neuronal bases of auditory restoration. Different types of neural responses supporting restoration have been found, supportive of multiple mechanisms working within a species. Yet a general principle has emerged that responses correlated with restoration mimic the response that would have been given to the uninterrupted sound of interest. Using the same technology to study different species will help us to better harness animal models of 'auditory scene analysis' to clarify the conserved neural mechanisms shaping the perceptual organization of sound and to advance strategies to improve hearing in natural environmental settings. © 2010 Elsevier B.V. All rights reserved.

Metal mixture modeling evaluation project: 2. Comparison of four modeling approaches.

PubMed

Farley, Kevin J; Meyer, Joseph S; Balistrieri, Laurie S; De Schamphelaere, Karel A C; Iwasaki, Yuichi; Janssen, Colin R; Kamo, Masashi; Lofts, Stephen; Mebane, Christopher A; Naito, Wataru; Ryan, Adam C; Santore, Robert C; Tipping, Edward

2015-04-01

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the US Geological Survey (USA), HDR|HydroQual (USA), and the Centre for Ecology and Hydrology (United Kingdom) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME workshop in Brussels, Belgium (May 2012), is provided in the present study. Overall, the models were found to be similar in structure (free ion activities computed by the Windermere humic aqueous model [WHAM]; specific or nonspecific binding of metals/cations in or on the organism; specification of metal potency factors or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single vs multiple types of binding sites on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong interrelationships among the model parameters (binding constants, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed. © 2014 SETAC.

A multi-scale approach to designing therapeutics for tuberculosis

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

Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje

Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. Lastly, we describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oralmore » and inhaled antibiotics, and (c) the effect of vaccination.« less

Magnetically multiplexed heating of single domain nanoparticles

NASA Astrophysics Data System (ADS)

Christiansen, M. G.; Senko, A. W.; Chen, R.; Romero, G.; Anikeeva, P.

2014-05-01

Selective hysteretic heating of multiple collocated types of single domain magnetic nanoparticles (SDMNPs) by alternating magnetic fields (AMFs) may offer a useful tool for biomedical applications. The possibility of "magnetothermal multiplexing" has not yet been realized, in part due to prevalent use of linear response theory to model SDMNP heating in AMFs. Dynamic hysteresis modeling suggests that specific driving conditions play an underappreciated role in determining optimal material selection strategies for high heat dissipation. Motivated by this observation, magnetothermal multiplexing is theoretically predicted and empirically demonstrated by selecting SDMNPs with properties that suggest optimal hysteretic heat dissipation at dissimilar AMF driving conditions. This form of multiplexing could effectively offer multiple channels for minimally invasive biological signaling applications.

A multi-scale approach to designing therapeutics for tuberculosis

DOE PAGES

Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje; ...

2015-04-20

Approximately one third of the world’s population is infected with Mycobacterium tuberculosis. Limited information about how the immune system fights M. tuberculosis and what constitutes protection from the bacteria impact our ability to develop effective therapies for tuberculosis. We present an in vivo systems biology approach that integrates data from multiple model systems and over multiple length and time scales into a comprehensive multi-scale and multi-compartment view of the in vivo immune response to M. tuberculosis. Lastly, we describe computational models that can be used to study (a) immunomodulation with the cytokines tumor necrosis factor and interleukin 10, (b) oralmore » and inhaled antibiotics, and (c) the effect of vaccination.« less

The Climate Response to Stratospheric Aerosol Geoengineering Can Be Tailored Using Multiple Injection Locations

NASA Astrophysics Data System (ADS)

MacMartin, Douglas G.; Kravitz, Ben; Tilmes, Simone; Richter, Jadwiga H.; Mills, Michael J.; Lamarque, Jean-Francois; Tribbia, Joseph J.; Vitt, Francis

2017-12-01

By injecting different amounts of SO2 at multiple different latitudes, the spatial pattern of aerosol optical depth (AOD) can be partially controlled. This leads to the ability to influence the climate response to geoengineering with stratospheric aerosols, providing the potential for design. We use simulations from the fully coupled whole-atmosphere chemistry climate model CESM1(WACCM) to demonstrate that by appropriately combining injection at just four different locations, 30°S, 15°S, 15°N, and 30°N, then three spatial degrees of freedom of AOD can be achieved: an approximately spatially uniform AOD distribution, the relative difference in AOD between Northern and Southern Hemispheres, and the relative AOD in high versus low latitudes. For forcing levels that yield 1-2°C cooling, the AOD and surface temperature response are sufficiently linear in this model so that the response to different combinations of injection at different latitudes can be estimated from single-latitude injection simulations; nonlinearities associated with both aerosol growth and changes to stratospheric circulation will be increasingly important at higher forcing levels. Optimized injection at multiple locations is predicted to improve compensation of CO2-forced climate change relative to a case using only equatorial aerosol injection (which overcools the tropics relative to high latitudes). The additional degrees of freedom can be used, for example, to balance the interhemispheric temperature gradient and the equator to pole temperature gradient in addition to the global mean temperature. Further research is needed to better quantify the impacts of these strategies on changes to long-term temperature, precipitation, and other climate parameters.

The contribution of future agricultural trends in the US Midwest to global climate change mitigation

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

Thomson, Allison M.; Kyle, G. Page; Zhang, Xuesong

2014-01-19

Land use change is a complex response to changing environmental and socioeconomic systems. Historical drivers of land use change include changes in the natural resource availability of a region, changes in economic conditions for production of certain products and changing policies. Most recently, introduction of policy incentives for biofuel production have influenced land use change in the US Midwest, leading to concerns that bioenergy production systems may compete with food production and land conservation. Here we explore how land use may be impacted by future climate mitigation measures by nesting a high resolution agricultural model (EPIC – Environmental Policy Indicatormore » Climate) for the US Midwest within a global integrated assessment model (GCAM – Global Change Assessment Model). This approach is designed to provide greater spatial resolution and detailed agricultural practice information by focusing on the climate mitigation potential of agriculture and land use in a specific region, while retaining the global economic context necessary to understand the far ranging effects of climate mitigation targets. We find that until the simulated carbon prices are very high, the US Midwest has a comparative advantage in producing traditional food and feed crops over bioenergy crops. Overall, the model responds to multiple pressures by adopting a mix of future responses. We also find that the GCAM model is capable of simulations at multiple spatial scales and agricultural technology resolution, which provides the capability to examine regional response to global policy and economic conditions in the context of climate mitigation.« less

Coding response to a case-mix measurement system based on multiple diagnoses.

PubMed

Preyra, Colin

2004-08-01

To examine the hospital coding response to a payment model using a case-mix measurement system based on multiple diagnoses and the resulting impact on a hospital cost model. Financial, clinical, and supplementary data for all Ontario short stay hospitals from years 1997 to 2002. Disaggregated trends in hospital case-mix growth are examined for five years following the adoption of an inpatient classification system making extensive use of combinations of secondary diagnoses. Hospital case mix is decomposed into base and complexity components. The longitudinal effects of coding variation on a standard hospital payment model are examined in terms of payment accuracy and impact on adjustment factors. Introduction of the refined case-mix system provided incentives for hospitals to increase reporting of secondary diagnoses and resulted in growth in highest complexity cases that were not matched by increased resource use over time. Despite a pronounced coding response on the part of hospitals, the increase in measured complexity and case mix did not reduce the unexplained variation in hospital unit cost nor did it reduce the reliance on the teaching adjustment factor, a potential proxy for case mix. The main implication was changes in the size and distribution of predicted hospital operating costs. Jurisdictions introducing extensive refinements to standard diagnostic related group (DRG)-type payment systems should consider the effects of induced changes to hospital coding practices. Assessing model performance should include analysis of the robustness of classification systems to hospital-level variation in coding practices. Unanticipated coding effects imply that case-mix models hypothesized to perform well ex ante may not meet expectations ex post.

Group-oriented coordination models for distributed client-server computing

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Hughes, Craig S.

1994-01-01

This paper describes group-oriented control models for distributed client-server interactions. These models transparently coordinate requests for services that involve multiple servers, such as queries across distributed databases. Specific capabilities include: decomposing and replicating client requests; dispatching request subtasks or copies to independent, networked servers; and combining server results into a single response for the client. The control models were implemented by combining request broker and process group technologies with an object-oriented communication middleware tool. The models are illustrated in the context of a distributed operations support application for space-based systems.

Developing a Mouse Model of Sensory and Cognitive Deficits for Multiple Sclerosis

DTIC Science & Technology

2012-07-01

ABRs and otoacoustic emissions. More sophisticates measures, such as neural processing of binaural responses are typically performed in rats, guinea...ears we are able to calculate the binaural component of the EEGs for comparison of wild type and Claudin 11 knockout responses. We are awaiting the...knockout of the Claudin 11 gene. 2. Development of a novel anesthesia protocol to measure binaural auditory signals in the superior olivary complex of

Climate change and watershed mercury export: a multiple projection and model analysis

USGS Publications Warehouse

Golden, Heather E.; Knightes, Christopher D.; Conrads, Paul; Feaster, Toby D.; Davis, Gary M.; Benedict, Stephen T.; Bradley, Paul M.

2013-01-01

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

A Stimulus-Locked Vector Autoregressive Model for Slow Event-Related fMRI Designs

PubMed Central

Siegle, Greg

2009-01-01

Summary Neuroscientists have become increasingly interested in exploring dynamic relationships among brain regions. Such a relationship, when directed from one region toward another, is denoted by “effective connectivity.” An fMRI experimental paradigm which is well-suited for examination of effective connectivity is the slow event-related design. This design presents stimuli at sufficient temporal spacing for determining within-trial trajectories of BOLD activation, allowing for the analysis of stimulus-locked temporal covariation of brain responses in multiple regions. This may be especially important for emotional stimuli processing, which can evolve over the course of several seconds, if not longer. However, while several methods have been devised for determining fMRI effective connectivity, few are adapted to event-related designs, which include non-stationary BOLD responses and multiple levels of nesting. We propose a model tailored for exploring effective connectivity of multiple brain regions in event-related fMRI designs - a semi-parametric adaptation of vector autoregressive (VAR) models, termed “stimulus-locked VAR” (SloVAR). Connectivity coefficients vary as a function of time relative to stimulus onset, are regularized via basis expansions, and vary randomly across subjects. SloVAR obtains flexible, data-driven estimates of effective connectivity and hence is useful for building connectivity models when prior information on dynamic regional relationships is sparse. Indices derived from the coefficient estimates can also be used to relate effective connectivity estimates to behavioral or clinical measures. We demonstrate the SloVAR model on a sample of clinically depressed and normal controls, showing that early but not late cortico-amygdala connectivity appears crucial to emotional control and early but not late cortico-cortico connectivity predicts depression severity in the depressed group, relationships that would have been missed in a more traditional VAR analysis. PMID:19236927

Therapeutic Efficacy of Suppressing the JAK/STAT Pathway in Multiple Models of EAE1

PubMed Central

Liu, Yudong; Holdbrooks, Andrew T.; De Sarno, Patrizia; Rowse, Amber L.; Yanagisawa, Lora L.; McFarland, Braden C.; Harrington, Laurie E.; Raman, Chander; Sabbaj, Steffanie; Benveniste, Etty N.; Qin, Hongwei

2014-01-01

Pathogenic T helper cells and myeloid cells are involved in the pathogenesis of Multiple Sclerosis (MS) and Experimental Autoimmune Encephalomyelitis (EAE), an animal model of MS. The JAK/STAT pathway is utilized by numerous cytokines for signaling, and is critical for development, regulation and termination of immune responses. Dysregulation of the JAK/STAT pathway has pathological implications in autoimmune and neuroinflammatory diseases. Many of the cytokines involved in MS/EAE, including IL-6, IL-12, IL-23, IFN-γ and GM-CSF, use the JAK/STAT pathway to induce biological responses. Thus, targeting JAKs has implications for treating autoimmune inflammation of the brain. We have utilized AZD1480, a JAK1/2 inhibitor, to investigate the therapeutic potential of inhibiting the JAK/STAT pathway in models of EAE. AZD1480 treatment inhibits disease severity in MOG-induced classical and atypical EAE models by preventing entry of immune cells into the brain, suppressing differentiation of Th1 and Th17 cells, deactivating myeloid cells, inhibiting STAT activation in the brain, and reducing expression of pro-inflammatory cytokines and chemokines. Treatment of SJL/J mice with AZD1480 delays disease onset of PLP-induced relapsing-remitting disease, reduces relapses and diminishes clinical severity. AZD1480 treatment was also effective in reducing ongoing paralysis induced by adoptive transfer of either pathogenic Th1 or Th17 cells. In vivo AZD1480 treatment impairs both the priming and expansion of T-cells, and attenuates antigen-presentation functions of myeloid cells. Inhibition of the JAK/STAT pathway has clinical efficacy in multiple pre-clinical models of MS, suggesting the feasibility of the JAK/STAT pathway as a target for neuroinflammatory diseases. PMID:24323580

MODIS polarization performance and anomalous four-cycle polarization phenomenon

NASA Astrophysics Data System (ADS)

Young, James B.; Knight, Ed; Merrow, Cindy

1998-10-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) will be one of the primary instruments observing the earth on the Earth Observing System (EOS) scheduled for launch in 1999. MODIS polarization performance characterization was required for the 0.4 to 0.6 micrometers (VIS), 0.6 micrometers to 1.0 micrometers (NIR), and 1.0 micrometers to 2.3 micrometers (SWIR) regions. A polarized source assembly (PSA) consisting of a collimator with a rotatable Ahrens polarizer was used to illuminate MODIS with a linearly polarized beam. MODIS signal function having two-cycles per 360 degrees prism rotation signal function was expected. However, some spectral bands had a distinct four-cycle anomalous signal. The expected two-cycle function was present in all regions with the four-cycle anomaly being limited to the NIR region. Fourier analysis was very useful tooling determining the cause of the anomaly. A simplified polarization model of the PSA and MODIS was generated using Mueller matrices-Stokes vector formalism. Parametric modeling illustrated that this anomaly could be produced by energy having multiple passes between PSA Ahrens prism and the MODIS focal plane filters. Furthermore, the model gave NIR four-cycle magnitudes that were consistent with observations. The IVS and SWIR optical trans had birefringent elements that served to scramble the multiple pass anomaly. The model validity was demonstrated with an experimental setup that had partial aperture illumination which eliminated the possibility of multiple passes. The four-cycle response was eliminated while producing the same two-cycle polarization response. Data will be shown to illustrate the four-cycle phenomenon.

Strain-specific functional and numerical responses are required to evaluate impacts on predator-prey dynamics.

PubMed

Yang, Zhou; Lowe, Chris D; Crowther, Will; Fenton, Andy; Watts, Phillip C; Montagnes, David J S

2013-02-01

We use strains recently collected from the field to establish cultures; then, through laboratory studies we investigate how among strain variation in protozoan ingestion and growth rates influences population dynamics and intraspecific competition. We focused on the impact of changing temperature because of its well-established effects on protozoan rates and its ecological relevance, from daily fluctuations to climate change. We show, first, that there is considerable inter-strain variability in thermal sensitivity of maximum growth rate, revealing distinct differences among multiple strains of our model species Oxyrrhis marina. We then intensively examined two representative strains that exhibit distinctly different thermal responses and parameterised the influence of temperature on their functional and numerical responses. Finally, we assessed how these responses alter predator-prey population dynamics. We do this first considering a standard approach, which assumes that functional and numerical responses are directly coupled, and then compare these results with a novel framework that incorporates both functional and numerical responses in a fully parameterised model. We conclude that: (i) including functional diversity of protozoa at the sub-species level will alter model predictions and (ii) including directly measured, independent functional and numerical responses in a model can provide a more realistic account of predator-prey dynamics.

A sustainable model for training teachers to use pivotal response training.

PubMed

Suhrheinrich, Jessica

2015-08-01

The increase in the rate of autism diagnoses has created a growing demand for teachers who are trained to use effective interventions. The train-the-trainer model, which involves training supervisors to train others, may be ideal for providing cost-effective training and ongoing support to teachers. Although research supports interventions, such as pivotal response training, as evidence-based, dissemination to school environments has been problematic. This study assessed the benefits of using the train-the-trainer model to disseminate pivotal response training to school settings. A multiple-baseline design was conducted across three training groups, each consisting of one school staff member (trainer), three special education teachers, and six students. Trainers conducted the teacher-training workshop with high adherence to training protocol and met mastery criteria in their ability to implement pivotal response training, assess implementation of pivotal response training, and provide feedback to teachers. Six of the nine teachers mastered all components of pivotal response training. The remaining three teachers implemented 89% of the pivotal response training components correctly. The majority of trainers and teachers maintained their abilities at follow-up. These results support the use of the train-the-trainer model as an effective method of disseminating evidence-based practices in school settings. © The Author(s) 2014.

Striatal and Hippocampal Entropy and Recognition Signals in Category Learning: Simultaneous Processes Revealed by Model-Based fMRI

PubMed Central

Davis, Tyler; Love, Bradley C.; Preston, Alison R.

2012-01-01

Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and adjust their representations to support behavior in future encounters. Many techniques that are available to understand the neural basis of category learning assume that the multiple processes that subserve it can be neatly separated between different trials of an experiment. Model-based functional magnetic resonance imaging offers a promising tool to separate multiple, simultaneously occurring processes and bring the analysis of neuroimaging data more in line with category learning’s dynamic and multifaceted nature. We use model-based imaging to explore the neural basis of recognition and entropy signals in the medial temporal lobe and striatum that are engaged while participants learn to categorize novel stimuli. Consistent with theories suggesting a role for the anterior hippocampus and ventral striatum in motivated learning in response to uncertainty, we find that activation in both regions correlates with a model-based measure of entropy. Simultaneously, separate subregions of the hippocampus and striatum exhibit activation correlated with a model-based recognition strength measure. Our results suggest that model-based analyses are exceptionally useful for extracting information about cognitive processes from neuroimaging data. Models provide a basis for identifying the multiple neural processes that contribute to behavior, and neuroimaging data can provide a powerful test bed for constraining and testing model predictions. PMID:22746951

Collaborative Research: Process-resolving Decomposition of the Global Temperature Response to Modes of Low Frequency Variability in a Changing Climate

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

Cai, Ming; Deng, Yi

2015-02-06

El Niño-Southern Oscillation (ENSO) and Annular Modes (AMs) represent respectively the most important modes of low frequency variability in the tropical and extratropical circulations. The future projection of the ENSO and AM variability, however, remains highly uncertain with the state-of-the-art coupled general circulation models. A comprehensive understanding of the factors responsible for the inter-model discrepancies in projecting future changes in the ENSO and AM variability, in terms of multiple feedback processes involved, has yet to be achieved. The proposed research aims to identify sources of such uncertainty and establish a set of process-resolving quantitative evaluations of the existing predictions ofmore » the future ENSO and AM variability. The proposed process-resolving evaluations are based on a feedback analysis method formulated in Lu and Cai (2009), which is capable of partitioning 3D temperature anomalies/perturbations into components linked to 1) radiation-related thermodynamic processes such as cloud and water vapor feedbacks, 2) local dynamical processes including convection and turbulent/diffusive energy transfer and 3) non-local dynamical processes such as the horizontal energy transport in the oceans and atmosphere. Taking advantage of the high-resolution, multi-model ensemble products from the Coupled Model Intercomparison Project Phase 5 (CMIP5) soon to be available at the Lawrence Livermore National Lab, we will conduct a process-resolving decomposition of the global three-dimensional (3D) temperature (including SST) response to the ENSO and AM variability in the preindustrial, historical and future climate simulated by these models. Specific research tasks include 1) identifying the model-observation discrepancies in the global temperature response to ENSO and AM variability and attributing such discrepancies to specific feedback processes, 2) delineating the influence of anthropogenic radiative forcing on the key feedback processes operating on ENSO and AM variability and quantifying their relative contributions to the changes in the temperature anomalies associated with different phases of ENSO and AMs, and 3) investigating the linkages between model feedback processes that lead to inter-model differences in time-mean temperature projection and model feedback processes that cause inter-model differences in the simulated ENSO and AM temperature response. Through a thorough model-observation and inter-model comparison of the multiple energetic processes associated with ENSO and AM variability, the proposed research serves to identify key uncertainties in model representation of ENSO and AM variability, and investigate how the model uncertainty in predicting time-mean response is related to the uncertainty in predicting response of the low-frequency modes. The proposal is thus a direct response to the first topical area of the solicitation: Interaction of Climate Change and Low Frequency Modes of Natural Climate Variability. It ultimately supports the accomplishment of the BER climate science activity Long Term Measure (LTM): "Deliver improved scientific data and models about the potential response of the Earth's climate and terrestrial biosphere to increased greenhouse gas levels for policy makers to determine safe levels of greenhouse gases in the atmosphere."« less

Metal Mixture Modeling Evaluation project: 2. Comparison of four modeling approaches

USGS Publications Warehouse

Farley, Kevin J.; Meyer, Joe; Balistrieri, Laurie S.; DeSchamphelaere, Karl; Iwasaki, Yuichi; Janssen, Colin; Kamo, Masashi; Lofts, Steve; Mebane, Christopher A.; Naito, Wataru; Ryan, Adam C.; Santore, Robert C.; Tipping, Edward

2015-01-01

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the U.S. Geological Survey (USA), HDR⎪HydroQual, Inc. (USA), and the Centre for Ecology and Hydrology (UK) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME Workshop in Brussels, Belgium (May 2012), is provided herein. Overall, the models were found to be similar in structure (free ion activities computed by WHAM; specific or non-specific binding of metals/cations in or on the organism; specification of metal potency factors and/or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single versus multiple types of binding site on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong inter-relationships among the model parameters (log KM values, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.

The use of generalised additive models (GAM) in dentistry.

PubMed

Helfenstein, U; Steiner, M; Menghini, G

1997-12-01

Ordinary multiple regression and logistic multiple regression are widely applied statistical methods which allow a researcher to 'explain' or 'predict' a response variable from a set of explanatory variables or predictors. In these models it is usually assumed that quantitative predictors such as age enter linearly into the model. During recent years these methods have been further developed to allow more flexibility in the way explanatory variables 'act' on a response variable. The methods are called 'generalised additive models' (GAM). The rigid linear terms characterising the association between response and predictors are replaced in an optimal way by flexible curved functions of the predictors (the 'profiles'). Plotting the 'profiles' allows the researcher to visualise easily the shape by which predictors 'act' over the whole range of values. The method facilitates detection of particular shapes such as 'bumps', 'U-shapes', 'J-shapes, 'threshold values' etc. Information about the shape of the association is not revealed by traditional methods. The shapes of the profiles may be checked by performing a Monte Carlo simulation ('bootstrapping'). After the presentation of the GAM a relevant case study is presented in order to demonstrate application and use of the method. The dependence of caries in primary teeth on a set of explanatory variables is investigated. Since GAMs may not be easily accessible to dentists, this article presents them in an introductory condensed form. It was thought that a nonmathematical summary and a worked example might encourage readers to consider the methods described. GAMs may be of great value to dentists in allowing visualisation of the shape by which predictors 'act' and obtaining a better understanding of the complex relationships between predictors and response.

A study of MRI-guided diffuse fluorescence molecular tomography for monitoring PDT effects in pancreas cancer

NASA Astrophysics Data System (ADS)

Samkoe, Kimberley S.; Davis, Scott C.; Srinivasan, Subhadra; O'Hara, Julia A.; Hasan, Tayyaba; Pogue, Brian W.

2009-06-01

Over the last several decades little progress has been made in the therapy and treatment monitoring of pancreas adenocarcinoma, a devastating and aggressive form of cancer that has a 5-year patient survival rate of 3%. Currently, investigations for the use of interstitial Verteporfin photodynamic therapy (PDT) are being undertaken in both orthotopic xenograft mouse models and in human clinical trials. In the mouse models, magnetic resonance (MR) imaging has been used as a measure of surrogate response to Verteporfin PDT; however, MR imaging alone lacks the molecular information required to assess the metabolic function and growth rates of the tumor immediately after treatment. We propose the implementation of MR-guided fluorescence tomography in conjunction with a fluorescently labeled (IR-Dye 800 CW, LI-COR) epidermal growth factor (EGF) as a molecular measure of surrogate response. To demonstrate the effectiveness of MR-guided diffuse fluorescence tomography for molecular imaging, we have used the AsPC-1 (+EGFR) human pancreatic adenocarcinoma in an orthotopic mouse model. EGF IRDye 800CW was injected 48 hours prior to imaging. MR image sequences were collected simultaneously with the fluorescence data using a MR-coupled diffuse optical tomography system. Image reconstruction was performed multiple times with varying abdominal organ segmentation in order to obtain a optimal tomographic image. It is shown that diffuse fluorescence tomography of the orthotopic pancreas model is feasible, with consideration of confounding fluorescence signals from the multiple organs and tissues surrounding the pancreas. MR-guided diffuse fluorescence tomography will be used to monitor EGF response after photodynamic therapy. Additionally, it provide the opportunity to individualize subsequent therapies based on response to PDT as well as to evaluate the success of combination therapies, such as PDT with chemotherapy, antibody therapy or even radiation.

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

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

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

Multiple Systems of Spatial Memory: Evidence from Described Scenes

ERIC Educational Resources Information Center

Avraamides, Marios N.; Kelly, Jonathan W.

2010-01-01

Recent models in spatial cognition posit that distinct memory systems are responsible for maintaining transient and enduring spatial relations. The authors used perspective-taking performance to assess the presence of these enduring and transient spatial memories for locations encoded through verbal descriptions. Across 3 experiments, spatial…

Teaching Helping to Adolescents with Autism

ERIC Educational Resources Information Center

Day-Watkins, Jessica; Murray, Rachel; Connell, James E.

2014-01-01

This study is a replication and extension of Reeve, Reeve, Townsend, and Poulson (2007) evaluating the effects of a treatment package that included multiple-exemplar training, video modeling, prompting, and reinforcement on helping of 3 adolescents with autism. Results demonstrated that all participants acquired the helping responses. Probes…

Generalized Full-Information Item Bifactor Analysis

ERIC Educational Resources Information Center

Cai, Li; Yang, Ji Seung; Hansen, Mark

2011-01-01

Full-information item bifactor analysis is an important statistical method in psychological and educational measurement. Current methods are limited to single-group analysis and inflexible in the types of item response models supported. We propose a flexible multiple-group item bifactor analysis framework that supports a variety of…

Effects of systemic glutamatergic manipulations on conditioned eyeblink responses and hyperarousal in a rabbit model of post-traumatic stress disorder.

PubMed

Burhans, Lauren B; Smith-Bell, Carrie A; Schreurs, Bernard G

2017-10-01

Glutamatergic dysfunction is implicated in many neuropsychiatric conditions, including post-traumatic stress disorder (PTSD). Glutamate antagonists have shown some utility in treating PTSD symptoms, whereas glutamate agonists may facilitate cognitive behavioral therapy outcomes. We have developed an animal model of PTSD, based on conditioning of the rabbit's eyeblink response, that addresses two key features: conditioned responses (CRs) to cues associated with an aversive event and a form of conditioned hyperarousal referred to as conditioning-specific reflex modification (CRM). The optimal treatment to reduce both CRs and CRM is unpaired extinction. The goals of the study were to examine whether treatment with the N-methyl-D-aspartate glutamate receptor antagonist ketamine could reduce CRs and CRM, and whether the N-methyl-D-aspartate agonist D-cycloserine combined with unpaired extinction treatment could enhance the extinction of both. Administration of a single dose of subanesthetic ketamine had no significant immediate or delayed effect on CRs or CRM. Combining D-cycloserine with a single day of unpaired extinction facilitated extinction of CRs in the short term while having no impact on CRM. These results caution that treatments may improve one aspect of the PTSD symptomology while having no significant effects on other symptoms, stressing the importance of a multiple-treatment approach to PTSD and of animal models that address multiple symptoms.

Signaling mechanisms underlying the robustness and tunability of the plant immune network

PubMed Central

Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

2014-01-01

Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

Enriching student concept images: Teaching and learning fractions through a multiple-embodiment approach

NASA Astrophysics Data System (ADS)

Zhang, Xiaofen; Clements, M. A. (Ken); Ellerton, Nerida F.

2015-06-01

This study investigated how fifth-grade children's concept images of the unit fractions represented by the symbols , , and changed as a result of their participation in an instructional intervention based on multiple embodiments of fraction concepts. The participants' concept images were examined through pre- and post-teaching written questions and pre- and post-teaching one-to-one verbal interview questions. Results showed that at the pre-teaching stage, the student concept images of unit fractions were very narrow and mainly linked to area models. However, after the instructional intervention, the fifth graders were able to select and apply a variety of models in response to unit fraction tasks, and their concept images of unit fractions were enriched and linked to capacity, perimeter, linear and discrete models, as well as to area models. Their performances on tests had improved, and their conceptual understandings of unit fractions had developed.

Analysis of dense-medium light scattering with applications to corneal tissue: experiments and Monte Carlo simulations.

PubMed

Kim, K B; Shanyfelt, L M; Hahn, D W

2006-01-01

Dense-medium scattering is explored in the context of providing a quantitative measurement of turbidity, with specific application to corneal haze. A multiple-wavelength scattering technique is proposed to make use of two-color scattering response ratios, thereby providing a means for data normalization. A combination of measurements and simulations are reported to assess this technique, including light-scattering experiments for a range of polystyrene suspensions. Monte Carlo (MC) simulations were performed using a multiple-scattering algorithm based on full Mie scattering theory. The simulations were in excellent agreement with the polystyrene suspension experiments, thereby validating the MC model. The MC model was then used to simulate multiwavelength scattering in a corneal tissue model. Overall, the proposed multiwavelength scattering technique appears to be a feasible approach to quantify dense-medium scattering such as the manifestation of corneal haze, although more complex modeling of keratocyte scattering, and animal studies, are necessary.

Multiple methods for multiple futures: Integrating qualitative scenario planning and quantitative simulation modeling for natural resource decision making

USGS Publications Warehouse

Symstad, Amy J.; Fisichelli, Nicholas A.; Miller, Brian W.; Rowland, Erika; Schuurman, Gregor W.

2017-01-01

Scenario planning helps managers incorporate climate change into their natural resource decision making through a structured “what-if” process of identifying key uncertainties and potential impacts and responses. Although qualitative scenarios, in which ecosystem responses to climate change are derived via expert opinion, often suffice for managers to begin addressing climate change in their planning, this approach may face limits in resolving the responses of complex systems to altered climate conditions. In addition, this approach may fall short of the scientific credibility managers often require to take actions that differ from current practice. Quantitative simulation modeling of ecosystem response to climate conditions and management actions can provide this credibility, but its utility is limited unless the modeling addresses the most impactful and management-relevant uncertainties and incorporates realistic management actions. We use a case study to compare and contrast management implications derived from qualitative scenario narratives and from scenarios supported by quantitative simulations. We then describe an analytical framework that refines the case study’s integrated approach in order to improve applicability of results to management decisions. The case study illustrates the value of an integrated approach for identifying counterintuitive system dynamics, refining understanding of complex relationships, clarifying the magnitude and timing of changes, identifying and checking the validity of assumptions about resource responses to climate, and refining management directions. Our proposed analytical framework retains qualitative scenario planning as a core element because its participatory approach builds understanding for both managers and scientists, lays the groundwork to focus quantitative simulations on key system dynamics, and clarifies the challenges that subsequent decision making must address.

A systems biology approach to the analysis of subset-specific responses to lipopolysaccharide in dendritic cells.

PubMed

Hancock, David G; Shklovskaya, Elena; Guy, Thomas V; Falsafi, Reza; Fjell, Chris D; Ritchie, William; Hancock, Robert E W; Fazekas de St Groth, Barbara

2014-01-01

Dendritic cells (DCs) are critical for regulating CD4 and CD8 T cell immunity, controlling Th1, Th2, and Th17 commitment, generating inducible Tregs, and mediating tolerance. It is believed that distinct DC subsets have evolved to control these different immune outcomes. However, how DC subsets mount different responses to inflammatory and/or tolerogenic signals in order to accomplish their divergent functions remains unclear. Lipopolysaccharide (LPS) provides an excellent model for investigating responses in closely related splenic DC subsets, as all subsets express the LPS receptor TLR4 and respond to LPS in vitro. However, previous studies of the LPS-induced DC transcriptome have been performed only on mixed DC populations. Moreover, comparisons of the in vivo response of two closely related DC subsets to LPS stimulation have not been reported in the literature to date. We compared the transcriptomes of murine splenic CD8 and CD11b DC subsets after in vivo LPS stimulation, using RNA-Seq and systems biology approaches. We identified subset-specific gene signatures, which included multiple functional immune mediators unique to each subset. To explain the observed subset-specific differences, we used a network analysis approach. While both DC subsets used a conserved set of transcription factors and major signalling pathways, the subsets showed differential regulation of sets of genes that 'fine-tune' the network Hubs expressed in common. We propose a model in which signalling through common pathway components is 'fine-tuned' by transcriptional control of subset-specific modulators, thus allowing for distinct functional outcomes in closely related DC subsets. We extend this analysis to comparable datasets from the literature and confirm that our model can account for cell subset-specific responses to LPS stimulation in multiple subpopulations in mouse and man.

FastSim: A Fast Simulation for the SuperB Detector

NASA Astrophysics Data System (ADS)

Andreassen, R.; Arnaud, N.; Brown, D. N.; Burmistrov, L.; Carlson, J.; Cheng, C.-h.; Di Simone, A.; Gaponenko, I.; Manoni, E.; Perez, A.; Rama, M.; Roberts, D.; Rotondo, M.; Simi, G.; Sokoloff, M.; Suzuki, A.; Walsh, J.

2011-12-01

We have developed a parameterized (fast) simulation for detector optimization and physics reach studies of the proposed SuperB Flavor Factory in Italy. Detector components are modeled as thin sections of planes, cylinders, disks or cones. Particle-material interactions are modeled using simplified cross-sections and formulas. Active detectors are modeled using parameterized response functions. Geometry and response parameters are configured using xml files with a custom-designed schema. Reconstruction algorithms adapted from BaBar are used to build tracks and clusters. Multiple sources of background signals can be merged with primary signals. Pattern recognition errors are modeled statistically by randomly misassigning nearby tracking hits. Standard BaBar analysis tuples are used as an event output. Hadronic B meson pair events can be simulated at roughly 10Hz.

An Investigation of High-Cycle Fatigue Models for Metallic Structures Exhibiting Snap-Through Response

NASA Technical Reports Server (NTRS)

Przekop, Adam; Rizzi, Stephen A.; Sweitzer, Karl A.

2007-01-01

A study is undertaken to develop a methodology for determining the suitability of various high-cycle fatigue models for metallic structures subjected to combined thermal-acoustic loadings. Two features of this problem differentiate it from the fatigue of structures subject to acoustic loading alone. Potentially large mean stresses associated with the thermally pre- and post-buckled states require models capable of handling those conditions. Snap-through motion between multiple post-buckled equilibrium positions introduces very high alternating stress. The thermal-acoustic time history response of a clamped aluminum beam structure with geometric and material nonlinearities is determined via numerical simulation. A cumulative damage model is employed using a rainflow cycle counting scheme and fatigue estimates are made for 2024-T3 aluminum using various non-zero mean fatigue models, including Walker, Morrow, Morrow with true fracture strength, and MMPDS. A baseline zero-mean model is additionally considered. It is shown that for this material, the Walker model produces the most conservative fatigue estimates when the stress response has a tensile mean introduced by geometric nonlinearity, but remains in the linear elastic range. However, when the loading level is sufficiently high to produce plasticity, the response becomes more fully reversed and the baseline, Morrow, and Morrow with true fracture strength models produce the most conservative fatigue estimates.

Multiple cues produced by a robotic fish modulate aggressive behaviour in Siamese fighting fishes.

PubMed

Romano, Donato; Benelli, Giovanni; Donati, Elisa; Remorini, Damiano; Canale, Angelo; Stefanini, Cesare

2017-07-05

The use of robotics to establish social interactions between animals and robots, represents an elegant and innovative method to investigate animal behaviour. However, robots are still underused to investigate high complex and flexible behaviours, such as aggression. Here, Betta splendens was tested as model system to shed light on the effect of a robotic fish eliciting aggression. We evaluated how multiple signal systems, including a light stimulus, affect aggressive responses in B. splendens. Furthermore, we conducted experiments to estimate if aggressive responses were triggered by the biomimetic shape of fish replica, or whether any intruder object was effective as well. Male fishes showed longer and higher aggressive displays as puzzled stimuli from the fish replica increased. When the fish replica emitted its full sequence of cues, the intensity of aggression exceeded even that produced by real fish opponents. Fish replica shape was necessary for conspecific opponent perception, evoking significant aggressive responses. Overall, this study highlights that the efficacy of an artificial opponent eliciting aggressive behaviour in fish can be boosted by exposure to multiple signals. Optimizing the cue combination delivered by the robotic fish replica may be helpful to predict escalating levels of aggression.

VISTA is a novel broad-spectrum negative checkpoint regulator for cancer immunotherapy.

PubMed

Lines, J Louise; Sempere, Lorenzo F; Broughton, Thomas; Wang, Li; Noelle, Randolph

2014-06-01

In the past few years, the field of cancer immunotherapy has made great progress and is finally starting to change the way cancer is treated. We are now learning that multiple negative checkpoint regulators (NCR) restrict the ability of T-cell responses to effectively attack tumors. Releasing these brakes through antibody blockade, first with anti-CTLA4 and now followed by anti-PD1 and anti-PDL1, has emerged as an exciting strategy for cancer treatment. More recently, a new NCR has surfaced called V-domain immunoglobulin (Ig)-containing suppressor of T-cell activation (VISTA). This NCR is predominantly expressed on hematopoietic cells, and in multiple murine cancer models is found at particularly high levels on myeloid cells that infiltrated the tumors. Preclinical studies with VISTA blockade have shown promising improvement in antitumor T-cell responses, leading to impeded tumor growth and improved survival. Clinical trials support combined anti-PD1 and anti-CTLA4 as safe and effective against late-stage melanoma. In the future, treatment may involve combination therapy to target the multiple cell types and stages at which NCRs, including VISTA, act during adaptive immune responses. ©2014 American Association for Cancer Research.

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.

Dose-Response for Multiple Biomarkers of Exposure and Genotoxic Effect Following Repeated Treatment of Rats with the Alkylating Agents, MMS and MNU.

PubMed

Ji, Zhiying; LeBaron, Matthew J; Schisler, Melissa R; Zhang, Fagen; Bartels, Michael J; Gollapudi, B Bhaskar; Pottenger, Lynn H

2016-05-01

The nature of the dose-response relationship for various in vivo endpoints of exposure and effect were investigated using the alkylating agents, methyl methanesulfonate (MMS) and methylnitrosourea (MNU). Six male F344 rats/group were dosed orally with 0, 0.5, 1, 5, 25 or 50mg/kg bw/day (mkd) of MMS, or 0, 0.01, 0.1, 1, 5, 10, 25 or 50 mkd of MNU, for 4 consecutive days and sacrificed 24h after the last dose. The dose-responses for multiple biomarkers of exposure and genotoxic effect were investigated. In MMS-treated rats, the hemoglobin adduct level, a systemic exposure biomarker, increased linearly with dose (r (2) = 0.9990, P < 0.05), indicating the systemic availability of MMS; however, the N7MeG DNA adduct, a target exposure biomarker, exhibited a non-linear dose-response in blood and liver tissues. Blood reticulocyte micronuclei (MN), a genotoxic effect biomarker, exhibited a clear no-observed-genotoxic-effect-level (NOGEL) of 5 mkd as a point of departure (PoD) for MMS. Two separate dose-response models, the Lutz and Lutz model and the stepwise approach using PROC REG both supported a bilinear/threshold dose-response for MN induction. Liver gene expression, a mechanistic endpoint, also exhibited a bilinear dose-response. Similarly, in MNU-treated rats, hepatic DNA adducts, gene expression changes and MN all exhibited clear PoDs, with a NOGEL of 1 mkd for MN induction, although dose-response modeling of the MNU-induced MN data showed a better statistical fit for a linear dose-response. In summary, these results provide in vivo data that support the existence of clear non-linear dose-responses for a number of biologically significant events along the pathway for genotoxicity induced by DNA-reactive agents. © The Author 2015. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Vertical axis wind turbine turbulent response model. Part 2: Response of Sandia National laboratories' 34-meter VAWT with aeroelastic effects

NASA Astrophysics Data System (ADS)

1990-01-01

The dynamic response of Sandia National Laboratories' 34-m Darrieus rotor wind turbine at Bushland, Texas, is presented. The formulation used a double-multiple streamtube aerodynamic model with a turbulent airflow and included the effects of linear aeroelastic forces. The structural analysis used established procedures with the program MSC/NASTRAN. The effects of aeroelastic forces on the damping of natural modes agree well with previous results at operating rotor speeds, but show some discrepancies at very high rotor speeds. A number of alternative expressions for the spectrum of turbulent wind were investigated. The model loading represented by each does not differ significantly; a more significant difference is caused by imposing a full lateral coherence of the turbulent flow. Spectra of the predicted stresses at various locations show that without aeroelastic forces, very severe resonance is likely to occur at certain natural frequencies. Inclusion of aeroelastic effects greatly attenuates this stochastic response, especially in modes involving in-plane blade bending.

Multiple piezo-patch energy harvesters on a thin plate with respective AC-DC conversion

NASA Astrophysics Data System (ADS)

Aghakhani, Amirreza; Basdogan, Ipek

2018-03-01

Piezoelectric patch energy harvesters can be directly integrated to plate-like structures which are widely used in automotive, marine and aerospace applications, to convert vibrational energy to electrical energy. This paper presents two different AC-DC conversion techniques for multiple patch harvesters, namely single rectifier and respective rectifiers. The first case considers all the piezo-patches are connected in parallel to a single rectifier, whereas in the second case, each harvester is respectively rectified and then connected in parallel to a smoothing capacitor and a resistive load. The latter configuration of AC-DC conversion helps to avoid the electrical charge cancellation which is a problem with the multiple harvesters attached to different locations of the host plate surface. Equivalent circuit model of the multiple piezo-patch harvesters is developed in the SPICE software to simulate the electrical response. The system parameters are obtained from the modal analysis solution of the plate. Simulations of the voltage frequency response functions (FRFs) for the standard AC input - AC output case are conducted and validated by experimental data. Finally, for the AC input - DC output case, numerical simulation and experimental results of the power outputs of multiple piezo-patch harvesters with multiple AC-DC converters are obtained for a wide range of resistive loads and compared with the same array of harvesters connected to a single AC-DC converter.

Should essays and other "open-ended"-type questions retain a place in written summative assessment in clinical medicine?

PubMed

Hift, Richard J

2014-11-28

Written assessments fall into two classes: constructed-response or open-ended questions, such as the essay and a number of variants of the short-answer question, and selected-response or closed-ended questions; typically in the form of multiple-choice. It is widely believed that constructed response written questions test higher order cognitive processes in a manner that multiple-choice questions cannot, and consequently have higher validity. An extensive review of the literature suggests that in summative assessment neither premise is evidence-based. Well-structured open-ended and multiple-choice questions appear equivalent in their ability to assess higher cognitive functions, and performance in multiple-choice assessments may correlate more highly than the open-ended format with competence demonstrated in clinical practice following graduation. Studies of construct validity suggest that both formats measure essentially the same dimension, at least in mathematics, the physical sciences, biology and medicine. The persistence of the open-ended format in summative assessment may be due to the intuitive appeal of the belief that synthesising an answer to an open-ended question must be both more cognitively taxing and similar to actual experience than is selecting a correct response. I suggest that cognitive-constructivist learning theory would predict that a well-constructed context-rich multiple-choice item represents a complex problem-solving exercise which activates a sequence of cognitive processes which closely parallel those required in clinical practice, hence explaining the high validity of the multiple-choice format. The evidence does not support the proposition that the open-ended assessment format is superior to the multiple-choice format, at least in exit-level summative assessment, in terms of either its ability to test higher-order cognitive functioning or its validity. This is explicable using a theory of mental models, which might predict that the multiple-choice format will have higher validity, a statement for which some empiric support exists. Given the superior reliability and cost-effectiveness of the multiple-choice format consideration should be given to phasing out open-ended format questions in summative assessment. Whether the same applies to non-exit-level assessment and formative assessment is a question which remains to be answered; particularly in terms of the educational effect of testing, an area which deserves intensive study.

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.;

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.

[Study on correction of data bias caused by different missing mechanisms in survey of medical expenditure among students enrolling in Urban Resident Basic Medical Insurance].

PubMed

Zhang, Haixia; Zhao, Junkang; Gu, Caijiao; Cui, Yan; Rong, Huiying; Meng, Fanlong; Wang, Tong

2015-05-01

The study of the medical expenditure and its influencing factors among the students enrolling in Urban Resident Basic Medical Insurance (URBMI) in Taiyuan indicated that non response bias and selection bias coexist in dependent variable of the survey data. Unlike previous studies only focused on one missing mechanism, a two-stage method to deal with two missing mechanisms simultaneously was suggested in this study, combining multiple imputation with sample selection model. A total of 1 190 questionnaires were returned by the students (or their parents) selected in child care settings, schools and universities in Taiyuan by stratified cluster random sampling in 2012. In the returned questionnaires, 2.52% existed not missing at random (NMAR) of dependent variable and 7.14% existed missing at random (MAR) of dependent variable. First, multiple imputation was conducted for MAR by using completed data, then sample selection model was used to correct NMAR in multiple imputation, and a multi influencing factor analysis model was established. Based on 1 000 times resampling, the best scheme of filling the random missing values is the predictive mean matching (PMM) method under the missing proportion. With this optimal scheme, a two stage survey was conducted. Finally, it was found that the influencing factors on annual medical expenditure among the students enrolling in URBMI in Taiyuan included population group, annual household gross income, affordability of medical insurance expenditure, chronic disease, seeking medical care in hospital, seeking medical care in community health center or private clinic, hospitalization, hospitalization canceled due to certain reason, self medication and acceptable proportion of self-paid medical expenditure. The two-stage method combining multiple imputation with sample selection model can deal with non response bias and selection bias effectively in dependent variable of the survey data.

Advanced Modeling and Uncertainty Quantification for Flight Dynamics; Interim Results and Challenges

NASA Technical Reports Server (NTRS)

Hyde, David C.; Shweyk, Kamal M.; Brown, Frank; Shah, Gautam

2014-01-01

As part of the NASA Vehicle Systems Safety Technologies (VSST), Assuring Safe and Effective Aircraft Control Under Hazardous Conditions (Technical Challenge #3), an effort is underway within Boeing Research and Technology (BR&T) to address Advanced Modeling and Uncertainty Quantification for Flight Dynamics (VSST1-7). The scope of the effort is to develop and evaluate advanced multidisciplinary flight dynamics modeling techniques, including integrated uncertainties, to facilitate higher fidelity response characterization of current and future aircraft configurations approaching and during loss-of-control conditions. This approach is to incorporate multiple flight dynamics modeling methods for aerodynamics, structures, and propulsion, including experimental, computational, and analytical. Also to be included are techniques for data integration and uncertainty characterization and quantification. This research shall introduce new and updated multidisciplinary modeling and simulation technologies designed to improve the ability to characterize airplane response in off-nominal flight conditions. The research shall also introduce new techniques for uncertainty modeling that will provide a unified database model comprised of multiple sources, as well as an uncertainty bounds database for each data source such that a full vehicle uncertainty analysis is possible even when approaching or beyond Loss of Control boundaries. Methodologies developed as part of this research shall be instrumental in predicting and mitigating loss of control precursors and events directly linked to causal and contributing factors, such as stall, failures, damage, or icing. The tasks will include utilizing the BR&T Water Tunnel to collect static and dynamic data to be compared to the GTM extended WT database, characterizing flight dynamics in off-nominal conditions, developing tools for structural load estimation under dynamic conditions, devising methods for integrating various modeling elements into a real-time simulation capability, generating techniques for uncertainty modeling that draw data from multiple modeling sources, and providing a unified database model that includes nominal plus increments for each flight condition. This paper presents status of testing in the BR&T water tunnel and analysis of the resulting data and efforts to characterize these data using alternative modeling methods. Program challenges and issues are also presented.

Online two-stage association method for robust multiple people tracking

NASA Astrophysics Data System (ADS)

Lv, Jingqin; Fang, Jiangxiong; Yang, Jie

2011-07-01

Robust multiple people tracking is very important for many applications. It is a challenging problem due to occlusion and interaction in crowded scenarios. This paper proposes an online two-stage association method for robust multiple people tracking. In the first stage, short tracklets generated by linking people detection responses grow longer by particle filter based tracking, with detection confidence embedded into the observation model. And, an examining scheme runs at each frame for the reliability of tracking. In the second stage, multiple people tracking is achieved by linking tracklets to generate trajectories. An online tracklet association method is proposed to solve the linking problem, which allows applications in time-critical scenarios. This method is evaluated on the popular CAVIAR dataset. The experimental results show that our two-stage method is robust.

Trusted Autonomy: Concept Development in Technology Foresight

DTIC Science & Technology

2015-09-01

executing the response . UNCLASSIFIED 19 UNCLASSIFIED DST-Group-TR-3153 UNCLASSIFIED 20 Previous models explored autonomy through the lenses of...w /users to leam to tackle complex problems Robots are able to intanalise and use world models Controllers have multiple modules based on leru.ning...technology across society. It aims to describe usage or uptake, and evolving trends, in technological development over time. Through doing so, it seeks to

The Role of Protein Radicals in Chronic Neuroimmune Dysfunction and Neuropathology in Response to a Multiple-Hit Model of Gulf War Exposures

DTIC Science & Technology

2015-10-01

neurotoxicants and triggers of inflammation, such as persistent peripheral inflammation and the organophosphate pesticide chlorpyrifos (CPF) may interact to...Model, Chlorpyrifos , LPS, NF-KB p50, microglia, chronic neuroinflammation, serum markers, neuropathology 16. SECURITY CLASSIFICATION OF: 17...potential neurotoxicants and triggers of inflammation, such as persistent infections, and the organophosphate pesticide chlorpyrifos (CPF) may

EEG and MEG data analysis in SPM8.

PubMed

Litvak, Vladimir; Mattout, Jérémie; Kiebel, Stefan; Phillips, Christophe; Henson, Richard; Kilner, James; Barnes, Gareth; Oostenveld, Robert; Daunizeau, Jean; Flandin, Guillaume; Penny, Will; Friston, Karl

2011-01-01

SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools.

EEG and MEG Data Analysis in SPM8

PubMed Central

Litvak, Vladimir; Mattout, Jérémie; Kiebel, Stefan; Phillips, Christophe; Henson, Richard; Kilner, James; Barnes, Gareth; Oostenveld, Robert; Daunizeau, Jean; Flandin, Guillaume; Penny, Will; Friston, Karl

2011-01-01

SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools. PMID:21437221

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.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

A response surface methodology based damage identification technique

NASA Astrophysics Data System (ADS)

Fang, S. E.; Perera, R.

2009-06-01

Response surface methodology (RSM) is a combination of statistical and mathematical techniques to represent the relationship between the inputs and outputs of a physical system by explicit functions. This methodology has been widely employed in many applications such as design optimization, response prediction and model validation. But so far the literature related to its application in structural damage identification (SDI) is scarce. Therefore this study attempts to present a systematic SDI procedure comprising four sequential steps of feature selection, parameter screening, primary response surface (RS) modeling and updating, and reference-state RS modeling with SDI realization using the factorial design (FD) and the central composite design (CCD). The last two steps imply the implementation of inverse problems by model updating in which the RS models substitute the FE models. The proposed method was verified against a numerical beam, a tested reinforced concrete (RC) frame and an experimental full-scale bridge with the modal frequency being the output responses. It was found that the proposed RSM-based method performs well in predicting the damage of both numerical and experimental structures having single and multiple damage scenarios. The screening capacity of the FD can provide quantitative estimation of the significance levels of updating parameters. Meanwhile, the second-order polynomial model established by the CCD provides adequate accuracy in expressing the dynamic behavior of a physical system.

Stable scalable control of soliton propagation in broadband nonlinear optical waveguides

NASA Astrophysics Data System (ADS)

Peleg, Avner; Nguyen, Quan M.; Huynh, Toan T.

2017-02-01

We develop a method for achieving scalable transmission stabilization and switching of N colliding soliton sequences in optical waveguides with broadband delayed Raman response and narrowband nonlinear gain-loss. We show that dynamics of soliton amplitudes in N-sequence transmission is described by a generalized N-dimensional predator-prey model. Stability and bifurcation analysis for the predator-prey model are used to obtain simple conditions on the physical parameters for robust transmission stabilization as well as on-off and off-on switching of M out of N soliton sequences. Numerical simulations for single-waveguide transmission with a system of N coupled nonlinear Schrödinger equations with 2 ≤ N ≤ 4 show excellent agreement with the predator-prey model's predictions and stable propagation over significantly larger distances compared with other broadband nonlinear single-waveguide systems. Moreover, stable on-off and off-on switching of multiple soliton sequences and stable multiple transmission switching events are demonstrated by the simulations. We discuss the reasons for the robustness and scalability of transmission stabilization and switching in waveguides with broadband delayed Raman response and narrowband nonlinear gain-loss, and explain their advantages compared with other broadband nonlinear waveguides.

Non-Lipschitzian dynamics for neural net modelling

NASA Technical Reports Server (NTRS)

Zak, Michail

1989-01-01

Failure of the Lipschitz condition in unstable equilibrium points of dynamical systems leads to a multiple-choice response to an initial deterministic input. The evolution of such systems is characterized by a special type of unpredictability measured by unbounded Liapunov exponents. Possible relation of these systems to future neural networks is discussed.

HexSim: A flexible simulation model for forecasting wildlife responses to multiple interacting stressors

EPA Science Inventory

With SERDP funding, we have improved upon a popular life history simulator (PATCH), and in doing so produced a powerful new forecasting tool (HexSim). PATCH, our starting point, was spatially explicit and individual-based, and was useful for evaluating a range of terrestrial lif...

Investigating Psychometric Isomorphism for Traditional and Performance-Based Assessment

ERIC Educational Resources Information Center

Fay, Derek M.; Levy, Roy; Mehta, Vandhana

2018-01-01

A common practice in educational assessment is to construct multiple forms of an assessment that consists of tasks with similar psychometric properties. This study utilizes a Bayesian multilevel item response model and descriptive graphical representations to evaluate the psychometric similarity of variations of the same task. These approaches for…

ASSESSMENT OF LAKE ECOSYSTEM RESPONSE TO TOXIC EVENTS WITH THE AQUATOX MODEL

EPA Science Inventory

An attack involving a toxic chemical added to a water resource could have multiple effects on the aquatic ecosystem of that resource. This is particularly significant for systems such as lakes and reservoirs, where the residence time of water is long and there is more opportunit...

New Zealand Management Students' Perceptions of Communication Technologies in Correspondence Education.

ERIC Educational Resources Information Center

Ostman, Ronald E.; Wagner, Graham A.

1987-01-01

Describes a survey of 724 management students in New Zealand's Technical Correspondence Institute which was conducted to determine whether the introduction of educational technologies could decrease the dropout rate. The multiple linear regression model that was used to analyze the questionnaire responses is presented, and predictor variables are…

Rat Models of Cardiovascular Disease Demonstrate Distinctive Pulmonary Gene Expressions for Vascular Response Genes: Impact of Ozone Exposure

EPA Science Inventory

Comparative gene expression profiling of multiple tissues from rat strains with genetic predisposition to diverse cardiovascular diseases (CVD) can help decode the transcriptional program that governs organ-specific functions. We examined expressions of CVD genes in the lungs of ...

Terrestrial biogeochemical cycles - Global interactions with the atmosphere and hydrology

NASA Technical Reports Server (NTRS)

Schimel, David S.; Parton, William J.; Kittel, Timothy G. F.

1991-01-01

A review is presented of developments in ecosystem theory, remote sensing, and geographic information systems that support new endeavors in spatial modeling. A paradigm has emerged to predict ecosystem behavior based on understanding responses to multiple resources. Ecosystem models couple primary production to decomposition and nutrient availability utilizing this paradigm. It is indicated that coupling of transport and ecosystem processes alters the behavior of earth system components (terrestrial ecosystems, hydrology, and the atmosphere) from that of an uncoupled model.

Simulating Vibrations in a Complex Loaded Structure

NASA Technical Reports Server (NTRS)

Cao, Tim T.

2005-01-01

The Dynamic Response Computation (DIRECT) computer program simulates vibrations induced in a complex structure by applied dynamic loads. Developed to enable rapid analysis of launch- and landing- induced vibrations and stresses in a space shuttle, DIRECT also can be used to analyze dynamic responses of other structures - for example, the response of a building to an earthquake, or the response of an oil-drilling platform and attached tanks to large ocean waves. For a space-shuttle simulation, the required input to DIRECT includes mathematical models of the space shuttle and its payloads, and a set of forcing functions that simulates launch and landing loads. DIRECT can accommodate multiple levels of payload attachment and substructure as well as nonlinear dynamic responses of structural interfaces. DIRECT combines the shuttle and payload models into a single structural model, to which the forcing functions are then applied. The resulting equations of motion are reduced to an optimum set and decoupled into a unique format for simulating dynamics. During the simulation, maximum vibrations, loads, and stresses are monitored and recorded for subsequent analysis to identify structural deficiencies in the shuttle and/or payloads.

Life-history strategies constrain invertebrate community tolerance to multiple stressors: A case study in the Ebro basin.

PubMed

Mondy, Cédric P; Muñoz, Isabel; Dolédec, Sylvain

2016-12-01

Multiple stressors constitute a serious threat to aquatic ecosystems, particularly in the Mediterranean region where water scarcity is likely to interact with other anthropogenic stressors. Biological traits potentially allow the unravelling of the effects of multiple stressors. However, thus far, trait-based approaches have failed to fully deliver on their promise and still lack strong predictive power when multiple stressors are present. We aimed to quantify specific community tolerances against six anthropogenic stressors and investigate the responses of the underlying macroinvertebrate biological traits and their combinations. We built and calibrated boosted regression tree models to predict community tolerances using multiple biological traits with a priori hypotheses regarding their individual responses to specific stressors. We analysed the combinations of traits underlying community tolerance and the effect of trait association on this tolerance. Our results validated the following three hypotheses: (i) the community tolerance models efficiently and robustly related trait combinations to stressor intensities and, to a lesser extent, to stressors related to the presence of dams and insecticides; (ii) the effects of traits on community tolerance not only depended on trait identity but also on the trait associations emerging at the community level from the co-occurrence of different traits in species; and (iii) the community tolerances and the underlying trait combinations were specific to the different stressors. This study takes a further step towards predictive tools in community ecology that consider combinations and associations of traits as the basis of stressor tolerance. Additionally, the community tolerance concept has potential application to help stream managers in the decision process regarding management options. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Performance of Geant4 in simulating semiconductor particle detector response in the energy range below 1 MeV

NASA Astrophysics Data System (ADS)

Soti, G.; Wauters, F.; Breitenfeldt, M.; Finlay, P.; Kraev, I. S.; Knecht, A.; Porobić, T.; Zákoucký, D.; Severijns, N.

2013-11-01

Geant4 simulations play a crucial role in the analysis and interpretation of experiments providing low energy precision tests of the Standard Model. This paper focuses on the accuracy of the description of the electron processes in the energy range between 100 and 1000 keV. The effect of the different simulation parameters and multiple scattering models on the backscattering coefficients is investigated. Simulations of the response of HPGe and passivated implanted planar Si detectors to β particles are compared to experimental results. An overall good agreement is found between Geant4 simulations and experimental data.

Novel Therapeutics for Multiple Sclerosis Designed by Parasitic Worms.

PubMed

Dixit, Aakanksha; Tanaka, Akane; Greer, Judith M; Donnelly, Sheila

2017-10-13

The evolutionary response to endemic infections with parasitic worms (helminth) was the development of a distinct regulatory immune profile arising from the need to encapsulate the helminths while simultaneously repairing tissue damage. According to the old friend's hypothesis, the diminished exposure to these parasites in the developed world has resulted in a dysregulated immune response that contributes to the increased incidence of immune mediated diseases such as Multiple Sclerosis (MS). Indeed, the global distribution of MS shows an inverse correlation to the prevalence of helminth infection. On this basis, the possibility of treating MS with helminth infection has been explored in animal models and phase 1 and 2 human clinical trials. However, the possibility also exists that the individual immune modulatory molecules secreted by helminth parasites may offer a more defined therapeutic strategy.

Variable- and Person-Centered Approaches to Examining Temperament Vulnerability and Resilience to the Effects of Contextual Risk

PubMed Central

Moran, Lyndsey; Lengua, Liliana J.; Zalewski, Maureen; Ruberry, Erika; Klien, Melanie; Thompson, Stephanie; Kiff, Cara

2016-01-01

Using both variable- and person-centered approaches, this study examined the role of temperament in relation to children's vulnerable or resilient responses to cumulative risk. Observed reactivity and regulation dimensions of temperament were tested as mediating and moderating the relation between family cumulative risk and teacher-reported adjustment problems in a sample of 259 preschool-age children. Further, latent profile analyses were used to examine whether profiles of temperament, accounting for multiple characteristics simultaneously, provided additional information about the role of temperament in children's responses to risk. Results support a diathesis-stress model in which high frustration, low fear, and low delay ability confer particular vulnerability for children in high-risk contexts. Benefits of multiple approaches are highlighted. PMID:28408769

Virally delivered Channelrhodopsin-2 Safely and Effectively Restores Visual Function in Multiple Mouse Models of Blindness

PubMed Central

Doroudchi, M Mehdi; Greenberg, Kenneth P; Liu, Jianwen; Silka, Kimberly A; Boyden, Edward S; Lockridge, Jennifer A; Arman, A Cyrus; Janani, Ramesh; Boye, Shannon E; Boye, Sanford L; Gordon, Gabriel M; Matteo, Benjamin C; Sampath, Alapakkam P; Hauswirth, William W; Horsager, Alan

2011-01-01

Previous work established retinal expression of channelrhodopsin-2 (ChR2), an algal cation channel gated by light, restored physiological and behavioral visual responses in otherwise blind rd1 mice. However, a viable ChR2-based human therapy must meet several key criteria: (i) ChR2 expression must be targeted, robust, and long-term, (ii) ChR2 must provide long-term and continuous therapeutic efficacy, and (iii) both viral vector delivery and ChR2 expression must be safe. Here, we demonstrate the development of a clinically relevant therapy for late stage retinal degeneration using ChR2. We achieved specific and stable expression of ChR2 in ON bipolar cells using a recombinant adeno-associated viral vector (rAAV) packaged in a tyrosine-mutated capsid. Targeted expression led to ChR2-driven electrophysiological ON responses in postsynaptic retinal ganglion cells and significant improvement in visually guided behavior for multiple models of blindness up to 10 months postinjection. Light levels to elicit visually guided behavioral responses were within the physiological range of cone photoreceptors. Finally, chronic ChR2 expression was nontoxic, with transgene biodistribution limited to the eye. No measurable immune or inflammatory response was observed following intraocular vector administration. Together, these data indicate that virally delivered ChR2 can provide a viable and efficacious clinical therapy for photoreceptor disease-related blindness. PMID:21505421

An application of a Hill-based response surface model for a drug combination experiment on lung cancer.

PubMed

Ning, Shaoyang; Xu, Hongquan; Al-Shyoukh, Ibrahim; Feng, Jiaying; Sun, Ren

2014-10-30

Combination chemotherapy with multiple drugs has been widely applied to cancer treatment owing to enhanced efficacy and reduced drug resistance. For drug combination experiment analysis, response surface modeling has been commonly adopted. In this paper, we introduce a Hill-based global response surface model and provide an application of the model to a 512-run drug combination experiment with three chemicals, namely AG490, U0126, and indirubin-3  ' -monoxime (I-3-M), on lung cancer cells. The results demonstrate generally improved goodness of fit of our model from the traditional polynomial model, as well as the original Hill model on the basis of fixed-ratio drug combinations. We identify different dose-effect patterns between normal and cancer cells on the basis of our model, which indicates the potential effectiveness of the drug combination in cancer treatment. Meanwhile, drug interactions are analyzed both qualitatively and quantitatively. The distinct interaction patterns between U0126 and I-3-M on two types of cells uncovered by the model could be a further indicator of the efficacy of the drug combination. Copyright © 2014 John Wiley & Sons, Ltd.

Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

PubMed Central

Bredbenner, Todd L.; Eliason, Travis D.; Francis, W. Loren; McFarland, John M.; Merkle, Andrew C.; Nicolella, Daniel P.

2014-01-01

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures. PMID:25506051

A Cognitive System Model for Human/Automation Dynamics in Airspace Management

NASA Technical Reports Server (NTRS)

Corker, Kevin M.; Pisanich, Gregory; Lebacqz, J. Victor (Technical Monitor)

1997-01-01

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.

An efficient multistage algorithm for full calibration of the hemodynamic model from BOLD signal responses.

PubMed

Zambri, Brian; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

2017-11-01

We propose a computational strategy that falls into the category of prediction/correction iterative-type approaches, for calibrating the hemodynamic model. The proposed method is used to estimate consecutively the values of the two sets of model parameters. Numerical results corresponding to both synthetic and real functional magnetic resonance imaging measurements for a single stimulus as well as for multiple stimuli are reported to highlight the capability of this computational methodology to fully calibrate the considered hemodynamic model. Copyright © 2017 John Wiley & Sons, Ltd.

Intrinsic optical signal imaging of glucose-stimulated physiological responses in the insulin secreting INS-1 β-cell line

NASA Astrophysics Data System (ADS)

Li, Yi-Chao; Cui, Wan-Xing; Wang, Xu-Jing; Amthor, Franklin; Yao, Xin-Cheng

2011-03-01

Intrinsic optical signal (IOS) imaging has been established for noninvasive monitoring of stimulus-evoked physiological responses in the retina and other neural tissues. Recently, we extended the IOS imaging technology for functional evaluation of insulin secreting INS-1 cells. INS-1 cells provide a popular model for investigating β-cell dysfunction and diabetes. Our experiments indicate that IOS imaging allows simultaneous monitoring of glucose-stimulated physiological responses in multiple cells with high spatial (sub-cellular) and temporal (sub-second) resolution. Rapid image sequences reveal transient optical responses that have time courses comparable to glucose-evoked β-cell electrical activities.

Modeling caprock fracture, CO2 migration and time dependent fault healing: A numerical study.

NASA Astrophysics Data System (ADS)

MacFarlane, J.; Mukerji, T.; Vanorio, T.

2017-12-01

The Campi Flegrei caldera, located near Naples, Italy, is one of the highest risk volcanoes on Earth due to its recent unrest and urban setting. A unique history of surface uplift within the caldera is characterized by long duration uplift and subsidence cycles which are periodically interrupted by rapid, short period uplift events. Several models have been proposed to explain this history; in this study we will present a hydro-mechanical model that takes into account the caprock that seismic studies show to exist at 1-2 km depth. Specifically, we develop a finite element model of the caldera and use a modified version of fault-valve theory to represent fracture within the caprock. The model accounts for fault healing using a simplified, time-dependent fault sealing model. Multiple fracture events are incorporated by using previous solutions to test prescribed conditions and determine changes in rock properties, such as porosity and permeability. Although fault-valve theory has been used to model single fractures and recharge, this model is unique in its ability to model multiple fracture events. By incorporating multiple fracture events we can assess changes in both long and short-term reservoir behavior at Campi Flegrei. By varying the model inputs, we model the poro-elastic response to CO2 injection at depth and the resulting surface deformation. The goal is to enable geophysicists to better interpret surface observations and predict outcomes from observed changes in reservoir conditions.

Modeling multiple resource limitation in tropical dry forests

NASA Astrophysics Data System (ADS)

Medvigy, D.; Xu, X.; Zarakas, C.

2015-12-01

Tropical dry forests (TDFs) are characterized by a long dry season when little rain falls. At the same time, many neotropical soils are highly weathered and relatively nutrient poor. Because TDFs are often subject to both water and nutrient constraints, the question of how they will respond to environmental perturbations is both complex and highly interesting. Models, our basic tools for projecting ecosystem responses to global change, can be used to address this question. However, few models have been specifically parameterized for TDFs. Here, we present a new version of the Ecosystem Demography 2 (ED2) model that includes a new parameterization of TDFs. In particular, we focus on the model's framework for representing limitation by multiple resources (carbon, water, nitrogen, and phosphorus). Plant functional types are represented in terms of a dichotomy between "acquisitive" and "conservative" resource acquisition strategies. Depending on their resource acquisition strategy and basic stoichiometry, plants can dynamically adjust their allocation to organs (leaves, stem, roots), symbionts (e.g. N2-fixing bacteria), and mycorrhizal fungi. Several case studies are used to investigate how resource acquisition strategies affect ecosystem responses to environmental perturbations. Results are described in terms of the basic setting (e.g., rich vs. poor soils; longer vs. shorter dry season), and well as the type and magnitude of environmental perturbation (e.g., changes in precipitation or temperature; changes in nitrogen deposition). Implications for ecosystem structure and functioning are discussed.

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.

Deteriorated Stress Response in Stationary-Phase Yeast: Sir2 and Yap1 Are Essential for Hsf1 Activation by Heat Shock and Oxidative Stress, Respectively

PubMed Central

Cohen, Aviv; Bar-Nun, Shoshana

2014-01-01

Stationary-phase cultures have been used as an important model of aging, a complex process involving multiple pathways and signaling networks. However, the molecular processes underlying stress response of non-dividing cells are poorly understood, although deteriorated stress response is one of the hallmarks of aging. The budding yeast Saccharomyces cerevisiae is a valuable model organism to study the genetics of aging, because yeast ages within days and are amenable to genetic manipulations. As a unicellular organism, yeast has evolved robust systems to respond to environmental challenges. This response is orchestrated largely by the conserved transcription factor Hsf1, which in S. cerevisiae regulates expression of multiple genes in response to diverse stresses. Here we demonstrate that Hsf1 response to heat shock and oxidative stress deteriorates during yeast transition from exponential growth to stationary-phase, whereas Hsf1 activation by glucose starvation is maintained. Overexpressing Hsf1 does not significantly improve heat shock response, indicating that Hsf1 dwindling is not the major cause for Hsf1 attenuated response in stationary-phase yeast. Rather, factors that participate in Hsf1 activation appear to be compromised. We uncover two factors, Yap1 and Sir2, which discretely function in Hsf1 activation by oxidative stress and heat shock. In Δyap1 mutant, Hsf1 does not respond to oxidative stress, while in Δsir2 mutant, Hsf1 does not respond to heat shock. Moreover, excess Sir2 mimics the heat shock response. This role of the NAD+-dependent Sir2 is supported by our finding that supplementing NAD+ precursors improves Hsf1 heat shock response in stationary-phase yeast, especially when combined with expression of excess Sir2. Finally, the combination of excess Hsf1, excess Sir2 and NAD+ precursors rejuvenates the heat shock response. PMID:25356557

Deteriorated stress response in stationary-phase yeast: Sir2 and Yap1 are essential for Hsf1 activation by heat shock and oxidative stress, respectively.

PubMed

Nussbaum, Inbal; Weindling, Esther; Jubran, Ritta; Cohen, Aviv; Bar-Nun, Shoshana

2014-01-01

Stationary-phase cultures have been used as an important model of aging, a complex process involving multiple pathways and signaling networks. However, the molecular processes underlying stress response of non-dividing cells are poorly understood, although deteriorated stress response is one of the hallmarks of aging. The budding yeast Saccharomyces cerevisiae is a valuable model organism to study the genetics of aging, because yeast ages within days and are amenable to genetic manipulations. As a unicellular organism, yeast has evolved robust systems to respond to environmental challenges. This response is orchestrated largely by the conserved transcription factor Hsf1, which in S. cerevisiae regulates expression of multiple genes in response to diverse stresses. Here we demonstrate that Hsf1 response to heat shock and oxidative stress deteriorates during yeast transition from exponential growth to stationary-phase, whereas Hsf1 activation by glucose starvation is maintained. Overexpressing Hsf1 does not significantly improve heat shock response, indicating that Hsf1 dwindling is not the major cause for Hsf1 attenuated response in stationary-phase yeast. Rather, factors that participate in Hsf1 activation appear to be compromised. We uncover two factors, Yap1 and Sir2, which discretely function in Hsf1 activation by oxidative stress and heat shock. In Δyap1 mutant, Hsf1 does not respond to oxidative stress, while in Δsir2 mutant, Hsf1 does not respond to heat shock. Moreover, excess Sir2 mimics the heat shock response. This role of the NAD+-dependent Sir2 is supported by our finding that supplementing NAD+ precursors improves Hsf1 heat shock response in stationary-phase yeast, especially when combined with expression of excess Sir2. Finally, the combination of excess Hsf1, excess Sir2 and NAD+ precursors rejuvenates the heat shock response.

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Precision analysis of the photomultiplier response to ultra low signals

NASA Astrophysics Data System (ADS)

Degtiarenko, Pavel

2017-11-01

A new computational model for the description of the photon detector response functions measured in conditions of low light is presented, together with examples of the observed photomultiplier signal amplitude distributions, successfully described using the parameterized model equation. In extension to the previously known approximations, the new model describes the underlying discrete statistical behavior of the photoelectron cascade multiplication processes in photon detectors with complex non-uniform gain structure of the first dynode. Important features of the model include the ability to represent the true single-photoelectron spectra from different photomultipliers with a variety of parameterized shapes, reflecting the variability in the design and in the individual parameters of the detectors. The new software tool is available for evaluation of the detectors' performance, response, and efficiency parameters that may be used in various applications including the ultra low background experiments such as the searches for Dark Matter and rare decays, underground neutrino studies, optimizing operations of the Cherenkov light detectors, help in the detector selection procedures, and in the experiment simulations.

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

Reducing attenuation in exposure-response relationships by exposure modeling and grouping: the relationship between wood dust exposure and lung function.

PubMed

Teschke, Kay; Spierings, Judith; Marion, Stephen A; Demers, Paul A; Davies, Hugh W; Kennedy, Susan M

2004-12-01

In a study of wood dust exposure and lung function, we tested the effect on the exposure-response relationship of six different exposure metrics using the mean measured exposure of each subject versus the mean exposure based on various methods of grouping subjects, including job-based groups and groups based on an empirical model of the determinants of exposure. Multiple linear regression was used to examine the association between wood dust concentration and forced expiratory volume in 1s (FEV(1)), adjusting for age, sex, height, race, pediatric asthma, and smoking. Stronger point estimates of the exposure-response relationships were observed when exposures were based on increasing levels of aggregation, allowing the relationships to be found statistically significant in four of the six metrics. The strongest point estimates were found when exposures were based on the determinants of exposure model. Determinants of exposure modeling offers the potential for improvement in risk estimation equivalent to or beyond that from job-based exposure grouping.

Engineered reversal of drug resistance in cancer cells--metastases suppressor factors as change agents.

PubMed

Yadav, Vinod Kumar; Kumar, Akinchan; Mann, Anita; Aggarwal, Suruchi; Kumar, Maneesh; Roy, Sumitabho Deb; Pore, Subrata Kumar; Banerjee, Rajkumar; Mahesh Kumar, Jerald; Thakur, Ram Krishna; Chowdhury, Shantanu

2014-01-01

Building molecular correlates of drug resistance in cancer and exploiting them for therapeutic intervention remains a pressing clinical need. To identify factors that impact drug resistance herein we built a model that couples inherent cell-based response toward drugs with transcriptomes of resistant/sensitive cells. To test this model, we focused on a group of genes called metastasis suppressor genes (MSGs) that influence aggressiveness and metastatic potential of cancers. Interestingly, modeling of 84 000 drug response transcriptome combinations predicted multiple MSGs to be associated with resistance of different cell types and drugs. As a case study, on inducing MSG levels in a drug resistant breast cancer line resistance to anticancer drugs caerulomycin, camptothecin and topotecan decreased by more than 50-60%, in both culture conditions and also in tumors generated in mice, in contrast to control un-induced cells. To our knowledge, this is the first demonstration of engineered reversal of drug resistance in cancer cells based on a model that exploits inherent cellular response profiles.

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.

Brassinosteroid and gibberellin control of seedling traits in maize (Zea mays L.).

PubMed

Hu, Songlin; Sanchez, Darlene L; Wang, Cuiling; Lipka, Alexander E; Yin, Yanhai; Gardner, Candice A C; Lübberstedt, Thomas

2017-10-01

In this study, we established two doubled haploid (DH) libraries with a total of 207 DH lines. We applied BR and GA inhibitors to all DH lines at seedling stage and measured seedling BR and GA inhibitor responses. Moreover, we evaluated field traits for each DH line (untreated). We conducted genome-wide association studies (GWAS) with 62,049 genome wide SNPs to explore the genetic control of seedling traits by BR and GA. In addition, we correlate seedling stage hormone inhibitor response with field traits. Large variation for BR and GA inhibitor response and field traits was observed across these DH lines. Seedling stage BR and GA inhibitor response was significantly correlate with yield and flowering time. Using three different GWAS approaches to balance false positive/negatives, multiple SNPs were discovered to be significantly associated with BR/GA inhibitor responses with some localized within gene models. SNPs from gene model GRMZM2G013391 were associated with GA inhibitor response across all three GWAS models. This gene is expressed in roots and shoots and was shown to regulate GA signaling. These results show that BRs and GAs have a great impact for controlling seedling growth. Gene models from GWAS results could be targets for seeding traits improvement. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional response of wolves preying on barren-ground caribou in a multiple-prey ecosystem

USGS Publications Warehouse

Dale, B.W.; Adams, Layne G.; Bowyer, R.T.

1994-01-01

1. We investigated the functional response of wolves (Canis lupus) to varying abundance of ungulate prey to test the hypothesis that switching from alternate prey to preferred prey results in regulation of a caribou (Rangifer tarandus) population at low densities. 2. We determined prey selection, kill rates, and prey abundance for four wolf packs during three 30-day periods in March 1989, March 1990, November 1990, and created a simple discrete model to evaluate the potential for the expected numerical and observed functional responses of wolves to regulate caribou populations. 3. We observed a quickly decelerating type II functional response that, in the absence of numerical response, implicates an anti-regulatory effect of wolf predation on barren-ground caribou dynamics. 4. There was little potential for regulation caused by the multiplicative effect of increasing functional and numerical responses because of presence of alternative prey. This resulted in high wolf:caribou ratios at low prey densities which precluded the effects of an increasing functional response. 5. Inversely density-dependent predation by other predators, such as bears, reduces the potential for predators to regulate caribou populations at low densities, and small reductions in predation by one predator may have disproportionately large effects on the total predation rate.

Separability of stimulus parameter encoding by on-off directionally selective rabbit retinal ganglion cells

PubMed Central

Nowak, Przemyslaw; Dobbins, Allan C.; Gawne, Timothy J.; Grzywacz, Norberto M.

2011-01-01

The ganglion cell output of the retina constitutes a bottleneck in sensory processing in that ganglion cells must encode multiple stimulus parameters in their responses. Here we investigate encoding strategies of On-Off directionally selective retinal ganglion cells (On-Off DS RGCs) in rabbits, a class of cells dedicated to representing motion. The exquisite axial discrimination of these cells to preferred vs. null direction motion is well documented: it is invariant with respect to speed, contrast, spatial configuration, spatial frequency, and motion extent. However, these cells have broad direction tuning curves and their responses also vary as a function of other parameters such as speed and contrast. In this study, we examined whether the variation in responses across multiple stimulus parameters is systematic, that is the same for all cells, and separable, such that the response to a stimulus is a product of the effects of each stimulus parameter alone. We extracellularly recorded single On-Off DS RGCs in a superfused eyecup preparation while stimulating them with moving bars. We found that spike count responses of these cells scaled as independent functions of direction, speed, and luminance. Moreover, the speed and luminance functions were common across the whole sample of cells. Based on these findings, we developed a model that accurately predicted responses of On-Off DS RGCs as products of separable functions of direction, speed, and luminance (r = 0.98; P < 0.0001). Such a multiplicatively separable encoding strategy may simplify the decoding of these cells' outputs by the higher visual centers. PMID:21325684

Shock spectra applications to a class of multiple degree-of-freedom structures system

NASA Technical Reports Server (NTRS)

Hwang, Shoi Y.

1988-01-01

The demand on safety performance of launching structure and equipment system from impulsive excitations necessitates a study which predicts the maximum response of the system as well as the maximum stresses in the system. A method to extract higher modes and frequencies for a class of multiple degree-of-freedom (MDOF) Structure system is proposed. And, along with the shock spectra derived from a linear oscillator model, a procedure to obtain upper bound solutions for maximum displacement and maximum stresses in the MDOF system is presented.

Forward modeling transient brightenings and microflares around an active region observed with Hi-C

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

Kobelski, Adam R.; McKenzie, David E., E-mail: kobelski@solar.physics.montana.edu

Small-scale flare-like brightenings around active regions are among the smallest and most fundamental of energetic transient events in the corona, providing a testbed for models of heating and active region dynamics. In a previous study, we modeled a large collection of these microflares observed with Hinode/X-Ray Telescope (XRT) using EBTEL and found that they required multiple heating events, but could not distinguish between multiple heating events on a single strand, or multiple strands each experiencing a single heating event. We present here a similar study, but with extreme-ultraviolet data of Active Region 11520 from the High Resolution Coronal Imager (Hi-C)more » sounding rocket. Hi-C provides an order of magnitude improvement to the spatial resolution of XRT, and a cooler temperature sensitivity, which combine to provide significant improvements to our ability to detect and model microflare activity around active regions. We have found that at the spatial resolution of Hi-C (≈0.''3), the events occur much more frequently than expected (57 events detected, only 1 or 2 expected), and are most likely made from strands of the order of 100 km wide, each of which is impulsively heated with multiple heating events. These findings tend to support bursty reconnection as the cause of the energy release responsible for the brightenings.« less

Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

NASA Astrophysics Data System (ADS)

Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin

2016-08-01

This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

A stochastic multiple imputation algorithm for missing covariate data in tree-structured survival analysis.

PubMed

Wallace, Meredith L; Anderson, Stewart J; Mazumdar, Sati

2010-12-20

Missing covariate data present a challenge to tree-structured methodology due to the fact that a single tree model, as opposed to an estimated parameter value, may be desired for use in a clinical setting. To address this problem, we suggest a multiple imputation algorithm that adds draws of stochastic error to a tree-based single imputation method presented by Conversano and Siciliano (Technical Report, University of Naples, 2003). Unlike previously proposed techniques for accommodating missing covariate data in tree-structured analyses, our methodology allows the modeling of complex and nonlinear covariate structures while still resulting in a single tree model. We perform a simulation study to evaluate our stochastic multiple imputation algorithm when covariate data are missing at random and compare it to other currently used methods. Our algorithm is advantageous for identifying the true underlying covariate structure when complex data and larger percentages of missing covariate observations are present. It is competitive with other current methods with respect to prediction accuracy. To illustrate our algorithm, we create a tree-structured survival model for predicting time to treatment response in older, depressed adults. Copyright © 2010 John Wiley & Sons, Ltd.

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

Pseudofracture: an acute peripheral tissue trauma model.

PubMed

Darwiche, Sophie S; Kobbe, Philipp; Pfeifer, Roman; Kohut, Lauryn; Pape, Hans-Christoph; Billiar, Timothy

2011-04-18

Following trauma there is an early hyper-reactive inflammatory response that can lead to multiple organ dysfunction and high mortality in trauma patients; this response is often accompanied by a delayed immunosuppression that adds the clinical complications of infection and can also increase mortality. Many studies have begun to assess these changes in the reactivity of the immune system following trauma. Immunologic studies are greatly supported through the wide variety of transgenic and knockout mice available for in vivo modeling; these strains aid in detailed investigations to assess the molecular pathways involved in the immunologic responses. The challenge in experimental murine trauma modeling is long term investigation, as fracture fixation techniques in mice, can be complex and not easily reproducible. This pseudofracture model, an easily reproduced trauma model, overcomes these difficulties by immunologically mimicking an extremity fracture environment, while allowing freedom of movement in the animals and long term survival without the continual, prolonged use of anaesthesia. The intent is to recreate the features of long bone fracture; injured muscle and soft tissue are exposed to damaged bone and bone marrow without breaking the native bone. The pseudofracture model consists of two parts: a bilateral muscle crush injury to the hindlimbs, followed by injection of a bone solution into these injured muscles. The bone solution is prepared by harvesting the long bones from both hindlimbs of an age- and weight-matched syngeneic donor. These bones are then crushed and resuspended in phosphate buffered saline to create the bone solution. Bilateral femur fracture is a commonly used and well-established model of extremity trauma, and was the comparative model during the development of the pseudofracture model. Among the variety of available fracture models, we chose to use a closed method of fracture with soft tissue injury as our comparison to the pseudofracture, as we wanted a sterile yet proportionally severe peripheral tissue trauma model. Hemorrhagic shock is a common finding in the setting of severe trauma, and the global hypoperfusion adds a very relevant element to a trauma model. The pseudofracture model can be easily combined with a hemorrhagic shock model for a multiple trauma model of high severity.

Bayesian dose-response analysis for epidemiological studies with complex uncertainty in dose estimation.

PubMed

Kwon, Deukwoo; Hoffman, F Owen; Moroz, Brian E; Simon, Steven L

2016-02-10

Most conventional risk analysis methods rely on a single best estimate of exposure per person, which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the relationship between radiation dose and disease outcomes by accounting for shared and unshared uncertainty in estimated dose. Our Bayesian risk analysis method utilizes multiple realizations of sets (vectors) of doses generated by a two-dimensional Monte Carlo simulation method that properly separates shared and unshared errors in dose estimation. The exposure model used in this work is taken from a study of the risk of thyroid nodules among a cohort of 2376 subjects who were exposed to fallout from nuclear testing in Kazakhstan. We assessed the performance of our method through an extensive series of simulations and comparisons against conventional regression risk analysis methods. When the estimated doses contain relatively small amounts of uncertainty, the Bayesian method using multiple a priori plausible draws of dose vectors gave similar results to the conventional regression-based methods of dose-response analysis. However, when large and complex mixtures of shared and unshared uncertainties are present, the Bayesian method using multiple dose vectors had significantly lower relative bias than conventional regression-based risk analysis methods and better coverage, that is, a markedly increased capability to include the true risk coefficient within the 95% credible interval of the Bayesian-based risk estimate. An evaluation of the dose-response using our method is presented for an epidemiological study of thyroid disease following radiation exposure. Copyright © 2015 John Wiley & Sons, Ltd.

Prognostic factors in multiple myeloma: selection using Cox's proportional hazard model.

PubMed

Pasqualetti, P; Collacciani, A; Maccarone, C; Casale, R

1996-01-01

The pretreatment characteristics of 210 patients with multiple myeloma, observed between 1980 and 1994, were evaluated as potential prognostic factors for survival. Multivariate analysis according to Cox's proportional hazard model identified in the 160 dead patients with myeloma, among 26 different single prognostic variables, the following factors in order of importance: beta 2-microglobulin; bone marrow plasma cell percentage, hemoglobinemia, degree of lytic bone lesions, serum creatinine, and serum albumin. By analysis of these variables a prognostic index (PI), that considers the regression coefficients derived by Cox's model of all significant factors, was obtained. Using this it was possible to separate the whole patient group into three stages: stage I (PI < 1.485, 67 patients), stage II (PI: 1.485-2.090, 76 patients), and stage III (PI > 2.090, 67 patients), with a median survivals of 68, 36 and 13 months (P < 0.0001), respectively. Also the responses to therapy (P < 0.0001) and the survival curves (P < 0.00001) presented significant differences among the three subgroups. Knowledge of these factors could be of value in predicting prognosis and in planning therapy in patients with multiple myeloma.

Distributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor tasks.

PubMed

Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Ferrigno, Giancarlo; D'Angelo, Egidio; Pedrocchi, Alessandra

2015-01-01

The cerebellum plays a crucial role in motor learning and it acts as a predictive controller. Modeling it and embedding it into sensorimotor tasks allows us to create functional links between plasticity mechanisms, neural circuits and behavioral learning. Moreover, if applied to real-time control of a neurorobot, the cerebellar model has to deal with a real noisy and changing environment, thus showing its robustness and effectiveness in learning. A biologically inspired cerebellar model with distributed plasticity, both at cortical and nuclear sites, has been used. Two cerebellum-mediated paradigms have been designed: an associative Pavlovian task and a vestibulo-ocular reflex, with multiple sessions of acquisition and extinction and with different stimuli and perturbation patterns. The cerebellar controller succeeded to generate conditioned responses and finely tuned eye movement compensation, thus reproducing human-like behaviors. Through a productive plasticity transfer from cortical to nuclear sites, the distributed cerebellar controller showed in both tasks the capability to optimize learning on multiple time-scales, to store motor memory and to effectively adapt to dynamic ranges of stimuli.

A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.

PubMed

Bersabé, Rosa; Rivas, Teresa

2010-05-01

The authors derive a general equation to compute multiple cut-offs on a total test score in order to classify individuals into more than two ordinal categories. The equation is derived from the multinomial logistic regression (MLR) model, which is an extension of the binary logistic regression (BLR) model to accommodate polytomous outcome variables. From this analytical procedure, cut-off scores are established at the test score (the predictor variable) at which an individual is as likely to be in category j as in category j+1 of an ordinal outcome variable. The application of the complete procedure is illustrated by an example with data from an actual study on eating disorders. In this example, two cut-off scores on the Eating Attitudes Test (EAT-26) scores are obtained in order to classify individuals into three ordinal categories: asymptomatic, symptomatic and eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalises DSM-IV criteria for eating disorders. Alternatives to the MLR model to set multiple cut-off scores are discussed.

Cognitive/emotional models for human behavior representation in 3D avatar simulations

NASA Astrophysics Data System (ADS)

Peterson, James K.

2004-08-01

Simplified models of human cognition and emotional response are presented which are based on models of auditory/ visual polymodal fusion. At the core of these models is a computational model of Area 37 of the temporal cortex which is based on new isocortex models presented recently by Grossberg. These models are trained using carefully chosen auditory (musical sequences), visual (paintings) and higher level abstract (meta level) data obtained from studies of how optimization strategies are chosen in response to outside managerial inputs. The software modules developed are then used as inputs to character generation codes in standard 3D virtual world simulations. The auditory and visual training data also enable the development of simple music and painting composition generators which significantly enhance one's ability to validate the cognitive model. The cognitive models are handled as interacting software agents implemented as CORBA objects to allow the use of multiple language coding choices (C++, Java, Python etc) and efficient use of legacy code.

Simulation of high-temperature superlocalization of plastic deformation in single-crystals of alloys with an L12 superstructure

NASA Astrophysics Data System (ADS)

Solov'eva, Yu. V.; Fakhrutdinova, Ya. D.; Starenchenko, V. A.

2015-01-01

The processes of the superlocalization of plastic deformation in L12 alloys have been studied numerically based on a combination of the model of the dislocation kinetics of the deformation-induced and heat-treatment-induced strengthening of an element of a deformable medium with the model of the mechanics of microplastic deformation described in terms of elastoplastic medium. It has been shown that the superlocalization of plastic deformation is determined by the presence of stress concentrators and by the nonmonotonic strengthening of the elements of the deformable medium. The multiple nonmonotonicity of the process of strengthening of the elementary volume of the medium can be responsible for the multiplicity of bands of microplastic localization of deformation.

Using Module Analysis for Multiple Choice Responses: A New Method Applied to Force Concept Inventory Data

ERIC Educational Resources Information Center

Brewe, Eric; Bruun, Jesper; Bearden, Ian G.

2016-01-01

We describe "Module Analysis for Multiple Choice Responses" (MAMCR), a new methodology for carrying out network analysis on responses to multiple choice assessments. This method is used to identify modules of non-normative responses which can then be interpreted as an alternative to factor analysis. MAMCR allows us to identify conceptual…

Integrating Remote Sensing, Field Observations, and Models to Understand Disturbance and Climate Effects on the Carbon Balance of the West Coast U.S.

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

Cohen, Warren

2014-07-03

As an element of NACP research, the proposed investigation is a two pronged approach that derives and evaluates a regional carbon (C) budget for Oregon, Washington, and California. Objectives are (1) Use multiple data sources, including AmeriFlux data, inventories, and multispectral remote sensing data to investigate trends in carbon storage and exchanges of CO2 and water with variation in climate and disturbance history; (2) Develop and apply regional modeling that relies on these multiple data sources to reduce uncertainty in spatial estimates of carbon storage and NEP, and relative contributions of terrestrial ecosystems and anthropogenic emissions to atmospheric CO2 inmore » the region; (3) Model terrestrial carbon processes across the region, using the Biome-BGC terrestrial ecosystem model, and an atmospheric inverse modeling approach to estimate variation in rate and timing of terrestrial uptake and feedbacks to the atmosphere in response to climate and disturbance.« less

Integrating Remote Sensing, Field Observations, and Models to Understand Disturbance and Climate Effects on the Carbon Balance of the West Coast U.S., Final Report

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

Beverly E. Law

2011-10-05

As an element of NACP research, the proposed investigation is a two pronged approach that derives and evaluates a regional carbon (C) budget for Oregon, Washington, and California. Objectives are (1) Use multiple data sources, including AmeriFlux data, inventories, and multispectral remote sensing data to investigate trends in carbon storage and exchanges of CO2 and water with variation in climate and disturbance history; (2) Develop and apply regional modeling that relies on these multiple data sources to reduce uncertainty in spatial estimates of carbon storage and NEP, and relative contributions of terrestrial ecosystems and anthropogenic emissions to atmospheric CO2 inmore » the region; (3) Model terrestrial carbon processes across the region, using the Biome-BGC terrestrial ecosystem model, and an atmospheric inverse modeling approach to estimate variation in rate and timing of terrestrial uptake and feedbacks to the atmosphere in response to climate and disturbance.« less

Additive-Multiplicative Approximation of Genotype-Environment Interaction

PubMed Central

Gimelfarb, A.

1994-01-01

A model of genotype-environment interaction in quantitative traits is considered. The model represents an expansion of the traditional additive (first degree polynomial) approximation of genotypic and environmental effects to a second degree polynomial incorporating a multiplicative term besides the additive terms. An experimental evaluation of the model is suggested and applied to a trait in Drosophila melanogaster. The environmental variance of a genotype in the model is shown to be a function of the genotypic value: it is a convex parabola. The broad sense heritability in a population depends not only on the genotypic and environmental variances, but also on the position of the genotypic mean in the population relative to the minimum of the parabola. It is demonstrated, using the model, that GXE interaction rectional may cause a substantial non-linearity in offspring-parent regression and a reversed response to directional selection. It is also shown that directional selection may be accompanied by an increase in the heritability. PMID:7896113

Analyzing coastal turbidity under complex terrestrial loads characterized by a 'stress connectivity matrix' with an atmosphere-watershed-coastal ocean coupled model

NASA Astrophysics Data System (ADS)

Yamamoto, Takahiro; Nadaoka, Kazuo

2018-04-01

Atmospheric, watershed and coastal ocean models were integrated to provide a holistic analysis approach for coastal ocean simulation. The coupled model was applied to coastal ocean in the Philippines where terrestrial sediment loads provided from several adjacent watersheds play a major role in influencing coastal turbidity and are partly responsible for the coastal ecosystem degradation. The coupled model was validated using weather and hydrologic measurement to examine its potential applicability. The results revealed that the coastal water quality may be governed by the loads not only from the adjacent watershed but also from the distant watershed via coastal currents. This important feature of the multiple linkages can be quantitatively characterized by a "stress connectivity matrix", which indicates the complex underlying structure of environmental stresses in coastal ocean. The multiple stress connectivity concept shows the potential advantage of the integrated modelling approach for coastal ocean assessment, which may also serve for compensating the lack of measured data especially in tropical basins.

Adaptive subdomain modeling: A multi-analysis technique for ocean circulation models

NASA Astrophysics Data System (ADS)

Altuntas, Alper; Baugh, John

2017-07-01

Many coastal and ocean processes of interest operate over large temporal and geographical scales and require a substantial amount of computational resources, particularly when engineering design and failure scenarios are also considered. This study presents an adaptive multi-analysis technique that improves the efficiency of these computations when multiple alternatives are being simulated. The technique, called adaptive subdomain modeling, concurrently analyzes any number of child domains, with each instance corresponding to a unique design or failure scenario, in addition to a full-scale parent domain providing the boundary conditions for its children. To contain the altered hydrodynamics originating from the modifications, the spatial extent of each child domain is adaptively adjusted during runtime depending on the response of the model. The technique is incorporated in ADCIRC++, a re-implementation of the popular ADCIRC ocean circulation model with an updated software architecture designed to facilitate this adaptive behavior and to utilize concurrent executions of multiple domains. The results of our case studies confirm that the method substantially reduces computational effort while maintaining accuracy.

A 1D thermomechanical network transition constitutive model coupled with multiple structural relaxation for shape memory polymers

NASA Astrophysics Data System (ADS)

Zeng, Hao; Xie, Zhimin; Gu, Jianping; Sun, Huiyu

2018-03-01

A new thermomechanical network transition constitutive model is proposed in the study to describe the viscoelastic behavior of shape memory polymers (SMPs). Based on the microstructure of semi-crystalline SMPs, a new simplified transformation equation is proposed to describe the transform of transient networks. And the generalized fractional Maxwell model is introduced in the paper to estimate the temperature-dependent storage modulus. In addition, a neo-KAHR theory with multiple discrete relaxation processes is put forward to study the structural relaxation of the nonlinear thermal strain in cooling/heating processes. The evolution equations of the time- and temperature-dependent stress and strain response are developed. In the model, the thermodynamical and mechanical characteristics of SMPs in the typical thermomechanical cycle are described clearly and the irreversible deformation is studied in detail. Finally, the typical thermomechanical cycles are simulated using the present constitutive model, and the simulation results agree well with the experimental results.

Preparation of stimulus responsive multiple emulsions by membrane emulsification using con a as biochemical sensor.

PubMed

Piacentini, Emma; Drioli, Enrico; Giorno, Lidietta

2011-04-01

In this work, a novel strategy for the controlled fabrication of biomolecular stimulus responsive water-in-oil-in-water (W/O/W) multiple emulsion using the membrane emulsification process was investigated. The emulsions interface was functionalized with a biomolecule able to function as a receptor for a target compound. The interaction between the biomolecular receptor and target stimulus activated the release of bioactive molecules contained within the structured emulsion. A glucose sensitive emulsion was investigated as a model study case. Concanavalin A (Con A) was used as the biomolecular glucose sensor. Various physicochemical strategies for stimulus responsive materials formulation are available in literature, but the preparation of biomolecule-responsive emulsions has been explored for the first time in this paper. The development of novel drug delivery systems requires advanced and highly precise techniques to obtain their particular properties and targeting requirements. The present study has proven the flexibility and suitability of membrane emulsification for the preparation of stable and functional multiple emulsions containing Con A as interfacial biomolecular receptor able to activate the release of a bioactive molecule as a consequence of interaction with the glucose target molecule. The influence of emulsion interfacial composition and membrane emulsification operating conditions on droplets stability and functional properties have been investigated. The release of the bioactive molecule as a function of glucose stimulus and its concentration has been demonstrated. Copyright © 2010 Wiley Periodicals, Inc.

Traumatogenic Processes and Pathways to Mental Health Outcomes for Sexual Minorities Exposed to Bias Crime Information.

PubMed

Lannert, Brittany K

2015-07-01

Vicarious traumatization of nonvictim members of communities targeted by bias crimes has been suggested by previous qualitative studies and often dominates public discussion following bias events, but proximal and distal responses of community members have yet to be comprehensively modeled, and quantitative research on vicarious responses is scarce. This comprehensive review integrates theoretical and empirical literatures in social, clinical, and physiological psychology in the development of a model of affective, cognitive, and physiological responses of lesbian, gay, and bisexual individuals upon exposure to information about bias crimes. Extant qualitative research in vicarious response to bias crimes is reviewed in light of theoretical implications and methodological limitations. Potential pathways to mental health outcomes are outlined, including accumulative effects of anticipatory defensive responding, multiplicative effects of minority stress, and putative traumatogenic physiological and cognitive processes of threat. Methodological considerations, future research directions, and clinical implications are also discussed. © The Author(s) 2014.

Evaluation of a Singular Value Decomposition Approach for Impact Dynamic Data Correlation

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Lyle, Karen H.; Lessard, Wendy B.

2003-01-01

Impact dynamic tests are used in the automobile and aircraft industries to assess survivability of occupants during crash, to assert adequacy of the design, and to gain federal certification. Although there is no substitute for experimental tests, analytical models are often developed and used to study alternate test conditions, to conduct trade-off studies, and to improve designs. To validate results from analytical predictions, test and analysis results must be compared to determine the model adequacy. The mathematical approach evaluated in this paper decomposes observed time responses into dominant deformation shapes and their corresponding contribution to the measured response. To correlate results, orthogonality of test and analysis shapes is used as a criterion. Data from an impact test of a composite fuselage is used and compared to finite element predictions. In this example, the impact response was decomposed into multiple shapes but only two dominant shapes explained over 85% of the measured response

Cellular Decision Making by Non-Integrative Processing of TLR Inputs.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Etzrodt, Martin; Tay, Savaş

2017-04-04

Cells receive a multitude of signals from the environment, but how they process simultaneous signaling inputs is not well understood. Response to infection, for example, involves parallel activation of multiple Toll-like receptors (TLRs) that converge on the nuclear factor κB (NF-κB) pathway. Although we increasingly understand inflammatory responses for isolated signals, it is not clear how cells process multiple signals that co-occur in physiological settings. We therefore examined a bacterial infection scenario involving co-stimulation of TLR4 and TLR2. Independent stimulation of these receptors induced distinct NF-κB dynamic profiles, although surprisingly, under co-stimulation, single cells continued to show ligand-specific dynamic responses characteristic of TLR2 or TLR4 signaling rather than a mixed response, comprising a cellular decision that we term "non-integrative" processing. Iterating modeling and microfluidic experiments revealed that non-integrative processing occurred through interaction of switch-like NF-κB activation, receptor-specific processing timescales, cell-to-cell variability, and TLR cross-tolerance mediated by multilayer negative feedback. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

The cellular response to vascular endothelial growth factors requires co-ordinated signal transduction, trafficking and proteolysis

PubMed Central

Smith, Gina A.; Fearnley, Gareth W.; Tomlinson, Darren C.; Harrison, Michael A.; Ponnambalam, Sreenivasan

2015-01-01

VEGFs (vascular endothelial growth factors) are a family of conserved disulfide-linked soluble secretory glycoproteins found in higher eukaryotes. VEGFs mediate a wide range of responses in different tissues including metabolic homoeostasis, cell proliferation, migration and tubulogenesis. Such responses are initiated by VEGF binding to soluble and membrane-bound VEGFRs (VEGF receptor tyrosine kinases) and co-receptors. VEGF and receptor splice isoform diversity further enhances complexity of membrane protein assembly and function in signal transduction pathways that control multiple cellular responses. Different signal transduction pathways are simultaneously activated by VEGFR–VEGF complexes with membrane trafficking along the endosome–lysosome network further modulating signal output from multiple enzymatic events associated with such pathways. Balancing VEGFR–VEGF signal transduction with trafficking and proteolysis is essential in controlling the intensity and duration of different intracellular signalling events. Dysfunction in VEGF-regulated signal transduction is important in chronic disease states including cancer, atherosclerosis and blindness. This family of growth factors and receptors is an important model system for understanding human disease pathology and developing new therapeutics for treating such ailments. PMID:26285805

Resonance properties of tidal channels with multiple retention basins: role of adjacent sea

NASA Astrophysics Data System (ADS)

Roos, Pieter C.; Schuttelaars, Henk M.

2015-03-01

We present an idealised model of the tidal response in a main channel with multiple secondary basins, co-oscillating with an adjacent sea. The sea is represented as a semi-infinite strip of finite width, anywhere between the limits of a channel extension (narrow) and a half-plane (wide). The sea geometry controls the extent to which radiative damping takes place and hence the type of conditions that effectively apply at the channel mouth. These conditions range between the two extremes of prescribing elevation (deep sea limit) and prescribing the incoming wave (sea as channel extension of the same depth, as done in an earlier study). The closer to this first extreme, the stronger the oscillations in the secondary basins may feed back onto the channel mouth and thus produce an amplified or weakened response in the system as a whole. The possibly resonant response is explained by analysing the additional waves that emerge on either side of the entrance of the secondary basin. Finally, we show that the simultaneous presence of two secondary basins may amplify or weaken the accumulated responses to these basins individually.

Reduced order model of a blended wing body aircraft configuration

NASA Astrophysics Data System (ADS)

Stroscher, F.; Sika, Z.; Petersson, O.

2013-12-01

This paper describes the full development process of a numerical simulation model for the ACFA2020 (Active Control for Flexible 2020 Aircraft) blended wing body (BWB) configuration. Its requirements are the prediction of aeroelastic and flight dynamic response in time domain, with relatively small model order. Further, the model had to be parameterized with regard to multiple fuel filling conditions, as well as flight conditions. High efforts have been conducted in high-order aerodynamic analysis, for subsonic and transonic regime, by several project partners. The integration of the unsteady aerodynamic databases was one of the key issues in aeroelastic modeling.

Multi-objective optimization of GENIE Earth system models.

PubMed

Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J

2009-07-13

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

Abducting Economics

PubMed Central

Singer, Burton

2018-01-01

Abduction is the process of generating and choosing models, hypotheses and data analyzed in response to surprising findings. All good empirical economists abduct. Explanations usually evolve as studies evolve. The abductive approach challenges economists to step outside the framework of received notions about the “identification problem” that rigidly separates the act of model and hypothesis creation from the act of inference from data. It asks the analyst to engage models and data in an iterative dynamic process, using multiple models and sources of data in a back and forth where both models and data are augmented as learning evolves. PMID:29430020