A voxel-based multiscale model to simulate the radiation response of hypoxic tumors.

Science.gov (United States)

Espinoza, I; Peschke, P; Karger, C P

2015-01-01

In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the model, tumor shrinkage was

A voxel-based multiscale model to simulate the radiation response of hypoxic tumors

International Nuclear Information System (INIS)

Espinoza, I.; Peschke, P.; Karger, C. P.

2015-01-01

Purpose: In radiotherapy, it is important to predict the response of tumors to irradiation prior to the treatment. This is especially important for hypoxic tumors, which are known to be highly radioresistant. Mathematical modeling based on the dose distribution, biological parameters, and medical images may help to improve this prediction and to optimize the treatment plan. Methods: A voxel-based multiscale tumor response model for simulating the radiation response of hypoxic tumors was developed. It considers viable and dead tumor cells, capillary and normal cells, as well as the most relevant biological processes such as (i) proliferation of tumor cells, (ii) hypoxia-induced angiogenesis, (iii) spatial exchange of cells leading to tumor growth, (iv) oxygen-dependent cell survival after irradiation, (v) resorption of dead cells, and (vi) spatial exchange of cells leading to tumor shrinkage. Oxygenation is described on a microscopic scale using a previously published tumor oxygenation model, which calculates the oxygen distribution for each voxel using the vascular fraction as the most important input parameter. To demonstrate the capabilities of the model, the dependence of the oxygen distribution on tumor growth and radiation-induced shrinkage is investigated. In addition, the impact of three different reoxygenation processes is compared and tumor control probability (TCP) curves for a squamous cells carcinoma of the head and neck (HNSSC) are simulated under normoxic and hypoxic conditions. Results: The model describes the spatiotemporal behavior of the tumor on three different scales: (i) on the macroscopic scale, it describes tumor growth and shrinkage during radiation treatment, (ii) on a mesoscopic scale, it provides the cell density and vascular fraction for each voxel, and (iii) on the microscopic scale, the oxygen distribution may be obtained in terms of oxygen histograms. With increasing tumor size, the simulated tumors develop a hypoxic core. Within the

Multi-gas interaction modeling on decorated semiconductor interfaces: A novel Fermi distribution-based response isotherm and the inverse hard/soft acid/base concept

Science.gov (United States)

Laminack, William; Gole, James

2015-12-01

A unique MEMS/NEMS approach is presented for the modeling of a detection platform for mixed gas interactions. Mixed gas analytes interact with nanostructured decorating metal oxide island sites supported on a microporous silicon substrate. The Inverse Hard/Soft acid/base (IHSAB) concept is used to assess a diversity of conductometric responses for mixed gas interactions as a function of these nanostructured metal oxides. The analyte conductometric responses are well represented using a combination diffusion/absorption-based model for multi-gas interactions where a newly developed response absorption isotherm, based on the Fermi distribution function is applied. A further coupling of this model with the IHSAB concept describes the considerations in modeling of multi-gas mixed analyte-interface, and analyte-analyte interactions. Taking into account the molecular electronic interaction of both the analytes with each other and an extrinsic semiconductor interface we demonstrate how the presence of one gas can enhance or diminish the reversible interaction of a second gas with the extrinsic semiconductor interface. These concepts demonstrate important considerations in the array-based formats for multi-gas sensing and its applications.

A response-modeling alternative to surrogate models for support in computational analyses

International Nuclear Information System (INIS)

Rutherford, Brian

2006-01-01

Often, the objectives in a computational analysis involve characterization of system performance based on some function of the computed response. In general, this characterization includes (at least) an estimate or prediction for some performance measure and an estimate of the associated uncertainty. Surrogate models can be used to approximate the response in regions where simulations were not performed. For most surrogate modeling approaches, however (1) estimates are based on smoothing of available data and (2) uncertainty in the response is specified in a point-wise (in the input space) fashion. These aspects of the surrogate model construction might limit their capabilities. One alternative is to construct a probability measure, G(r), for the computer response, r, based on available data. This 'response-modeling' approach will permit probability estimation for an arbitrary event, E(r), based on the computer response. In this general setting, event probabilities can be computed: prob(E)=∫ r I(E(r))dG(r) where I is the indicator function. Furthermore, one can use G(r) to calculate an induced distribution on a performance measure, pm. For prediction problems where the performance measure is a scalar, its distribution F pm is determined by: F pm (z)=∫ r I(pm(r)≤z)dG(r). We introduce response models for scalar computer output and then generalize the approach to more complicated responses that utilize multiple response models

Using risk based tools in emergency response

International Nuclear Information System (INIS)

Dixon, B.W.; Ferns, K.G.

1987-01-01

Probabilistic Risk Assessment (PRA) techniques are used by the nuclear industry to model the potential response of a reactor subjected to unusual conditions. The knowledge contained in these models can aid in emergency response decision making. This paper presents requirements for a PRA based emergency response support system to date. A brief discussion of published work provides background for a detailed description of recent developments. A rapid deep assessment capability for specific portions of full plant models is presented. The program uses a screening rule base to control search space expansion in a combinational algorithm

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

Science.gov (United States)

Made Tirta, I.; Anggraeni, Dian

2018-04-01

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

Multi-gas interaction modeling on decorated semiconductor interfaces: A novel Fermi distribution-based response isotherm and the inverse hard/soft acid/base concept

Energy Technology Data Exchange (ETDEWEB)

Laminack, William [Department of Physics, Georgia Institute of Technology, Atlanta, GA 30332 (United States); Gole, James, E-mail: James.Gole@physics.gatech.edu [Department of Physics, Georgia Institute of Technology, Atlanta, GA 30332 (United States); Department of Mechanical Engineering, Georgia Tech, Atlanta, GA 30332 (United States)

2015-12-30

Graphical abstract: Visual representation of the PS interface interacting with mixed gas configurations. The red dots correspond to nanostructured metal oxides. Each combination of distinct molecules are labeled below the pores, which are oversized in the figure. - Highlights: • First study of mixed gas analytes interacting with a micro-porous silicon substrate. • Responses are represented by a newly developed response absorption isotherm. • This isotherm is modeled on the basis of the Fermi distribution function. • The developing IHSAB concept explains multi-gas analyte–analyte interactions. - Abstract: A unique MEMS/NEMS approach is presented for the modeling of a detection platform for mixed gas interactions. Mixed gas analytes interact with nanostructured decorating metal oxide island sites supported on a microporous silicon substrate. The Inverse Hard/Soft acid/base (IHSAB) concept is used to assess a diversity of conductometric responses for mixed gas interactions as a function of these nanostructured metal oxides. The analyte conductometric responses are well represented using a combination diffusion/absorption-based model for multi-gas interactions where a newly developed response absorption isotherm, based on the Fermi distribution function is applied. A further coupling of this model with the IHSAB concept describes the considerations in modeling of multi-gas mixed analyte–interface, and analyte–analyte interactions. Taking into account the molecular electronic interaction of both the analytes with each other and an extrinsic semiconductor interface we demonstrate how the presence of one gas can enhance or diminish the reversible interaction of a second gas with the extrinsic semiconductor interface. These concepts demonstrate important considerations in the array-based formats for multi-gas sensing and its applications.

Experimental data and dose-response models

International Nuclear Information System (INIS)

Ullrich, R.L.

1985-01-01

Dose-response relationships for radiation carcinogenesis have been of interest to biologists, modelers, and statisticians for many years. Despite his interest there are few instances in which there are sufficient experimental data to allow the fitting of various dose-response models. In those experimental systems for which data are available the dose-response curves for tumor induction for the various systems cannot be described by a single model. Dose-response models which have been observed following acute exposures to gamma rays include threshold, quadratic, and linear models. Data on sex, age, and environmental influences of dose suggest a strong role of host factors on the dose response. With decreasing dose rate the effectiveness of gamma ray irradiation tends to decrease in essentially every instance. In those cases in which the high dose rate dose response could be described by a quadratic model, the effect of dose rate is consistent with predictions based on radiation effects on the induction of initial events. Whether the underlying reasons for the observed dose-rate effect is a result of effects on the induction of initial events or is due to effects on the subsequent steps in the carcinogenic process is unknown. Information on the dose response for tumor induction for high LET (linear energy transfer) radiations such as neutrons is even more limited. The observed dose and dose rate data for tumor induction following neutron exposure are complex and do not appear to be consistent with predictions based on models for the induction of initial events

Dissonance-Based Eating Disorder Prevention Program Reduces Reward Region Response to Thin Models; How Actions Shape Valuation.

Directory of Open Access Journals (Sweden)

Eric Stice

Full Text Available Research supports the effectiveness of a dissonance-based eating disorder prevention program wherein high-risk young women with body dissatisfaction critique the thin ideal, which reduces pursuit of this ideal, and the theory that dissonance induction contributes to these effects. Based on evidence that dissonance produces attitudinal change by altering neural representation of valuation, we tested whether completing the Body Project would reduce response of brain regions implicated in reward valuation to thin models. Young women with body dissatisfaction were randomized to this intervention or an educational control condition, completing assessments and fMRI scans while viewing images of thin versus average-weight female models at pre and post. Whole brain analyses indicated that, compared to controls, Body Project participants showed greater reductions in caudate response to images of thin versus average-weight models, though participants in the two conditions showed pretest differences in responsivity of other brain regions that might have contributed to this effect. Greater pre-post reductions in caudate and putamen response to thin models correlated with greater reductions in body dissatisfaction. The finding that the Body Project reduces caudate response to thin models provides novel preliminary evidence that this intervention reduces valuation of media images thought to contribute to body dissatisfaction and eating disorders, providing support for the intervention theory by documenting that this intervention alters an objective biological outcome.

Agent-based modeling of oxygen-responsive transcription factors in Escherichia coli.

Directory of Open Access Journals (Sweden)

Hao Bai

2014-04-01

Full Text Available In the presence of oxygen (O2 the model bacterium Escherichia coli is able to conserve energy by aerobic respiration. Two major terminal oxidases are involved in this process - Cyo has a relatively low affinity for O2 but is able to pump protons and hence is energetically efficient; Cyd has a high affinity for O2 but does not pump protons. When E. coli encounters environments with different O2 availabilities, the expression of the genes encoding the alternative terminal oxidases, the cydAB and cyoABCDE operons, are regulated by two O2-responsive transcription factors, ArcA (an indirect O2 sensor and FNR (a direct O2 sensor. It has been suggested that O2-consumption by the terminal oxidases located at the cytoplasmic membrane significantly affects the activities of ArcA and FNR in the bacterial nucleoid. In this study, an agent-based modeling approach has been taken to spatially simulate the uptake and consumption of O2 by E. coli and the consequent modulation of ArcA and FNR activities based on experimental data obtained from highly controlled chemostat cultures. The molecules of O2, transcription factors and terminal oxidases are treated as individual agents and their behaviors and interactions are imitated in a simulated 3-D E. coli cell. The model implies that there are two barriers that dampen the response of FNR to O2, i.e. consumption of O2 at the membrane by the terminal oxidases and reaction of O2 with cytoplasmic FNR. Analysis of FNR variants suggested that the monomer-dimer transition is the key step in FNR-mediated repression of gene expression.

Antitumour responses induced by a cell-based Reovirus vaccine in murine lung and melanoma models

International Nuclear Information System (INIS)

Campion, Ciorsdan A.; Soden, Declan; Forde, Patrick F.

2016-01-01

The ever increasing knowledge in the areas of cell biology, the immune system and the mechanisms of cancer are allowing a new phase of immunotherapy to develop. The aim of cancer vaccination is to activate the host immune system and some success has been observed particularly in the use of the BCG vaccine for bladder cancer as an immunostimulant. Reovirus, an orphan virus, has proven itself as an oncolytic virus in vitro and in vivo. Over 80 % of tumour cell lines have been found to be susceptible to Reovirus infection and it is currently in phase III clinical trials. It has been shown to induce immune responses to tumours with very low toxicities. In this study, Reovirus was examined in two main approaches in vivo, in mice, using the melanoma B16F10 and Lewis Lung Carcinoma (LLC) models. Initially, mice were treated intratumourally (IT) with Reovirus and the immune responses determined by cytokine analysis. Mice were also vaccinated using a cell-based Reovirus vaccine and subsequently exposed to a tumourigenic dose of cells (B16F10 or LLC). Using the same cell-based Reovirus vaccine, established tumours were treated and subsequent immune responses and virus retrieval investigated. Upregulation of several cytokines was observed following treatment and replication-competent virus was also retrieved from treated tumours. Varying levels of cytokine upregulation were observed and no replication-competent virus was retrieved in vaccine-treated mice. Prolongation of survival and delayed tumour growth were observed in all models and an immune response to Reovirus, either using Reovirus alone or a cell-based vaccine was also observed in all mice. This study provides evidence of immune response to tumours using a cell-based Reovirus vaccine in both tumour models investigated, B16F10 and LLC, cytokine induction was observed with prolongation of survival in almost all cases which may suggest a new method for using Reovirus in the clinic

Mechanism-Based Modeling of Gastric Emptying Rate and Gallbladder Emptying in Response to Caloric Intake

DEFF Research Database (Denmark)

Guiastrennec, B; Sonne, David Peick; Hansen, M

2016-01-01

Bile acids released postprandially modify the rate and extent of absorption of lipophilic compounds. The present study aimed to predict gastric emptying (GE) rate and gallbladder emptying (GBE) patterns in response to caloric intake. A mechanism-based model for GE, cholecystokinin plasma concentr......Bile acids released postprandially modify the rate and extent of absorption of lipophilic compounds. The present study aimed to predict gastric emptying (GE) rate and gallbladder emptying (GBE) patterns in response to caloric intake. A mechanism-based model for GE, cholecystokinin plasma...... concentrations, and GBE was developed on data from 33 patients with type 2 diabetes and 33 matched nondiabetic individuals who were administered various test drinks. A feedback action of the caloric content entering the proximal small intestine was identified for the rate of GE. The cholecystokinin...

Evaluation of iodide deficiency in the lactating rat and pup using a biologically based dose-response model

Science.gov (United States)

A biologically-based dose response (BBDR) model for the hypothalamic-pituitary thyroid (BPT) axis in the lactating rat and nursing pup was developed to describe the perturbations caused by iodide deficiency on the HPT axis. Model calibrations, carried out by adjusting key model p...

Response Styles in the Partial Credit Model

OpenAIRE

Tutz, Gerhard; Schauberger, Gunther; Berger, Moritz

2016-01-01

In the modelling of ordinal responses in psychological measurement and survey- based research, response styles that represent specific answering patterns of respondents are typically ignored. One consequence is that estimates of item parameters can be poor and considerably biased. The focus here is on the modelling of a tendency to extreme or middle categories. An extension of the Partial Credit Model is proposed that explicitly accounts for this specific response style. In contrast to exi...

Improved utilization of ADAS-cog assessment data through item response theory based pharmacometric modeling.

Science.gov (United States)

Ueckert, Sebastian; Plan, Elodie L; Ito, Kaori; Karlsson, Mats O; Corrigan, Brian; Hooker, Andrew C

2014-08-01

This work investigates improved utilization of ADAS-cog data (the primary outcome in Alzheimer's disease (AD) trials of mild and moderate AD) by combining pharmacometric modeling and item response theory (IRT). A baseline IRT model characterizing the ADAS-cog was built based on data from 2,744 individuals. Pharmacometric methods were used to extend the baseline IRT model to describe longitudinal ADAS-cog scores from an 18-month clinical study with 322 patients. Sensitivity of the ADAS-cog items in different patient populations as well as the power to detect a drug effect in relation to total score based methods were assessed with the IRT based model. IRT analysis was able to describe both total and item level baseline ADAS-cog data. Longitudinal data were also well described. Differences in the information content of the item level components could be quantitatively characterized and ranked for mild cognitively impairment and mild AD populations. Based on clinical trial simulations with a theoretical drug effect, the IRT method demonstrated a significantly higher power to detect drug effect compared to the traditional method of analysis. A combined framework of IRT and pharmacometric modeling permits a more effective and precise analysis than total score based methods and therefore increases the value of ADAS-cog data.

Developing Environmentally Responsible Behaviours Through the Implementation of Argumentation- and Problem-Based Learning Models

Science.gov (United States)

Fettahlıoğlu, Pınar; Aydoğdu, Mustafa

2018-04-01

The purpose of this research is to investigate the effect of using argumentation and problem-based learning approaches on the development of environmentally responsible behaviours among pre-service science teachers. Experimental activities were implemented for 14 weeks for 52 class hours in an environmental education class within a science teaching department. A mixed method was used as a research design; particularly, a special type of Concurrent Nested Strategy was applied. The quantitative portion was based on the one-group pre-test and post-test models, and the qualitative portion was based on the holistic multiple-case study method. The quantitative portion of the research was conducted with 34 third-year pre-service science teachers studying at a state university. The qualitative portion of the study was conducted with six pre-service science teachers selected among the 34 pre-service science teachers based on the pre-test results obtained from an environmentally responsible behaviour scale. t tests for dependent groups were used to analyse quantitative data. Both descriptive and content analyses of the qualitative data were performed. The results of the study showed that the use of the argumentation and problem-based learning approaches significantly contributed to the development of environmentally responsible behaviours among pre-service science teachers.

Model-based flaw localization from perturbations in the dynamic response of complex mechanical structures

Energy Technology Data Exchange (ETDEWEB)

Chambers, D H

2009-02-24

A new method of locating structural damage using measured differences in vibrational response and a numerical model of the undamaged structure has been presented. This method is particularly suited for complex structures with little or no symmetry. In a prior study the method successively located simulated damage from measurements of the vibrational response on two simple structures. Here we demonstrate that it can locate simulated damage in a complex structure. A numerical model of a complex structure was used to calculate the structural response before and after the introduction of a void. The method can now be considered for application to structures of programmatic interest. It could be used to monitor the structural integrity of complex mechanical structures and assemblies over their lifetimes. This would allow early detection of damage, when repair is relatively easy and inexpensive. It would also allow one to schedule maintenance based on actual damage instead of a time schedule.

Evaluation of iodide deficiency in the lactating rat and pup using a biologically based dose response (BBDR) Model***

Science.gov (United States)

A biologically-based dose response (BBDR) model for the hypothalamic-pituitary thyroid (HPT) axis in the lactating rat and nursing pup was developed to describe the perturbations caused by iodide deficiency on the 1-IPT axis. Model calibrations, carried out by adjusting key model...

Survey of Models on Demand, Customer Base-Line and Demand Response and Their Relationships in the Power Market

OpenAIRE

Heshmati, Almas

2012-01-01

The increasing use of demand-side management as a tool to reliably meet electricity demand at peak time has stimulated interest among researchers, consumers and producer organizations, managers, regulators and policymakers, This research reviews the growing literature on models used to study demand, consumer baseline (CBL) and demand response in the electricity market. After characterizing the general demand models, it reviews consumer baseline based on which further study the demand response...

Dynamical response of multi-walled carbon nanotube resonators based on continuum mechanics modeling for mass sensing applications

Energy Technology Data Exchange (ETDEWEB)

Choi, Myungseok; Olshevskiy, Alexander; Kim, Chang-Wan [Konkuk University, Seoul (Korea, Republic of); Eom, Kilho [Sungkyunkwan University, Suwon (Korea, Republic of); Gwak, Kwanwoong [Sejong University, Seoul (Korea, Republic of); Dai, Mai Duc [Ho Chi Minh City University of Technology and Education, Ho Chi Minh (Viet Nam)

2017-05-15

Carbon nanotube (CNT) has recently received much attention due to its excellent electromechanical properties, indicating that CNT can be employed for development of Nanoelectromechanical system (NEMS) such as nanomechanical resonators. For effective design of CNT-based resonators, it is required to accurately predict the vibration behavior of CNT resonators as well as their frequency response to mass adsorption. In this work, we have studied the vibrational behavior of Multi-walled CNT (MWCNT) resonators by using a continuum mechanics modeling that was implemented in Finite element method (FEM). In particular, we consider a transversely isotropic hollow cylinder solid model with Finite element (FE) implementation for modeling the vibration behavior of Multi-walled CNT (MWCNT) resonators. It is shown that our continuum mechanics model provides the resonant frequencies of various MWCNTs being comparable to those obtained from experiments. Moreover, we have investigated the frequency response of MWCNT resonators to mass adsorption by using our continuum model with FE implementation. Our study sheds light on our continuum mechanics model that is useful in predicting not only the vibration behavior of MWCNT resonators but also their sensing performance for further effective design of MWCNT- based NEMS devices.

The evaluation of distributed damage in concrete based on sinusoidal modeling of the ultrasonic response.

Science.gov (United States)

Sepehrinezhad, Alireza; Toufigh, Vahab

2018-05-25

Ultrasonic wave attenuation is an effective descriptor of distributed damage in inhomogeneous materials. Methods developed to measure wave attenuation have the potential to provide an in-site evaluation of existing concrete structures insofar as they are accurate and time-efficient. In this study, material classification and distributed damage evaluation were investigated based on the sinusoidal modeling of the response from the through-transmission ultrasonic tests on polymer concrete specimens. The response signal was modeled as single or the sum of damping sinusoids. Due to the inhomogeneous nature of concrete materials, model parameters may vary from one specimen to another. Therefore, these parameters are not known in advance and should be estimated while the response signal is being received. The modeling procedure used in this study involves a data-adaptive algorithm to estimate the parameters online. Data-adaptive algorithms are used due to a lack of knowledge of the model parameters. The damping factor was estimated as a descriptor of the distributed damage. The results were compared in two different cases as follows: (1) constant excitation frequency with varying concrete mixtures and (2) constant mixture with varying excitation frequencies. The specimens were also loaded up to their ultimate compressive strength to investigate the effect of distributed damage in the response signal. The results of the estimation indicated that the damping was highly sensitive to the change in material inhomogeneity, even in comparable mixtures. In addition to the proposed method, three methods were employed to compare the results based on their accuracy in the classification of materials and the evaluation of the distributed damage. It is shown that the estimated damping factor is not only sensitive to damage in the final stages of loading, but it is also applicable in evaluating micro damages in the earlier stages providing a reliable descriptor of damage. In addition

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

Science.gov (United States)

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

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

Radiogenomics and radiotherapy response modeling

Science.gov (United States)

El Naqa, Issam; Kerns, Sarah L.; Coates, James; Luo, Yi; Speers, Corey; West, Catharine M. L.; Rosenstein, Barry S.; Ten Haken, Randall K.

2017-08-01

Advances in patient-specific information and biotechnology have contributed to a new era of computational medicine. Radiogenomics has emerged as a new field that investigates the role of genetics in treatment response to radiation therapy. Radiation oncology is currently attempting to embrace these recent advances and add to its rich history by maintaining its prominent role as a quantitative leader in oncologic response modeling. Here, we provide an overview of radiogenomics starting with genotyping, data aggregation, and application of different modeling approaches based on modifying traditional radiobiological methods or application of advanced machine learning techniques. We highlight the current status and potential for this new field to reshape the landscape of outcome modeling in radiotherapy and drive future advances in computational oncology.

Physically-Based Modelling of the Post-Fire Runoff Response of a Forest Catchment in Central Portugal

NARCIS (Netherlands)

Eck, Van Christel M.; Nunes, Joao P.; Vieira, Diana C.S.; Keesstra, Saskia; Keizer, Jan Jacob

2016-01-01

Forest fires are a recurrent phenomenon in Mediterranean forests, with impacts for human landscapes and communities, which must be understood before they can be managed. This study used the physically based Limburg Soil Erosion Model (LISEM) to simulate rainfall–runoff response, under soil water

Cortical processing of pitch: Model-based encoding and decoding of auditory fMRI responses to real-life sounds.

Science.gov (United States)

De Angelis, Vittoria; De Martino, Federico; Moerel, Michelle; Santoro, Roberta; Hausfeld, Lars; Formisano, Elia

2017-11-13

Pitch is a perceptual attribute related to the fundamental frequency (or periodicity) of a sound. So far, the cortical processing of pitch has been investigated mostly using synthetic sounds. However, the complex harmonic structure of natural sounds may require different mechanisms for the extraction and analysis of pitch. This study investigated the neural representation of pitch in human auditory cortex using model-based encoding and decoding analyses of high field (7 T) functional magnetic resonance imaging (fMRI) data collected while participants listened to a wide range of real-life sounds. Specifically, we modeled the fMRI responses as a function of the sounds' perceived pitch height and salience (related to the fundamental frequency and the harmonic structure respectively), which we estimated with a computational algorithm of pitch extraction (de Cheveigné and Kawahara, 2002). First, using single-voxel fMRI encoding, we identified a pitch-coding region in the antero-lateral Heschl's gyrus (HG) and adjacent superior temporal gyrus (STG). In these regions, the pitch representation model combining height and salience predicted the fMRI responses comparatively better than other models of acoustic processing and, in the right hemisphere, better than pitch representations based on height/salience alone. Second, we assessed with model-based decoding that multi-voxel response patterns of the identified regions are more informative of perceived pitch than the remainder of the auditory cortex. Further multivariate analyses showed that complementing a multi-resolution spectro-temporal sound representation with pitch produces a small but significant improvement to the decoding of complex sounds from fMRI response patterns. In sum, this work extends model-based fMRI encoding and decoding methods - previously employed to examine the representation and processing of acoustic sound features in the human auditory system - to the representation and processing of a relevant

A model of roles and responsibilities in oral health promotion based on perspectives of a community-based initiative for pre-school children in the U.K.

Science.gov (United States)

Henderson, E; Rubin, G

2014-03-01

(i) To explore dental, school and family perspectives of an oral health promotion (OHP) initiative to improve access for pre-school children in deprived communities; (ii) to develop a model of roles and responsibilities for OHP in community settings. Semi-structured focus groups (n = 6) with dental practice staff (n = 24), and semi-structured interviews with school staff (n = 9) and parents and children (n = 4) who were involved in an OHP initiative for pre-school children. Framework analysis was applied to identify themes. Themes were used to develop a model of roles and responsibilities for OHP, based on the WHO Planning and evaluating health promotion model. Respondents subscribed to a community-based approach to improving access to dental services for pre-school children in deprived areas, with an emphasis on shared responsibility and communication. In addition to macro-level actions in directing health policy and services, commissioners were held responsible for investing in micro-level actions, such as funding OHP training and involving parents, and meso-level actions such as reducing barriers to access. The model we have developed builds on WHO recommendations on health promotion to identify the key roles and responsibilities that should be incorporated into further initiatives in OHP.

Comparative investigation of ELM control based on toroidal modelling of plasma response to RMP fields

Science.gov (United States)

Liu, Yueqiang

2016-10-01

The type-I edge localized mode (ELM), bursting at low frequency and with large amplitude, can channel a substantial amount of the plasma thermal energy into the surrounding plasma-facing components in tokamak devices operating at the high-confinement mode, potentially causing severe material damages. Learning effective ways of controlling this instability is thus an urgent issue in fusion research, in particular in view of the next generation large devices such as ITER and DEMO. Among other means, externally applied, three-dimensional resonant magnetic perturbation (RMP) fields have been experimentally demonstrated to be successful in mitigating or suppressing the type-I ELM, in multiple existing devices. In this work, we shall report results of a comparative study of ELM control using RMPs. Comparison is made between the modelled plasma response to the 3D external fields and the observed change of the ELM behaviour on multiple devices, including MAST, ASDEX Upgrade, EAST, DIII-D, JET, and KSTAR. We show that toroidal modelling of the plasma response, based on linear and quasi-linear magnetohydrodynamic (MHD) models, provides essential insights that are useful in interpreting and guiding the ELM control experiments. In particular, linear toroidal modelling results, using the MARS-F code, reveal the crucial role of the edge localized peeling-tearing mode response during ELM mitigation/suppression on all these devices. Such response often leads to strong peaking of the plasma surface displacement near the region of weak equilibrium poloidal field (e.g. the X-point), and this provides an alternative practical criterion for ELM control, as opposed to the vacuum field based Chirikov criteria. Quasi-linear modelling using MARS-Q provides quantitative interpretation of the side effects due to the ELM control coils, on the plasma toroidal momentum and particle confinements. The particular role of the momentum and particle fluxes, associated with the neoclassical toroidal

Multiscale modeling of mucosal immune responses

Science.gov (United States)

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

Multiscale modeling of mucosal immune responses.

Science.gov (United States)

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

Fitting Diffusion Item Response Theory Models for Responses and Response Times Using the R Package diffIRT

Directory of Open Access Journals (Sweden)

Dylan Molenaar

2015-08-01

Full Text Available In the psychometric literature, item response theory models have been proposed that explicitly take the decision process underlying the responses of subjects to psychometric test items into account. Application of these models is however hampered by the absence of general and flexible software to fit these models. In this paper, we present diffIRT, an R package that can be used to fit item response theory models that are based on a diffusion process. We discuss parameter estimation and model fit assessment, show the viability of the package in a simulation study, and illustrate the use of the package with two datasets pertaining to extraversion and mental rotation. In addition, we illustrate how the package can be used to fit the traditional diffusion model (as it has been originally developed in experimental psychology to data.

History-Based Response Threshold Model for Division of Labor in Multi-Agent Systems

Science.gov (United States)

Lee, Wonki; Kim, DaeEun

2017-01-01

Dynamic task allocation is a necessity in a group of robots. Each member should decide its own task such that it is most commensurate with its current state in the overall system. In this work, the response threshold model is applied to a dynamic foraging task. Each robot employs a task switching function based on the local task demand obtained from the surrounding environment, and no communication occurs between the robots. Each individual member has a constant-sized task demand history that reflects the global demand. In addition, it has response threshold values for all of the tasks and manages the task switching process depending on the stimuli of the task demands. The robot then determines the task to be executed to regulate the overall division of labor. This task selection induces a specialized tendency for performing a specific task and regulates the division of labor. In particular, maintaining a history of the task demands is very effective for the dynamic foraging task. Various experiments are performed using a simulation with multiple robots, and the results show that the proposed algorithm is more effective as compared to the conventional model. PMID:28555031

Nonrigid, Linear Plasma Response Model Based on Perturbed Equilibria for Axisymmetric Tokamak Control Design

International Nuclear Information System (INIS)

Welander, A.S.; Deranian, R.D.; Humphreys, D.A.; Leuer, J.A.; Walker, M.L.

2005-01-01

Tokamak control design relies on an accurate linear model of the plasma response, which can often dominate the local field variations in regions under active feedback control. For example, when fluxes at selected points on the plasma boundary are regulated in DIII-D, the plasma response to a change in a coil current gives rise to a flux change which can be larger than and opposite to the flux change caused by the coil alone.In the past, rigid plasma models have been used for linear stability and shape control design. In a rigid model, the plasma current profile is considered fixed and moves rigidly in response to control coils to maintain radial and vertical force balance. In a nonrigid model, however, changes in the plasma shape and current profile are taken into account. Such models are expected to be important for future advanced tokamak control design. The present work describes development of a nonrigid plasma response model for high-accuracy multivariable control design and provides comparisons of model predictions against DIII-D experimental data. The linear perturbed plasma response model is calculated rapidly from an existing equilibrium solution

Mechanism-based population modelling for assessment of L-cell function based on total GLP-1 response following an oral glucose tolerance test

DEFF Research Database (Denmark)

Møller, Jonas B.; Jusko, William J.; Gao, Wei

2011-01-01

was to build a mechanism-based population model that describes the time course of total GLP-1 and provides indices for capability of secretion in each subject. The goal was thus to model the secretion of GLP-1, and not its effect on insulin production. Single 75 g doses of glucose were administered orally......GLP-1 is an insulinotropic hormone that synergistically with glucose gives rise to an increased insulin response. Its secretion is increased following a meal and it is thus of interest to describe the secretion of this hormone following an oral glucose tolerance test (OGTT). The aim of this study....... The individual estimates of absorption rate constants were used in the model for GLP-1 secretion. Estimation of parameters was performed using the FOCE method with interaction implemented in NONMEM VI. The final transit/indirect-response model obtained for GLP-1 production following an OGTT included two...

A demand response modeling for residential consumers in smart grid environment using game theory based energy scheduling algorithm

Directory of Open Access Journals (Sweden)

S. Sofana Reka

2016-06-01

Full Text Available In this paper, demand response modeling scheme is proposed for residential consumers using game theory algorithm as Generalized Tit for Tat (GTFT Dominant Game based Energy Scheduler. The methodology is established as a work flow domain model between the utility and the user considering the smart grid framework. It exhibits an algorithm which schedules load usage by creating several possible tariffs for consumers such that demand is never raised. This can be done both individually and among multiple users of a community. The uniqueness behind the demand response proposed is that, the tariff is calculated for all hours and the load during the peak hours which can be rescheduled is shifted based on the Peak Average Ratio. To enable the vitality of the work simulation results of a general case of three domestic consumers are modeled extended to a comparative performance and evaluation with other algorithms and inference is analyzed.

In situ measurement and modeling of biomechanical response of human cadaveric soft tissues for physics-based surgical simulation.

Science.gov (United States)

Lim, Yi-Je; Deo, Dhanannjay; Singh, Tejinder P; Jones, Daniel B; De, Suvranu

2009-06-01

Development of a laparoscopic surgery simulator that delivers high-fidelity visual and haptic (force) feedback, based on the physical models of soft tissues, requires the use of empirical data on the mechanical behavior of intra-abdominal organs under the action of external forces. As experiments on live human patients present significant risks, the use of cadavers presents an alternative. We present techniques of measuring and modeling the mechanical response of human cadaveric tissue for the purpose of developing a realistic model. The major contribution of this paper is the development of physics-based models of soft tissues that range from linear elastic models to nonlinear viscoelastic models which are efficient for application within the framework of a real-time surgery simulator. To investigate the in situ mechanical, static, and dynamic properties of intra-abdominal organs, we have developed a high-precision instrument by retrofitting a robotic device from Sensable Technologies (position resolution of 0.03 mm) with a six-axis Nano 17 force-torque sensor from ATI Industrial Automation (force resolution of 1/1,280 N along each axis), and used it to apply precise displacement stimuli and record the force response of liver and stomach of ten fresh human cadavers. The mean elastic modulus of liver and stomach is estimated as 5.9359 kPa and 1.9119 kPa, respectively over the range of indentation depths tested. We have also obtained the parameters of a quasilinear viscoelastic (QLV) model to represent the nonlinear viscoelastic behavior of the cadaver stomach and liver over a range of indentation depths and speeds. The models are found to have an excellent goodness of fit (with R (2) > 0.99). The data and models presented in this paper together with additional ones based on the principles presented in this paper would result in realistic physics-based surgical simulators.

Characterization and Modeling of Electrical Response of Electrode Catalyzed Reactions in AIGaN/GaN-Based Gas Sensors

Science.gov (United States)

Melby, Jacob H.

AlGaN/GaN high electron mobility transistors (HEMT) and AlGaN/GaN diodes have promise for use as hydrogen and hydrocarbon sensors for a variety of industrial, military, and commercial applications. These semiconductor-based sensors have a number of advantages over other sensor technologies, such as the ability to operate at high temperatures, in corrosive environments, or under ionizing radiation. The high sensitivity of these devices to hydrogen-containing gases is associated with polarization differences within the AlGaN/GaN heterostructure that give rise to the formation of a two-dimensional electron gas (2DEG); exposure of the device to hydrogen changes the density of the 2DEG, which can be detected in a HEMT or diode structure. Although sensitivity to a range of gases has been reported, the factors that influence the behavior of the sensors are not well studied. The overarching goals of the research that follows were to determine how gas exposure conditions affect sensor behavior, to characterize and model the relationship between the electrical response of the sensors and the external gaseous environment, and to investigate the effects of using different metal catalysts on sensor behavior. The heterostructures used in this work were grown via metalorganic vapor phase epitaxy (MOVPE). Schottky diode and transistor devices employing platinum-group (Pd, Pt, Rh, Ir, Ru, and Os) catalysts were fabricated to allow electrical sensitivity in the presence of hydrogen and hydrogen containing gases. The generation of atomic hydrogen on the catalyst surface results in the rapid formation of hydrogen dipoles at the metal-semiconductor interface, which produces a measurable electronic response. The electrical response of Pt-gated HEMT-based sensors were measured in a flowing gaseous stream consisting of hydrogen in a pure nitrogen diluent at ambient and elevated temperatures. The transistors exhibited excellent transfer characteristics for temperatures ranging from 25�

3-D seismic response of a base-isolated fast reactor

International Nuclear Information System (INIS)

Kitamura, S.; Morishita, M.; Iwata, K.

1992-01-01

This paper describes a 3-D response analysis methodology development and its application to a base-isolated fast breeder reactor (FBR) plant. At first, studies on application of a base-isolation system to an FBR plant were performed to identify a range of appropriate characteristics of the system. A response analysis method was developed based on mathematical models for the restoring force characteristics of several types of the systems. A series of shaking table tests using a small scale model was carried out to verify the analysis method. A good agreement was seen between the test and analysis results in terms of the horizontal and vertical responses. Parametric studies were then made to assess the effects of various factors which might be influential to the seismic response of the system. Moreover, the method was applied to evaluate three-dimensional response of the base-isolated FBR. (author)

Use of a viscoelastic model for the seismic response of base-isolated buildings

International Nuclear Information System (INIS)

Uras, R.A.

1994-01-01

Due to recent developments in elastomer technology, seismic isolation using elastomer bearings is rapidly becoming an acceptable design tool to enhance structural seismic margins and to protect people and equipment from earthquake damage. With proper design of isolators, high-energy seismic input motions are transformed into low-frequency, low energy harmonic motions and the accelerations acting on the isolated building are significantly reduced. Several alternatives exist for the modeling of the isolators. This study is concerned with the use of a viscoelastic model to predict the seismic response of base-isolated buildings. The in-house finite element computer code has been modified to incorporate a viscoelastic spring element, and several simulations are performed. Then, the computed results have been compared with the corresponding observed data recorded at the test facility

Modeling the frequency response of photovoltaic inverters

NARCIS (Netherlands)

Ernauli Christine Aprilia, A.; Cuk, V.; Cobben, J.F.G.; Ribeiro, P.F.; Kling, W.L.

2012-01-01

The increased presence of photovoltaic (PV) systems inevitably affects the power quality in the grid. This new reality demands grid power quality studies involving PV inverters. This paper proposes several frequency response models in the form of equivalent circuits. Models are based on laboratory

Response of base-isolated nuclear structures to extreme earthquake shaking

Energy Technology Data Exchange (ETDEWEB)

Kumar, Manish, E-mail: mkumar2@buffalo.edu; Whittaker, Andrew S.; Constantinou, Michael C.

2015-12-15

Highlights: • Response-history analysis of nuclear structures base-isolated using lead–rubber bearings is performed. • Advanced numerical model of lead–rubber bearing is used to capture behavior under extreme earthquake shaking. • Results of response-history analysis obtained using simplified and advanced model of lead–rubber bearings are compared. • Heating of the lead core and variation in buckling load and axial stiffness affect the response. - Abstract: Seismic isolation using low damping rubber and lead–rubber bearings is a viable strategy for mitigating the effects of extreme earthquake shaking on safety-related nuclear structures. The mechanical properties of these bearings are not expected to change substantially in design basis shaking. However, under shaking more intense than design basis, the properties of the lead cores in lead–rubber bearings may degrade due to heating associated with energy dissipation, some bearings in an isolation system may experience net tension, and the compression and tension stiffness may be affected by the lateral displacement of the isolation system. The effects of intra-earthquake changes in mechanical properties on the response of base-isolated nuclear power plants (NPPs) are investigated using an advanced numerical model of a lead–rubber bearing that has been verified and validated, and implemented in OpenSees. A macro-model is used for response-history analysis of base-isolated NPPs. Ground motions are selected and scaled to be consistent with response spectra for design basis and beyond design basis earthquake shaking at the site of the Diablo Canyon Nuclear Generating Station. Ten isolation systems of two periods and five characteristic strengths are analyzed. The responses obtained using simplified and advanced isolator models are compared. Strength degradation due to heating of lead cores and changes in buckling load most significantly affect the response of the base-isolated NPP.

Response of base-isolated nuclear structures to extreme earthquake shaking

International Nuclear Information System (INIS)

Kumar, Manish; Whittaker, Andrew S.; Constantinou, Michael C.

2015-01-01

Highlights: • Response-history analysis of nuclear structures base-isolated using lead–rubber bearings is performed. • Advanced numerical model of lead–rubber bearing is used to capture behavior under extreme earthquake shaking. • Results of response-history analysis obtained using simplified and advanced model of lead–rubber bearings are compared. • Heating of the lead core and variation in buckling load and axial stiffness affect the response. - Abstract: Seismic isolation using low damping rubber and lead–rubber bearings is a viable strategy for mitigating the effects of extreme earthquake shaking on safety-related nuclear structures. The mechanical properties of these bearings are not expected to change substantially in design basis shaking. However, under shaking more intense than design basis, the properties of the lead cores in lead–rubber bearings may degrade due to heating associated with energy dissipation, some bearings in an isolation system may experience net tension, and the compression and tension stiffness may be affected by the lateral displacement of the isolation system. The effects of intra-earthquake changes in mechanical properties on the response of base-isolated nuclear power plants (NPPs) are investigated using an advanced numerical model of a lead–rubber bearing that has been verified and validated, and implemented in OpenSees. A macro-model is used for response-history analysis of base-isolated NPPs. Ground motions are selected and scaled to be consistent with response spectra for design basis and beyond design basis earthquake shaking at the site of the Diablo Canyon Nuclear Generating Station. Ten isolation systems of two periods and five characteristic strengths are analyzed. The responses obtained using simplified and advanced isolator models are compared. Strength degradation due to heating of lead cores and changes in buckling load most significantly affect the response of the base-isolated NPP.

The conceptual model of organization social responsibility

OpenAIRE

LUO, Lan; WEI, Jingfu

2014-01-01

With the developing of the research of CSR, people more and more deeply noticethat the corporate should take responsibility. Whether other organizations besides corporatesshould not take responsibilities beyond their field? This paper puts forward theconcept of organization social responsibility on the basis of the concept of corporate socialresponsibility and other theories. And the conceptual models are built based on theconception, introducing the OSR from three angles: the types of organi...

ENVIRONMENTAL RESPONSIBILITY MODEL BASED ON ISO 14000 MANAGEMENT SYSTEMS

Directory of Open Access Journals (Sweden)

Catalina SITNIKOV

2012-01-01

Full Text Available Worldwide corporations, as well as their stakeholders, are more conscious of the need for environmental management, SR behaviour, and sustainable growth and development. International Standards are becoming more significant for corporations to work towards common environmental management practices. ISO 14001 is the first and the broadest standard intended at a more responsible approach of corporations and the world’s most acknowledged framework for environmental management systems that assists corporations to better manage the effect of their activities on the environment. This article aims to study ISO 14001 implementation and its effects on the environmental responsibility. A model will be built, which covers the environmental management system, the components of organizational culture, being able to influence environmental standards implementation.

Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system.

Science.gov (United States)

Lumen, Annie; McNally, Kevin; George, Nysia; Fisher, Jeffrey W; Loizou, George D

2015-01-01

A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local sensitivity analysis.

Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system

Directory of Open Access Journals (Sweden)

Annie eLumen

2015-05-01

Full Text Available A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local

Quantal Response: Nonparametric Modeling

Science.gov (United States)

2017-01-01

capture the behavior of observed phenomena. Higher-order polynomial and finite-dimensional spline basis models allow for more complicated responses as the...flexibility as these are nonparametric (not constrained to any particular functional form). These should be useful in identifying nonstandard behavior via... deviance ∆ = −2 log(Lreduced/Lfull) is defined in terms of the likelihood function L. For normal error, Lfull = 1, and based on Eq. A-2, we have log

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

Science.gov (United States)

Bolsinova, Maria; Tijmstra, Jesper; Molenaar, Dylan

2017-05-01

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

Sharing experiences: towards an evidence based model of dengue surveillance and outbreak response in Latin America and Asia.

OpenAIRE

Badurdeen, Shiraz; Valladares, David; Farrar, Jeremy; Gozzer, Ernesto; Kroeger, Axel; Kuswara, Novia; Ranzinger, Silvia; Tinh, Hien; Leite, Priscila; Mahendradhata, Yodi; Skewes, Ronald; Verrall, Ayesha

2013-01-01

BACKGROUND\\ud The increasing frequency and intensity of dengue outbreaks in endemic and non-endemic countries requires a rational, evidence based response. To this end, we aimed to collate the experiences of a number of affected countries, identify strengths and limitations in dengue surveillance, outbreak preparedness, detection and response and contribute towards the development of a model contingency plan adaptable to country needs.\\ud \\ud METHODS\\ud The study was undertaken in five Latin ...

Amazon rainforest responses to elevated CO2: Deriving model-based hypotheses for the AmazonFACE experiment

Science.gov (United States)

Rammig, A.; Fleischer, K.; Lapola, D.; Holm, J.; Hoosbeek, M.

2017-12-01

Increasing atmospheric CO2 concentration is assumed to have a stimulating effect ("CO2 fertilization effect") on forest growth and resilience. Empirical evidence, however, for the existence and strength of such a tropical CO2 fertilization effect is scarce and thus a major impediment for constraining the uncertainties in Earth System Model projections. The implications of the tropical CO2 effect are far-reaching, as it strongly influences the global carbon and water cycle, and hence future global climate. In the scope of the Amazon Free Air CO2 Enrichment (FACE) experiment, we addressed these uncertainties by assessing the CO2 fertilization effect at ecosystem scale. AmazonFACE is the first FACE experiment in an old-growth, highly diverse tropical rainforest. Here, we present a priori model-based hypotheses for the experiment derived from a set of 12 ecosystem models. Model simulations identified key uncertainties in our understanding of limiting processes and derived model-based hypotheses of expected ecosystem responses to elevated CO2 that can directly be tested during the experiment. Ambient model simulations compared satisfactorily with in-situ measurements of ecosystem carbon fluxes, as well as carbon, nitrogen, and phosphorus stocks. Models consistently predicted an increase in photosynthesis with elevated CO2, which declined over time due to developing limitations. The conversion of enhanced photosynthesis into biomass, and hence ecosystem carbon sequestration, varied strongly among the models due to different assumptions on nutrient limitation. Models with flexible allocation schemes consistently predicted an increased investment in belowground structures to alleviate nutrient limitation, in turn accelerating turnover rates of soil organic matter. The models diverged on the prediction for carbon accumulation after 10 years of elevated CO2, mainly due to contrasting assumptions in their phosphorus cycle representation. These differences define the expected

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

Science.gov (United States)

Palsson, Sirus; Hickling, Timothy P; Bradshaw-Pierce, Erica L; Zager, Michael; Jooss, Karin; O'Brien, Peter J; Spilker, Mary E; Palsson, Bernhard O; Vicini, Paolo

2013-09-28

The complexity and multiscale nature of the mammalian immune response provides an excellent test bed for the potential of mathematical modeling and simulation to facilitate mechanistic understanding. Historically, mathematical models of the immune response focused on subsets of the immune system and/or specific aspects of the response. Mathematical models have been developed for the humoral side of the immune response, or for the cellular side, or for cytokine kinetics, but rarely have they been proposed to encompass the overall system complexity. We propose here a framework for integration of subset models, based on a system biology approach. A dynamic simulator, the Fully-integrated Immune Response Model (FIRM), was built in a stepwise fashion by integrating published subset models and adding novel features. The approach used to build the model includes the formulation of the network of interacting species and the subsequent introduction of rate laws to describe each biological process. The resulting model represents a multi-organ structure, comprised of the target organ where the immune response takes place, circulating blood, lymphoid T, and lymphoid B tissue. The cell types accounted for include macrophages, a few T-cell lineages (cytotoxic, regulatory, helper 1, and helper 2), and B-cell activation to plasma cells. Four different cytokines were accounted for: IFN-γ, IL-4, IL-10 and IL-12. In addition, generic inflammatory signals are used to represent the kinetics of IL-1, IL-2, and TGF-β. Cell recruitment, differentiation, replication, apoptosis and migration are described as appropriate for the different cell types. The model is a hybrid structure containing information from several mammalian species. The structure of the network was built to be physiologically and biochemically consistent. Rate laws for all the cellular fate processes, growth factor production rates and half-lives, together with antibody production rates and half-lives, are provided. The

Population-expression models of immune response

International Nuclear Information System (INIS)

Stromberg, Sean P; Antia, Rustom; Nemenman, Ilya

2013-01-01

The immune response to a pathogen has two basic features. The first is the expansion of a few pathogen-specific cells to form a population large enough to control the pathogen. The second is the process of differentiation of cells from an initial naive phenotype to an effector phenotype which controls the pathogen, and subsequently to a memory phenotype that is maintained and responsible for long-term protection. The expansion and the differentiation have been considered largely independently. Changes in cell populations are typically described using ecologically based ordinary differential equation models. In contrast, differentiation of single cells is studied within systems biology and is frequently modeled by considering changes in gene and protein expression in individual cells. Recent advances in experimental systems biology make available for the first time data to allow the coupling of population and high dimensional expression data of immune cells during infections. Here we describe and develop population-expression models which integrate these two processes into systems biology on the multicellular level. When translated into mathematical equations, these models result in non-conservative, non-local advection-diffusion equations. We describe situations where the population-expression approach can make correct inference from data while previous modeling approaches based on common simplifying assumptions would fail. We also explore how model reduction techniques can be used to build population-expression models, minimizing the complexity of the model while keeping the essential features of the system. While we consider problems in immunology in this paper, we expect population-expression models to be more broadly applicable. (paper)

Benchmarking nuclear models for Gamow–Teller response

International Nuclear Information System (INIS)

Litvinova, E.; Brown, B.A.; Fang, D.-L.; Marketin, T.; Zegers, R.G.T.

2014-01-01

A comparative study of the nuclear Gamow–Teller response (GTR) within conceptually different state-of-the-art approaches is presented. Three nuclear microscopic models are considered: (i) the recently developed charge-exchange relativistic time blocking approximation (RTBA) based on the covariant density functional theory, (ii) the shell model (SM) with an extended “jj77” model space and (iii) the non-relativistic quasiparticle random-phase approximation (QRPA) with a Brueckner G-matrix effective interaction. We study the physics cases where two or all three of these models can be applied. The Gamow–Teller response functions are calculated for 208 Pb, 132 Sn and 78 Ni within both RTBA and QRPA. The strengths obtained for 208 Pb are compared to data that enable a firm model benchmarking. For the nucleus 132 Sn, also SM calculations are performed within the model space truncated at the level of a particle–hole (ph) coupled to vibration configurations. This allows a consistent comparison to the RTBA where ph⊗phonon coupling is responsible for the spreading width and considerable quenching of the GTR. Differences between the models and perspectives of their future developments are discussed.

Benchmarking nuclear models for Gamow–Teller response

Energy Technology Data Exchange (ETDEWEB)

Litvinova, E., E-mail: elena.litvinova@wmich.edu [Department of Physics, Western Michigan University, Kalamazoo, MI 49008-5252 (United States); National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824-1321 (United States); Brown, B.A. [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824-1321 (United States); National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824-1321 (United States); Fang, D.-L. [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824-1321 (United States); Joint Institute for Nuclear Astrophysics, Michigan State University, East Lansing, MI 48824-1321 (United States); Marketin, T. [Physics Department, Faculty of Science, University of Zagreb (Croatia); Zegers, R.G.T. [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824-1321 (United States); National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824-1321 (United States); Joint Institute for Nuclear Astrophysics, Michigan State University, East Lansing, MI 48824-1321 (United States)

2014-03-07

A comparative study of the nuclear Gamow–Teller response (GTR) within conceptually different state-of-the-art approaches is presented. Three nuclear microscopic models are considered: (i) the recently developed charge-exchange relativistic time blocking approximation (RTBA) based on the covariant density functional theory, (ii) the shell model (SM) with an extended “jj77” model space and (iii) the non-relativistic quasiparticle random-phase approximation (QRPA) with a Brueckner G-matrix effective interaction. We study the physics cases where two or all three of these models can be applied. The Gamow–Teller response functions are calculated for {sup 208}Pb, {sup 132}Sn and {sup 78}Ni within both RTBA and QRPA. The strengths obtained for {sup 208}Pb are compared to data that enable a firm model benchmarking. For the nucleus {sup 132}Sn, also SM calculations are performed within the model space truncated at the level of a particle–hole (ph) coupled to vibration configurations. This allows a consistent comparison to the RTBA where ph⊗phonon coupling is responsible for the spreading width and considerable quenching of the GTR. Differences between the models and perspectives of their future developments are discussed.

PID controller auto-tuning based on process step response and damping optimum criterion.

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Pavković, Danijel; Polak, Siniša; Zorc, Davor

2014-01-01

This paper presents a novel method of PID controller tuning suitable for higher-order aperiodic processes and aimed at step response-based auto-tuning applications. The PID controller tuning is based on the identification of so-called n-th order lag (PTn) process model and application of damping optimum criterion, thus facilitating straightforward algebraic rules for the adjustment of both the closed-loop response speed and damping. The PTn model identification is based on the process step response, wherein the PTn model parameters are evaluated in a novel manner from the process step response equivalent dead-time and lag time constant. The effectiveness of the proposed PTn model parameter estimation procedure and the related damping optimum-based PID controller auto-tuning have been verified by means of extensive computer simulations. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Study of cumulative fatigue damage detection for used parts with nonlinear output frequency response functions based on NARMAX modelling

Science.gov (United States)

Huang, Honglan; Mao, Hanying; Mao, Hanling; Zheng, Weixue; Huang, Zhenfeng; Li, Xinxin; Wang, Xianghong

2017-12-01

Cumulative fatigue damage detection for used parts plays a key role in the process of remanufacturing engineering and is related to the service safety of the remanufactured parts. In light of the nonlinear properties of used parts caused by cumulative fatigue damage, the based nonlinear output frequency response functions detection approach offers a breakthrough to solve this key problem. First, a modified PSO-adaptive lasso algorithm is introduced to improve the accuracy of the NARMAX model under impulse hammer excitation, and then, an effective new algorithm is derived to estimate the nonlinear output frequency response functions under rectangular pulse excitation, and a based nonlinear output frequency response functions index is introduced to detect the cumulative fatigue damage in used parts. Then, a novel damage detection approach that integrates the NARMAX model and the rectangular pulse is proposed for nonlinear output frequency response functions identification and cumulative fatigue damage detection of used parts. Finally, experimental studies of fatigued plate specimens and used connecting rod parts are conducted to verify the validity of the novel approach. The obtained results reveal that the new approach can detect cumulative fatigue damages of used parts effectively and efficiently and that the various values of the based nonlinear output frequency response functions index can be used to detect the different fatigue damages or working time. Since the proposed new approach can extract nonlinear properties of systems by only a single excitation of the inspected system, it shows great promise for use in remanufacturing engineering applications.

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

Energy Technology Data Exchange (ETDEWEB)

Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias; Zhang, Jianhua; Li, Zhigang; Shafie-Khah, Miadreza; Catalao, Joao P. S.

2017-11-01

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

Seismic response of base-isolated buildings using a viscoelastic model

International Nuclear Information System (INIS)

Uras, R.A.

1993-01-01

Due to recent developments in elastomer technology,seismic isolation using elastomer bearings is rapidly gaining acceptance as a design tool to enhance structural seismic margins and to protect people and equipment from earthquake damage. With proper design of isolators, the fundamental frequency of the structure can be reduced to a value that is lower than the dominant frequencies of earthquake ground motions. The other feature of an isolation system is that it can provide a mechanism for energy dissipation. In the USA, the use of seismic base-isolation has become an alternate strategy for advanced Liquid Metal-cooled Reactors (LMRs). ANL has been deeply involved in the development and implementation of seismic isolation for use in both nuclear facilities and civil structures for the past decade. Shimizu Corporation of Japan has a test facility at Tohoku University in Sendai, Japan. The test facility has two buildings: one is base isolated and the other is conventionally founded. The buildings are full-size, three-story reinforced concrete structures. The dimensions and construction of the superstructures are identical. They were built side by side in a seismically active area. In 1988, the ANL/Shimizu Joint Program was established to study the differences in behavior of base-isolated and ordinarily founded structures when subjected to earthquake loading. A more comprehensive description of this joint program is presented in a companion paper (Wang et al. 1993). With the increased use of elastomeric polymers in industrial applications such as isolation bearings, the importance of constitutive modeling of viscoelastic materials is more and more pronounced. A realistic representation of material behavior is essential for computer simulations to replicate the response observed in experiments

A model for predicting lung cancer response to therapy

International Nuclear Information System (INIS)

Seibert, Rebecca M.; Ramsey, Chester R.; Hines, J. Wesley; Kupelian, Patrick A.; Langen, Katja M.; Meeks, Sanford L.; Scaperoth, Daniel D.

2007-01-01

Purpose: Volumetric computed tomography (CT) images acquired by image-guided radiation therapy (IGRT) systems can be used to measure tumor response over the course of treatment. Predictive adaptive therapy is a novel treatment technique that uses volumetric IGRT data to actively predict the future tumor response to therapy during the first few weeks of IGRT treatment. The goal of this study was to develop and test a model for predicting lung tumor response during IGRT treatment using serial megavoltage CT (MVCT). Methods and Materials: Tumor responses were measured for 20 lung cancer lesions in 17 patients that were imaged and treated with helical tomotherapy with doses ranging from 2.0 to 2.5 Gy per fraction. Five patients were treated with concurrent chemotherapy, and 1 patient was treated with neoadjuvant chemotherapy. Tumor response to treatment was retrospectively measured by contouring 480 serial MVCT images acquired before treatment. A nonparametric, memory-based locally weight regression (LWR) model was developed for predicting tumor response using the retrospective tumor response data. This model predicts future tumor volumes and the associated confidence intervals based on limited observations during the first 2 weeks of treatment. The predictive accuracy of the model was tested using a leave-one-out cross-validation technique with the measured tumor responses. Results: The predictive algorithm was used to compare predicted verse-measured tumor volume response for all 20 lesions. The average error for the predictions of the final tumor volume was 12%, with the true volumes always bounded by the 95% confidence interval. The greatest model uncertainty occurred near the middle of the course of treatment, in which the tumor response relationships were more complex, the model has less information, and the predictors were more varied. The optimal days for measuring the tumor response on the MVCT images were on elapsed Days 1, 2, 5, 9, 11, 12, 17, and 18 during

Reliability evaluation of microgrid considering incentive-based demand response

Science.gov (United States)

Huang, Ting-Cheng; Zhang, Yong-Jun

2017-07-01

Incentive-based demand response (IBDR) can guide customers to adjust their behaviour of electricity and curtail load actively. Meanwhile, distributed generation (DG) and energy storage system (ESS) can provide time for the implementation of IBDR. The paper focus on the reliability evaluation of microgrid considering IBDR. Firstly, the mechanism of IBDR and its impact on power supply reliability are analysed. Secondly, the IBDR dispatch model considering customer’s comprehensive assessment and the customer response model are developed. Thirdly, the reliability evaluation method considering IBDR based on Monte Carlo simulation is proposed. Finally, the validity of the above models and method is studied through numerical tests on modified RBTS Bus6 test system. Simulation results demonstrated that IBDR can improve the reliability of microgrid.

Direct-to-consumer advertising of predictive genetic tests: a health belief model based examination of consumer response.

Science.gov (United States)

Rollins, Brent L; Ramakrishnan, Shravanan; Perri, Matthew

2014-01-01

Direct-to-consumer (DTC) advertising of predictive genetic tests (PGTs) has added a new dimension to health advertising. This study used an online survey based on the health belief model framework to examine and more fully understand consumers' responses and behavioral intentions in response to a PGT DTC advertisement. Overall, consumers reported moderate intentions to talk with their doctor and seek more information about PGTs after advertisement exposure, though consumers did not seem ready to take the advertised test or engage in active information search. Those who perceived greater threat from the disease, however, had significantly greater behavioral intentions and information search behavior.

A template-based approach for responsibility management in executable business processes

Science.gov (United States)

Cabanillas, Cristina; Resinas, Manuel; Ruiz-Cortés, Antonio

2018-05-01

Process-oriented organisations need to manage the different types of responsibilities their employees may have w.r.t. the activities involved in their business processes. Despite several approaches provide support for responsibility modelling, in current Business Process Management Systems (BPMS) the only responsibility considered at runtime is the one related to performing the work required for activity completion. Others like accountability or consultation must be implemented by manually adding activities in the executable process model, which is time-consuming and error-prone. In this paper, we address this limitation by enabling current BPMS to execute processes in which people with different responsibilities interact to complete the activities. We introduce a metamodel based on Responsibility Assignment Matrices (RAM) to model the responsibility assignment for each activity, and a flexible template-based mechanism that automatically transforms such information into BPMN elements, which can be interpreted and executed by a BPMS. Thus, our approach does not enforce any specific behaviour for the different responsibilities but new templates can be modelled to specify the interaction that best suits the activity requirements. Furthermore, libraries of templates can be created and reused in different processes. We provide a reference implementation and build a library of templates for a well-known set of responsibilities.

A Generalized QMRA Beta-Poisson Dose-Response Model.

Science.gov (United States)

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

2016-10-01

Quantitative microbial risk assessment (QMRA) is widely accepted for characterizing the microbial risks associated with food, water, and wastewater. Single-hit dose-response models are the most commonly used dose-response models in QMRA. Denoting PI(d) as the probability of infection at a given mean dose d, a three-parameter generalized QMRA beta-Poisson dose-response model, PI(d|α,β,r*), is proposed in which the minimum number of organisms required for causing infection, K min , is not fixed, but a random variable following a geometric distribution with parameter 0Poisson model, PI(d|α,β), is a special case of the generalized model with K min = 1 (which implies r*=1). The generalized beta-Poisson model is based on a conceptual model with greater detail in the dose-response mechanism. Since a maximum likelihood solution is not easily available, a likelihood-free approximate Bayesian computation (ABC) algorithm is employed for parameter estimation. By fitting the generalized model to four experimental data sets from the literature, this study reveals that the posterior median r* estimates produced fall short of meeting the required condition of r* = 1 for single-hit assumption. However, three out of four data sets fitted by the generalized models could not achieve an improvement in goodness of fit. These combined results imply that, at least in some cases, a single-hit assumption for characterizing the dose-response process may not be appropriate, but that the more complex models may be difficult to support especially if the sample size is small. The three-parameter generalized model provides a possibility to investigate the mechanism of a dose-response process in greater detail than is possible under a single-hit model. © 2016 Society for Risk Analysis.

Autonomous journaling response using data model LUTS

Science.gov (United States)

Jaenisch, Holger; Handley, James; Albritton, Nathaniel; Whitener, David; Burnett, Randel; Caspers, Robert; Moren, Stephen; Alexander, Thomas; Maddox, William, III; Albritton, William, Jr.

2009-04-01

Matching journal entries to appropriate context responses can be a daunting problem, especially when there are no salient keyword matches between the entry and the proposed library of appropriate responses. We examine a real-world application for matching interactive journaling requests for guidance to an a priori established archive of sufficient multimedia responses. We show the analysis required to enable a Data Model based algorithm to group journaling entries according to intrinsic context information and type. We demonstrate a new lookup table (LUT) classifier that exploits all available data in LUT form.

Impulse-response analysis of the market share attraction model

NARCIS (Netherlands)

D. Fok (Dennis); Ph.H.B.F. Franses (Philip Hans)

1999-01-01

textabstractWe propose a simulation-based technique to calculate impulse-response functions and their confidence intervals in a market share attraction model [MCI]. As an MCI model implies a reduced form model for the logs of relative market shares, simulation techniques have to be used to obtain

Blinded prospective evaluation of computer-based mechanistic schizophrenia disease model for predicting drug response.

Directory of Open Access Journals (Sweden)

Hugo Geerts

Full Text Available The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published 'Quantitative Systems Pharmacology' computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D(2 antagonist and ocaperidone, a very high affinity dopamine D(2 antagonist, using only pharmacology and human positron emission tomography (PET imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS total score and the higher extra-pyramidal symptom (EPS liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development.

Thermodynamical aspects of modeling the mechanical response of granular materials

International Nuclear Information System (INIS)

Elata, D.

1995-01-01

In many applications in rock physics, the material is treated as a continuum. By supplementing the related conservation laws with constitutive equations such as stress-strain relations, a well-posed problem can be formulated and solved. The stress-strain relations may be based on a combination of experimental data and a phenomenological or micromechanical model. If the model is physically sound and its parameters have a physical meaning, it can serve to predict the stress response of the material to unmeasured deformations, predict the stress response of other materials, and perhaps predict other categories of the mechanical response such as failure, permeability, and conductivity. However, it is essential that the model be consistent with all conservation laws and consistent with the second law of thermodynamics. Specifically, some models of the mechanical response of granular materials proposed in literature, are based on intergranular contact force-displacement laws that violate the second law of thermodynamics by permitting energy generation at no cost. This diminishes the usefulness of these models as it invalidates their predictive capabilities. [This work was performed under the auspices of the U.S. DOE by Lawrence Livermore National Laboratory under Contract No. W-7405-ENG-48.

Online Statistical Modeling (Regression Analysis) for Independent Responses

Science.gov (United States)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

Bayes Factor Covariance Testing in Item Response Models.

Science.gov (United States)

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Improving Rice Modeling Success Rate with Ternary Non-structural Fertilizer Response Model.

Science.gov (United States)

Li, Juan; Zhang, Mingqing; Chen, Fang; Yao, Baoquan

2018-06-13

Fertilizer response modelling is an important technical approach to realize metrological fertilization on rice. With the goal of solving the problems of a low success rate of a ternary quadratic polynomial model (TPFM) and to expand the model's applicability, this paper established a ternary non-structural fertilizer response model (TNFM) based on the experimental results from N, P and K fertilized rice fields. Our research results showed that the TNFM significantly improved the modelling success rate by addressing problems arising from setting the bias and multicollinearity in a TPFM. The results from 88 rice field trials in China indicated that the proportion of typical TNFMs that satisfy the general fertilizer response law of plant nutrition was 40.9%, while the analogous proportion of TPFMs was only 26.1%. The recommended fertilization showed a significant positive linear correlation between the two models, and the parameters N 0 , P 0 and K 0 that estimated the value of soil supplying nutrient equivalents can be used as better indicators of yield potential in plots where no N or P or K fertilizer was applied. The theoretical analysis showed that the new model has a higher fitting accuracy and a wider application range.

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

Science.gov (United States)

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

2015-03-01

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

Earthquake response analysis of a base isolated building

International Nuclear Information System (INIS)

Mazda, T.; Shiojiri, H.; Sawada, Y.; Harada, O.; Kawai, N.; Ontsuka, S.

1989-01-01

Recently, the seismic isolation has become one of the popular methods in the design of important structures or equipments against the earthquakes. However, it is desired to accumulate the demonstration data on reliability of seismically isolated structures and to establish the analysis methods of those structures. Based on the above recognition, the vibration tests of a base isolated building were carried out in Tsukuba Science City. After that, many earthquake records have been obtained at the building. In order to examine the validity of numerical models, earthquake response analyses have been executed by using both lumped mass model, and finite element model

Modelling structural systems for transient response analysis

International Nuclear Information System (INIS)

Melosh, R.J.

1975-01-01

This paper introduces and reports success of a direct means of determining the time periods in which a structural system behaves as a linear system. Numerical results are based on post fracture transient analyses of simplified nuclear piping systems. Knowledge of the linear response ranges will lead to improved analysis-test correlation and more efficient analyses. It permits direct use of data from physical tests in analysis and simplication of the analytical model and interpretation of its behavior. The paper presents a procedure for deducing linearity based on transient responses. Given the forcing functions and responses of discrete points of the system at various times, the process produces evidence of linearity and quantifies an adequate set of equations of motion. Results of use of the process with linear and nonlinear analyses of piping systems with damping illustrate its success. Results cover the application to data from mathematical system responses. The process is successfull with mathematical models. In loading ranges in which all modes are excited, eight digit accuracy of predictions are obtained from the equations of motion deduced. Small changes (less than 0.01%) in the norm of the transfer matrices are produced by manipulation errors for linear systems yielding evidence that nonlinearity is easily distinguished. Significant changes (greater than five %) are coincident with relatively large norms of the equilibrium correction vector in nonlinear analyses. The paper shows that deducing linearity and, when admissible, quantifying linear equations of motion from transient response data for piping systems can be achieved with accuracy comparable to that of response data

A new constitutive model for prediction of impact rates response of polypropylene

Directory of Open Access Journals (Sweden)

Buckley C.P.

2012-08-01

Full Text Available This paper proposes a new constitutive model for predicting the impact rates response of polypropylene. Impact rates, as used here, refer to strain rates greater than 1000 1/s. The model is a physically based, three-dimensional constitutive model which incorporates the contributions of the amorphous, crystalline, pseudo-amorphous and entanglement networks to the constitutive response of polypropylene. The model mathematics is based on the well-known Glass-Rubber model originally developed for glassy polymers but the arguments have herein been extended to semi-crystalline polymers. In order to predict the impact rates behaviour of polypropylene, the model exploits the well-known framework of multiple processes yielding of polymers. This work argues that two dominant viscoelastic relaxation processes – the alpha- and beta-processes – can be associated with the yield responses of polypropylene observed at low-rate-dominant and impact-rates dominant loading regimes. Compression test data on polypropylene have been used to validate the model. The study has found that the model predicts quite well the experimentally observed nonlinear rate-dependent impact response of polypropylene.

A biological-based model that links genomic instability, bystander effects, and adaptive response

International Nuclear Information System (INIS)

Scott, B.R.

2004-01-01

This paper links genomic instability, bystander effects, and adaptive response in mammalian cell communities via a novel biological-based, dose-response model called NEOTRANS 3 . The model is an extension of the NEOTRANS 2 model that addressed stochastic effects (genomic instability, mutations, and neoplastic transformation) associated with brief exposure to low radiation doses. With both models, ionizing radiation produces DNA damage in cells that can be associated with varying degrees of genomic instability. Cells with persistent problematic instability (PPI) are mutants that arise via misrepair of DNA damage. Progeny of PPI cells also have PPI and can undergo spontaneous neoplastic transformation. Unlike NEOTRANS 2 , with NEOTRANS 3 newly induced mutant PPI cells and their neoplastically transformed progeny can be suppressed via our previously introduced protective apoptosis-mediated (PAM) process, which can be activated by low linear energy transfer (LET) radiation. However, with NEOTRANS 3 (which like NEOTRANS 2 involves cross-talk between nongenomically compromised [e.g., nontransformed, nonmutants] and genomically compromised [e.g., mutants, transformants, etc.] cells), it is assumed that PAM is only activated over a relatively narrow, dose-rate-dependent interval (D PAM ,D off ); where D PAM is a small stochastic activation threshold, and D off is the stochastic dose above which PAM does not occur. PAM cooperates with activated normal DNA repair and with activated normal apoptosis in guarding against genomic instability. Normal repair involves both error-free repair and misrepair components. Normal apoptosis and the error-free component of normal repair protect mammals by preventing the occurrence of mutant cells. PAM selectively removes mutant cells arising via the misrepair component of normal repair, selectively removes existing neoplastically transformed cells, and probably selectively removes other genomically compromised cells when it is activated

Using an agent-based model to analyze the dynamic communication network of the immune response

Directory of Open Access Journals (Sweden)

Doolittle John

2011-01-01

loss outcomes. Conclusions An agent-based model capturing several key aspects of complex system dynamics was used to study the emergent properties of the immune response to viral infection. Specific patterns of interactions between leukocyte agents occurring early in the response significantly improved outcome. More interactions at later stages correlated with persistent inflammation and infection. These simulation experiments highlight the importance of commonly overlooked aspects of the immune response and provide insight into these processes at a resolution level exceeding the capabilities of current laboratory technologies.

Simulation-based Strategies for Smart Demand Response

Directory of Open Access Journals (Sweden)

Ines Leobner

2018-03-01

Full Text Available Demand Response can be seen as one effective way to harmonize demand and supply in order to achieve high self-coverage of energy consumption by means of renewable energy sources. This paper presents two different simulation-based concepts to integrate demand-response strategies into energy management systems in the customer domain of the Smart Grid. The first approach is a Model Predictive Control of the heating and cooling system of a low-energy office building. The second concept aims at industrial Demand Side Management by integrating energy use optimization into industrial automation systems. Both approaches are targeted at day-ahead planning. Furthermore, insights gained into the implications of the concepts onto the design of the model, simulation and optimization will be discussed. While both approaches share a similar architecture, different modelling and simulation approaches were required by the use cases.

Modeling the controllable pH-responsive swelling and pore size of networked alginate based biomaterials.

Science.gov (United States)

Chan, Ariel W; Neufeld, Ronald J

2009-10-01

Semisynthetic network alginate polymer (SNAP), synthesized by acetalization of linear alginate with di-aldehyde, is a pH-responsive tetrafunctionally linked 3D gel network, and has potential application in oral delivery of protein therapeutics and active biologicals, and as tissue bioscaffold for regenerative medicine. A constitutive polyelectrolyte gel model based on non-Gaussian polymer elasticity, Flory-Huggins liquid lattice theory, and non-ideal Donnan membrane equilibria was derived, to describe SNAP gel swelling in dilute and ionic solutions containing uni-univalent, uni-bivalent, bi-univalent or bi-bi-valent electrolyte solutions. Flory-Huggins interaction parameters as a function of ionic strength and characteristic ratio of alginates of various molecular weights were determined experimentally to numerically predict SNAP hydrogel swelling. SNAP hydrogel swells pronouncedly to 1000 times in dilute solution, compared to its compact polymer volume, while behaving as a neutral polymer with limited swelling in high ionic strength or low pH solutions. The derived model accurately describes the pH-responsive swelling of SNAP hydrogel in acid and alkaline solutions of wide range of ionic strength. The pore sizes of the synthesized SNAP hydrogels of various crosslink densities were estimated from the derived model to be in the range of 30-450 nm which were comparable to that measured by thermoporometry, and diffusion of bovine serum albumin. The derived equilibrium swelling model can characterize hydrogel structure such as molecular weight between crosslinks and crosslinking density, or can be used as predictive model for swelling, pore size and mechanical properties if gel structural information is known, and can potentially be applied to other point-link network polyelectrolytes such as hyaluronic acid gel.

Modeling urbanized watershed flood response changes with distributed hydrological model: key hydrological processes, parameterization and case studies

Science.gov (United States)

Chen, Y.

2017-12-01

Urbanization is the world development trend for the past century, and the developing countries have been experiencing much rapider urbanization in the past decades. Urbanization brings many benefits to human beings, but also causes negative impacts, such as increasing flood risk. Impact of urbanization on flood response has long been observed, but quantitatively studying this effect still faces great challenges. For example, setting up an appropriate hydrological model representing the changed flood responses and determining accurate model parameters are very difficult in the urbanized or urbanizing watershed. In the Pearl River Delta area, rapidest urbanization has been observed in China for the past decades, and dozens of highly urbanized watersheds have been appeared. In this study, a physically based distributed watershed hydrological model, the Liuxihe model is employed and revised to simulate the hydrological processes of the highly urbanized watershed flood in the Pearl River Delta area. A virtual soil type is then defined in the terrain properties dataset, and its runoff production and routing algorithms are added to the Liuxihe model. Based on a parameter sensitive analysis, the key hydrological processes of a highly urbanized watershed is proposed, that provides insight into the hydrological processes and for parameter optimization. Based on the above analysis, the model is set up in the Songmushan watershed where there is hydrological data observation. A model parameter optimization and updating strategy is proposed based on the remotely sensed LUC types, which optimizes model parameters with PSO algorithm and updates them based on the changed LUC types. The model parameters in Songmushan watershed are regionalized at the Pearl River Delta area watersheds based on the LUC types of the other watersheds. A dozen watersheds in the highly urbanized area of Dongguan City in the Pearl River Delta area were studied for the flood response changes due to

Modelling sequentially scored item responses

NARCIS (Netherlands)

Akkermans, W.

2000-01-01

The sequential model can be used to describe the variable resulting from a sequential scoring process. In this paper two more item response models are investigated with respect to their suitability for sequential scoring: the partial credit model and the graded response model. The investigation is

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

Science.gov (United States)

van Rijn, Peter W; Ali, Usama S

2017-05-01

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

On the relation between Kaiser–Bessel blob and tube of response based modelling of the system matrix in iterative PET image reconstruction

International Nuclear Information System (INIS)

Lougovski, Alexandr; Hofheinz, Frank; Maus, Jens; Schramm, Georg; Van den Hoff, Jörg

2015-01-01

We investigate the question of how the blob approach is related to tube of response based modelling of the system matrix. In our model, the tube of response (TOR) is approximated as a cylinder with constant density (TOR-CD) and the cubic voxels are replaced by spheres. Here we investigate a modification of the TOR model that makes it effectively equivalent to the blob model, which models the intersection of lines of response (LORs) with radially variant basis functions (‘blobs’) replacing the cubic voxels. Implications of the achieved equivalence regarding the necessity of final resampling in blob-based reconstructions are considered. We extended TOR-CD to a variable density tube model (TOR-VD) that yields a weighting function (defining all system matrix elements) which is essentially identical to that of the blob model. The variable density of TOR-VD was modelled by a Gaussian and a Kaiser–Bessel function, respectively. The free parameters of both model functions were determined by fitting the corresponding weighting function to the weighting function of the blob model. TOR-CD and the best-fitting TOR-VD were compared to the blob model with a final resampling step (BLOB-RS) and without resampling (BLOB-NRS) in phantom studies. For three different contrast ratios and two different voxel sizes, resolution noise curves were generated. TOR-VD and BLOB-NRS lead to nearly identical images for all investigated contrast ratios and voxel sizes. Both models showed strong Gibbs artefacts at 4 mm voxel size, while at 2 mm voxel size there were no Gibbs artefacts visible. The spatial resolution was similar to the resolution with TOR-CD in all cases. The resampling step removed most of the Gibbs artefacts and reduced the noise level but also degraded the spatial resolution substantially. We conclude that the blob model can be considered just as a special case of a TOR-based reconstruction. The latter approach provides a more natural description of the detection process

Modeling the mechanical response of PBX 9501

Energy Technology Data Exchange (ETDEWEB)

Ragaswamy, Partha [Los Alamos National Laboratory; Lewis, Matthew W [Los Alamos National Laboratory; Liu, Cheng [Los Alamos National Laboratory; Thompson, Darla G [Los Alamos National Laboratory

2010-01-01

An engineering overview of the mechanical response of Plastic-Bonded eXplosives (PBXs), specifically PBX 9501, will be provided with emphasis on observed mechanisms associated with different types of mechanical testing. Mechanical tests in the form of uniaxial tension, compression, cyclic loading, creep (compression and tension), and Hopkinson bar show strain rate and temperature dependence. A range of mechanical behavior is observed which includes small strain recoverable response in the form of viscoelasticity; change in stiffness and softening beyond peak strength due to damage in the form microcracks, debonding, void formation and the growth of existing voids; inelastic response in the form of irrecoverable strain as shown in cyclic tests, and viscoelastic creep combined with plastic response as demonstrated in creep and recovery tests. The main focus of this paper is to elucidate the challenges and issues involved in modeling the mechanical behavior of PBXs for simulating thermo-mechanical responses in engineering components. Examples of validation of a constitutive material model based on a few of the observed mechanisms will be demonstrated against three point bending, split Hopkinson pressure bar and Brazilian disk geometry.

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

Science.gov (United States)

Molenaar, Dylan; de Boeck, Paul

2018-06-01

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

Hydrologic response to multimodel climate output using a physically based model of groundwater/surface water interactions

Science.gov (United States)

Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.

2012-12-01

General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.

Least-squares model-based halftoning

Science.gov (United States)

Pappas, Thrasyvoulos N.; Neuhoff, David L.

1992-08-01

A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach

Modeling exposure–lag–response associations with distributed lag non-linear models

Science.gov (United States)

Gasparrini, Antonio

2014-01-01

In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure–lag–response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24027094

Development of an interactive exploratory web-based modelling platform for informed decision-making and knowledgeable responses to global change

Science.gov (United States)

Holman, I.; Harrison, P.; Cojocaru, G.

2013-12-01

Informed decision-making and knowledgeable responses to global climate change impacts on natural resources and ecosystem services requires access to information resources that are credible, accurate, easy to understand, and appropriate. Too often stakeholders are limited to restricted scientific outputs produced by inaccessible models, generated from a limited number of scenario simulations chosen arbitrarily by researchers. This paper describes the outcomes of the CLIMSAVE project (www.climsave.eu), which has attempted to democratise climate change impacts, adaptation and vulnerability modelling, through developing the public domain interactive exploratory web-based CLIMSAVE Integrated Assessment (IA) Platform. The CLIMSAVE Integrated Assessment (IA) Platform aims to enable a wide range of stakeholders to improve their understanding surrounding impacts, adaptation responses and vulnerability of natural resources and ecosystem services under uncertain futures across Europe. The CLIMSAVE IA Platform contain linked simulation models (of the urban, water, agriculture, forestry, biodiversity and other sectors), IPCC AR4 climate scenarios and CLIMSAVE socio-economic scenarios, enabling users to select their inputs (climate and socioeconomic), rapidly run the models across Europe using their input settings and view their selected Impact (before, or after, adaptation) and Vulnerability (Figure 1) indicators. The CLIMSAVE IA Platform has been designed to promote both cognitive accessibility - the ease of understanding - and practical accessibility - the ease of application. Based upon partner and CLIMSAVE international experts' experience, examination of other participatory model interfaces and potential user requirements, we describe the design concepts and functionality that were identified, incorporated into the prototype CLIMSAVE IA Platform and further refined based on stakeholder feedback. The CLIMSAVE IA Platform is designed to facilitate a two-way iterative process

Response-based estimation of sea state parameters - Influence of filtering

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam

2007-01-01

Reliable estimation of the on-site sea state parameters is essential to decision support systems for safe navigation of ships. The wave spectrum can be estimated from procedures based on measured ship responses. The paper deals with two procedures—Bayesian Modelling and Parametric Modelling...

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

Science.gov (United States)

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

2015-02-01

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

Theory of thermoluminescence gamma dose response: The unified interaction model

International Nuclear Information System (INIS)

Horowitz, Y.S.

2001-01-01

We describe the development of a comprehensive theory of thermoluminescence (TL) dose response, the unified interaction model (UNIM). The UNIM is based on both radiation absorption stage and recombination stage mechanisms and can describe dose response for heavy charged particles (in the framework of the extended track interaction model - ETIM) as well as for isotropically ionising gamma rays and electrons (in the framework of the TC/LC geminate recombination model) in a unified and self-consistent conceptual and mathematical formalism. A theory of optical absorption dose response is also incorporated in the UNIM to describe the radiation absorption stage. The UNIM is applied to the dose response supralinearity characteristics of LiF:Mg,Ti and is especially and uniquely successful in explaining the ionisation density dependence of the supralinearity of composite peak 5 in TLD-100. The UNIM is demonstrated to be capable of explaining either qualitatively or quantitatively all of the major features of TL dose response with many of the variable parameters of the model strongly constrained by ancilliary optical absorption and sensitisation measurements

Modeling metabolic response to changes of enzyme amount in ...

African Journals Online (AJOL)

Based on the work of Hynne et al. (2001), in an in silico model of glycolysis, Saccharomyces cerevisiae is established by introducing an enzyme amount multiple factor (.) into the kinetic equations. The model is aimed to predict the metabolic response to the change of enzyme amount. With the help of .α, the amounts of ...

Declarative Event-Based Workflow as Distributed Dynamic Condition Response Graphs

DEFF Research Database (Denmark)

Hildebrandt, Thomas; Mukkamala, Raghava Rao

2010-01-01

We present Dynamic Condition Response Graphs (DCR Graphs) as a declarative, event-based process model inspired by the workflow language employed by our industrial partner and conservatively generalizing prime event structures. A dynamic condition response graph is a directed graph with nodes repr...... exemplify the use of distributed DCR Graphs on a simple workflow taken from a field study at a Danish hospital, pointing out their flexibility compared to imperative workflow models. Finally we provide a mapping from DCR Graphs to Buchi-automata....

Environmental optimal control strategies based on plant canopy photosynthesis responses and greenhouse climate model

Science.gov (United States)

Deng, Lujuan; Xie, Songhe; Cui, Jiantao; Liu, Tao

2006-11-01

It is the essential goal of intelligent greenhouse environment optimal control to enhance income of cropper and energy save. There were some characteristics such as uncertainty, imprecision, nonlinear, strong coupling, bigger inertia and different time scale in greenhouse environment control system. So greenhouse environment optimal control was not easy and especially model-based optimal control method was more difficult. So the optimal control problem of plant environment in intelligent greenhouse was researched. Hierarchical greenhouse environment control system was constructed. In the first level data measuring was carried out and executive machine was controlled. Optimal setting points of climate controlled variable in greenhouse was calculated and chosen in the second level. Market analysis and planning were completed in third level. The problem of the optimal setting point was discussed in this paper. Firstly the model of plant canopy photosynthesis responses and the model of greenhouse climate model were constructed. Afterwards according to experience of the planting expert, in daytime the optimal goals were decided according to the most maximal photosynthesis rate principle. In nighttime on plant better growth conditions the optimal goals were decided by energy saving principle. Whereafter environment optimal control setting points were computed by GA. Compared the optimal result and recording data in real system, the method is reasonable and can achieve energy saving and the maximal photosynthesis rate in intelligent greenhouse

Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization.

Directory of Open Access Journals (Sweden)

Devaraj Jayachandran

Full Text Available 6-Mercaptopurine (6-MP is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN through enzymatic reaction involving thiopurine methyltransferase (TPMT. Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP's widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient's ability to metabolize the drug instead of the traditional standard-dose-for-all approach.

Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization

Science.gov (United States)

Jayachandran, Devaraj; Laínez-Aguirre, José; Rundell, Ann; Vik, Terry; Hannemann, Robert; Reklaitis, Gintaras; Ramkrishna, Doraiswami

2015-01-01

6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP’s widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient’s ability to metabolize the drug instead of the traditional standard-dose-for-all approach. PMID:26226448

Modeling individuals’ cognitive and affective responses in spatial learning behavior

NARCIS (Netherlands)

Han, Q.; Arentze, T.A.; Timmermans, H.J.P.; Janssens, D.; Wets, G.; Lo, H.P.; Leung, Stephen C.H.; Tan, Susanna M.L.

2008-01-01

Activity-based analysis has slowly shifted gear from analysis of daily activity patterns to analysis and modeling of dynamic activity-travel patterns. In this paper, we describe a dynamic model that is concerned with simulating cognitive and affective responses in spatial learning behavior for a

Responsibility modelling for civil emergency planning

OpenAIRE

Sommerville, Ian; Storer, Timothy; Lock, Russell

2009-01-01

This paper presents a new approach to analysing and understanding civil emergency planning based on the notion of responsibility modelling combined with HAZOPS-style analysis of information requirements. Our goal is to represent complex contingency plans so that they can be more readily understood, so that inconsistencies can be highlighted and vulnerabilities discovered. In this paper, we outline the framework for contingency planning in the United Kingdom and introduce the notion of respons...

SU-D-207B-07: Development of a CT-Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer

Energy Technology Data Exchange (ETDEWEB)

Klawikowski, S; Christian, J; Schott, D; Zhang, M; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

2016-06-15

Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each daily CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p

A Theoretical Hypothesis on Ferris Wheel Model of University Social Responsibility

OpenAIRE

Le Kang

2016-01-01

According to the nature of the university, as a free and responsible academic community, USR is based on a different foundation —academic responsibility, so the Pyramid and the IC Model of CSR could not fully explain the most distinguished feature of USR. This paper sought to put forward a new model— Ferris Wheel Model, to illustrate the nature of USR and the process of achievement. The Ferris Wheel Model of USR shows the university creates a balanced, fairness and neutrality systemic structu...

An agent-based model of the response to angioplasty and bare-metal stent deployment in an atherosclerotic blood vessel.

Directory of Open Access Journals (Sweden)

Antonia E Curtin

Full Text Available PURPOSE: While animal models are widely used to investigate the development of restenosis in blood vessels following an intervention, computational models offer another means for investigating this phenomenon. A computational model of the response of a treated vessel would allow investigators to assess the effects of altering certain vessel- and stent-related variables. The authors aimed to develop a novel computational model of restenosis development following an angioplasty and bare-metal stent implantation in an atherosclerotic vessel using agent-based modeling techniques. The presented model is intended to demonstrate the body's response to the intervention and to explore how different vessel geometries or stent arrangements may affect restenosis development. METHODS: The model was created on a two-dimensional grid space. It utilizes the post-procedural vessel lumen diameter and stent information as its input parameters. The simulation starting point of the model is an atherosclerotic vessel after an angioplasty and stent implantation procedure. The model subsequently generates the final lumen diameter, percent change in lumen cross-sectional area, time to lumen diameter stabilization, and local concentrations of inflammatory cytokines upon simulation completion. Simulation results were directly compared with the results from serial imaging studies and cytokine levels studies in atherosclerotic patients from the relevant literature. RESULTS: The final lumen diameter results were all within one standard deviation of the mean lumen diameters reported in the comparison studies. The overlapping-stent simulations yielded results that matched published trends. The cytokine levels remained within the range of physiological levels throughout the simulations. CONCLUSION: We developed a novel computational model that successfully simulated the development of restenosis in a blood vessel following an angioplasty and bare-metal stent deployment based on

A constructive Indian country response to the evidence-based program mandate.

Science.gov (United States)

Walker, R Dale; Bigelow, Douglas A

2011-01-01

Over the last 20 years governmental mandates for preferentially funding evidence-based "model" practices and programs has become doctrine in some legislative bodies, federal agencies, and state agencies. It was assumed that what works in small sample, controlled settings would work in all community settings, substantially improving safety, effectiveness, and value-for-money. The evidence-based "model" programs mandate has imposed immutable "core components," fidelity testing, alien programming and program developers, loss of familiar programs, and resource capacity requirements upon tribes, while infringing upon their tribal sovereignty and consultation rights. Tribal response in one state (Oregon) went through three phases: shock and rejection; proposing an alternative approach using criteria of cultural appropriateness, aspiring to evaluability; and adopting logic modeling. The state heard and accepted the argument that the tribal way of knowing is different and valid. Currently, a state-authorized tribal logic model and a review panel process are used to approve tribal best practices for state funding. This constructive response to the evidence-based program mandate elevates tribal practices in the funding and regulatory world, facilitates continuing quality improvement and evaluation, while ensuring that practices and programs remain based on local community context and culture. This article provides details of a model that could well serve tribes facing evidence-based model program mandates throughout the country.

Proposal of a probabilistic dose-response model

International Nuclear Information System (INIS)

Barrachina, M.

1997-01-01

A biologically updated dose-response model is presented as an alternative to the linear-quadratic model currently in use for cancer risk assessment. The new model is based on the probability functions for misrepair and/or unrepair of DNA lesions, in terms of the radiation damage production rate in the cell (supposedly, a stem cell) and its repair-rate constant. The model makes use, interpreting it on the basis of misrepair probabilities, of the ''dose and dose-rate effectiveness factor'' of ICRP, and provides the way for a continuous extrapolation between the high and low dose-rate regions, ratifying the ''linear non-threshold hypothesis'' as the main option. Anyhow, the model throws some doubts about the additive property of the dose. (author)

Simulation of dynamic response of nuclear power plant based on user-defined model in PSASP

International Nuclear Information System (INIS)

Zhao Jie; Liu Dichen; Xiong Li; Chen Qi; Du Zhi; Lei Qingsheng

2010-01-01

Based on the energy transformation regularity in physical process of pressurized water reactors (PWR), PWR NPP models are established in PSASP (Power System Analysis Software Package), which are applicable for calculating the dynamic process of PWR NPP and power system transient stabilization. The power dynamic characteristics of PWR NPP is simulated and analyzed, including the PWR self-stability, self-regulation and power step responses under power regulation system. The results indicate that the PWR NPP can afford certain exterior disturbances and 10%P n step under temperature negative feedbacks. The regulate speed of PWR power can reach 5%P n /min under the power regulation system, which meets the requirement of peak regulation in Power Grid. (authors)

Sharing experiences: towards an evidence based model of dengue surveillance and outbreak response in Latin America and Asia.

Science.gov (United States)

Badurdeen, Shiraz; Valladares, David Benitez; Farrar, Jeremy; Gozzer, Ernesto; Kroeger, Axel; Kuswara, Novia; Ranzinger, Silvia Runge; Tinh, Hien Tran; Leite, Priscila; Mahendradhata, Yodi; Skewes, Ronald; Verrall, Ayesha

2013-06-24

The increasing frequency and intensity of dengue outbreaks in endemic and non-endemic countries requires a rational, evidence based response. To this end, we aimed to collate the experiences of a number of affected countries, identify strengths and limitations in dengue surveillance, outbreak preparedness, detection and response and contribute towards the development of a model contingency plan adaptable to country needs. The study was undertaken in five Latin American (Brazil, Colombia, Dominican Republic, Mexico, Peru) and five in Asian countries (Indonesia, Malaysia, Maldives, Sri Lanka, Vietnam). A mixed-methods approach was used which included document analysis, key informant interviews, focus-group discussions, secondary data analysis and consensus building by an international dengue expert meeting organised by the World Health Organization, Special Program for Research and Training in Tropical Diseases (WHO-TDR). Country information on dengue is based on compulsory notification and reporting ("passive surveillance"), with laboratory confirmation (in all participating Latin American countries and some Asian countries) or by using a clinical syndromic definition. Seven countries additionally had sentinel sites with active dengue reporting, some also had virological surveillance. Six had agreed a formal definition of a dengue outbreak separate to seasonal variation in case numbers. Countries collected data on a range of warning signs that may identify outbreaks early, but none had developed a systematic approach to identifying and responding to the early stages of an outbreak. Outbreak response plans varied in quality, particularly regarding the early response. The surge capacity of hospitals with recent dengue outbreaks varied; those that could mobilise additional staff, beds, laboratory support and resources coped best in comparison to those improvising a coping strategy during the outbreak. Hospital outbreak management plans were present in 9

Designing Iranian Model to Assess the Level of Health System Responsiveness.

Science.gov (United States)

Askari, Roohollah; Arab, Mohammad; Rashidian, Arash; Akbari-Sari, Ali; Hosseini, Seyed Mostafa; Gharaee, Hojat

2016-03-01

Given the rapid pace of changes in community health needs and the mission of healthcare organizations to provide and promote the community's health, the growing need to increase health system responsiveness to people as a key element of observance and fulfillment of justice is felt more than ever. This study was aimed at designing the native model of responsiveness for Iran and to validate the aspects of the proposed model. Our study had a cross-sectional design and was a validation study performed in 2014. In order to define and identify responsiveness model aspects, the first phase recorded the views of 200 key informants from 19 provinces of Iran. Snowball sampling was used to select experts (based on WHO guideline). Then, the opinions of 18 comments were received from service recipients in the form of three focus group discussions and were analyzed by the frame framework analysis (interviewed recipients were selected using the purposive sampling method). Finally, in order to confirm the model's efficacy, a responsiveness questionnaire with 7 aspects (domains) and 52 indicators (items) obtained from the initial proposed model was answered by 600 members of the selected families in the two provinces of Fars and Yazd. A multi-stage cluster sampling approach was used for the household survey. The results were analyzed by the Confirmatory Factor Analysis (CFA) test and through the use of Lisrel software. Confirmatory Factor Analysis, based on the results of the key informant survey and group discussions, showed that according to quantities of GFI = 0.91, CFI = 0.93, NFI = 0.91, RMSEA = 0.074, SRMR = 0.061 and Hoelter (CN) = 178.54 in outpatient services and where GFI = 0.89, CFI = 0.91, NFI = 0.86, RMSEA = 0.064, SRMR = 0.053 and Hoelter (CN) = 158.93 for inpatient services, seven factors (F) (dignity, informed choice, confidentiality, patient training and informing, access to services, quality of basic amenities, and access to social support) are the main

Process-based modeling of species' responses to climate change - a proof of concept using western North American trees

Science.gov (United States)

Evans, M. E.; Merow, C.; Record, S.; Menlove, J.; Gray, A.; Cundiff, J.; McMahon, S.; Enquist, B. J.

2013-12-01

Current attempts to forecast how species' distributions will change in response to climate change suffer under a fundamental trade-off: between modeling many species superficially vs. few species in detail (between correlative vs. mechanistic models). The goals of this talk are two-fold: first, we present a Bayesian multilevel modeling framework, dynamic range modeling (DRM), for building process-based forecasts of many species' distributions at a time, designed to address the trade-off between detail and number of distribution forecasts. In contrast to 'species distribution modeling' or 'niche modeling', which uses only species' occurrence data and environmental data, DRMs draw upon demographic data, abundance data, trait data, occurrence data, and GIS layers of climate in a single framework to account for two processes known to influence range dynamics - demography and dispersal. The vision is to use extensive databases on plant demography, distributions, and traits - in the Botanical Information and Ecology Network, the Forest Inventory and Analysis database (FIA), and the International Tree Ring Data Bank - to develop DRMs for North American trees. Second, we present preliminary results from building the core submodel of a DRM - an integral projection model (IPM) - for a sample of dominant tree species in western North America. IPMs are used to infer demographic niches - i.e., the set of environmental conditions under which population growth rate is positive - and project population dynamics through time. Based on >550,000 data points derived from FIA for nine tree species in western North America, we show IPM-based models of their current and future distributions, and discuss how IPMs can be used to forecast future forest productivity, mortality patterns, and inform efforts at assisted migration.

Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

Science.gov (United States)

Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng

2017-10-01

Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

Residential Demand Response Behaviour Modeling applied to Cyber-physical Intrusion Detection

DEFF Research Database (Denmark)

Heussen, Kai; Tyge, Emil; Kosek, Anna Magdalena

2017-01-01

by a mix of physical system parameters, exogenous influences, user behaviour and preferences, which can be characterized by unstructured models such as a time-varying finite impulse response. In this study, which is based on field data, it is shown how this characteristic response behaviours can...

Skull base chordomas: analysis of dose-response characteristics

International Nuclear Information System (INIS)

Niemierko, Andrzej; Terahara, Atsuro; Goitein, Michael

1997-01-01

Objective: To extract dose-response characteristics from dose-volume histograms and corresponding actuarial survival statistics for 115 patients with skull base chordomas. Materials and Methods: We analyzed data for 115 patients with skull base chordoma treated with combined photon and proton conformal radiotherapy to doses in the range 66.6Gy - 79.2Gy. Data set for each patient included gender, histology, age, tumor volume, prescribed dose, overall treatment time, time to recurrence or time to last observation, target dose-volume histogram, and several dosimetric parameters (minimum/mean/median/maximum target dose, percent of the target volume receiving the prescribed dose, dose to 90% of the target volume, and the Equivalent Uniform Dose (EUD). Data were analyzed using the Kaplan-Meier survivor function estimate, the proportional hazards (Cox) model, and parametric modeling of the actuarial probability of recurrence. Parameters of dose-response characteristics were obtained using the maximum likelihood method. Results: Local failure developed in 42 (36%) of patients, with actuarial local control rates at 5 years of 59.2%. The proportional hazards model revealed significant dependence of gender on the probability of recurrence, with female patients having significantly poorer prognosis (hazard ratio of 2.3 with the p value of 0.008). The Wilcoxon and the log-rank tests of the corresponding Kaplan-Meier recurrence-free survival curves confirmed statistical significance of this effect. The Cox model with stratification by gender showed significance of tumor volume (p=0.01), the minimum target dose (p=0.02), and the EUD (p=0.02). Other parameters were not significant at the α level of significance of 0.05, including the prescribed dose (p=0.21). Parametric analysis using a combined model of tumor control probability (to account for non-uniformity of target dose distribution) and the Weibull failure time model (to account for censoring) allowed us to estimate

Seismic Response Analysis and Design of Structure with Base Isolation

International Nuclear Information System (INIS)

Rosko, Peter

2010-01-01

The paper reports the study on seismic response and energy distribution of a multi-story civil structure. The nonlinear analysis used the 2003 Bam earthquake acceleration record as the excitation input to the structural model. The displacement response was analyzed in time domain and in frequency domain. The displacement and its derivatives result energy components. The energy distribution in each story provides useful information for the structural upgrade with help of added devices. The objective is the structural displacement response minimization. The application of the structural seismic response research is presented in base-isolation example.

Structural Damage Detection using Frequency Response Function Index and Surrogate Model Based on Optimized Extreme Learning Machine Algorithm

Directory of Open Access Journals (Sweden)

R. Ghiasi

2017-09-01

Full Text Available Utilizing surrogate models based on artificial intelligence methods for detecting structural damages has attracted the attention of many researchers in recent decades. In this study, a new kernel based on Littlewood-Paley Wavelet (LPW is proposed for Extreme Learning Machine (ELM algorithm to improve the accuracy of detecting multiple damages in structural systems.  ELM is used as metamodel (surrogate model of exact finite element analysis of structures in order to efficiently reduce the computational cost through updating process. In the proposed two-step method, first a damage index, based on Frequency Response Function (FRF of the structure, is used to identify the location of damages. In the second step, the severity of damages in identified elements is detected using ELM. In order to evaluate the efficacy of ELM, the results obtained from the proposed kernel were compared with other kernels proposed for ELM as well as Least Square Support Vector Machine algorithm. The solved numerical problems indicated that ELM algorithm accuracy in detecting structural damages is increased drastically in case of using LPW kernel.

Factorial-based response-surface modeling with confidence intervals for optimizing thermal-optical transmission analysis of atmospheric black carbon

International Nuclear Information System (INIS)

Conny, J.M.; Norris, G.A.; Gould, T.R.

2009-01-01

Thermal-optical transmission (TOT) analysis measures black carbon (BC) in atmospheric aerosol on a fibrous filter. The method pyrolyzes organic carbon (OC) and employs laser light absorption to distinguish BC from the pyrolyzed OC; however, the instrument does not necessarily separate the two physically. In addition, a comprehensive temperature protocol for the analysis based on the Beer-Lambert Law remains elusive. Here, empirical response-surface modeling was used to show how the temperature protocol in TOT analysis can be modified to distinguish pyrolyzed OC from BC based on the Beer-Lambert Law. We determined the apparent specific absorption cross sections for pyrolyzed OC (σ Char ) and BC (σ BC ), which accounted for individual absorption enhancement effects within the filter. Response-surface models of these cross sections were derived from a three-factor central-composite factorial experimental design: temperature and duration of the high-temperature step in the helium phase, and the heating increase in the helium-oxygen phase. The response surface for σ BC , which varied with instrument conditions, revealed a ridge indicating the correct conditions for OC pyrolysis in helium. The intersection of the σ BC and σ Char surfaces indicated the conditions where the cross sections were equivalent, satisfying an important assumption upon which the method relies. 95% confidence interval surfaces defined a confidence region for a range of pyrolysis conditions. Analyses of wintertime samples from Seattle, WA revealed a temperature between 830 deg. C and 850 deg. C as most suitable for the helium high-temperature step lasting 150 s. However, a temperature as low as 750 deg. C could not be rejected statistically

The fractional volatility model: An agent-based interpretation

Science.gov (United States)

Vilela Mendes, R.

2008-06-01

Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions

Science.gov (United States)

Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

2014-01-01

Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled

A Hearing-Based, Frequency Domain Sound Quality Model for Combined Aerodynamic and Power Transmission Response with Application to Rotorcraft Interior Noise

Science.gov (United States)

Sondkar, Pravin B.

The severity of combined aerodynamics and power transmission response in high-speed, high power density systems such as a rotorcraft is still a major cause of annoyance in spite of recent advancement in passive, semi-active and active control. With further increase in the capacity and power of this class of machinery systems, the acoustic noise levels are expected to increase even more. To achieve further improvements in sound quality, a more refined understanding of the factors and attributes controlling human perception is needed. In the case of rotorcraft systems, the perceived quality of the interior sound field is a major determining factor of passenger comfort. Traditionally, this sound quality factor is determined by measuring the response of a chosen set of juries who are asked to compare their qualitative reactions to two or more sounds based on their subjective impressions. This type of testing is very time-consuming, costly, often inconsistent, and not useful for practical design purposes. Furthermore, there is no known universal model for sound quality. The primary aim of this research is to achieve significant improvements in quantifying the sound quality of combined aerodynamic and power transmission response in high-speed, high power density machinery systems such as a rotorcraft by applying relevant objective measures related to the spectral characteristics of the sound field. Two models have been proposed in this dissertation research. First, a classical multivariate regression analysis model based on currently known sound quality metrics as well some new metrics derived in this study is presented. Even though the analysis resulted in the best possible multivariate model as a measure of the acoustic noise quality, it lacks incorporation of human judgment mechanism. The regression model can change depending on specific application, nature of the sounds and types of juries used in the study. Also, it predicts only the averaged preference scores and

Equipment response spectra for base-isolated shear beam structures

International Nuclear Information System (INIS)

Ahmadi, G.; Su, L.

1992-01-01

Equipment response spectra in base-isolated structure under seismic ground excitations are studied. The equipment is treated as a single-degree-of-freedom system attached to a nonuniform elastic beam structural model. Several leading base isolation systems, including the laminated rubber bearing, the resilient-friction base isolator with and without a sliding upper plate, and the EDF system are considered. Deflection and acceleration response spectra for the equipment and the shear beam structure subject to a sinusoidal and the accelerogram of the N00W component of El Centro 1940 earthquake are evaluated. Primary-secondary interaction effects are included in the analysis. Several numerical parametric studies are carried out and the effectiveness of different base isolation systems in protecting the nonstructural components is studied. It is shown that use of properly designed base isolation systems provides considerable protection for secondary systems, as well as, the structure against severe seismic loadings. (orig.)

Calibration and testing of IKU's oil spill contingency and response (OSCAR) model system

International Nuclear Information System (INIS)

Reed, M.; Aamo, O.M.; Downing, K.

1996-01-01

A computer modeling system entitled Oil Spill Contingency and Response (OSCAR), was calibrated and tested using a variety of field observations. The objective of the exercise was to establish model credibility and increase confidence in efforts to compare alternate oil spill response strategies, while maintaining a balance between response costs and environmental protection. The key components of the system are IKU's data-based oil weathering model, a three dimensional oil trajectory and chemical fates model, an oil spill combat model, and exposure models for fish, ichthyoplankton, birds, and marine mammals. Most modelled calculations were in good agreement with field observations. One discrepancy was found which could be attributed to an underestimation of wind drift in the current model. 21 refs., 4 tabs., 32 figs

Endochronic constitutive model for general hysteretic response of soils. Final report

International Nuclear Information System (INIS)

Read, H.E.; Valanis, K.C.

1979-01-01

A new endochronic theory of plasticity is presented which can accurately describe the mechanical response of hysteretic materials to complex, three-dimensional deformation histories, including cyclic deformation. The theory is based on several new advancements in the endochronic framework, which broaden its predictive scope. Various features of the resulting model are illustrated, including its ability to describe (1) cyclic simple shear of dry sand and wet clay over many cycles of deformation, (2) response of a real soil (McCormick Ranch soil) to the standard laboratory soil tests, and (3) response of McCormick Ranch soil to cyclic triaxial tests. It is believed that this is the first constitutive model that has demonstrated the capability to realistically describe, for a given soil, both standard laboratory tests and cyclic response under three-dimensional loading conditions. The constitutive model presented here should allow more meaningful analyses to be made in many areas of soil response, particularly for ground motion and soil-structure interaction due to to other seimsic disturbances. The proposed model also has wide application to other materials, such as metals, and could provide improved descriptions of the response of various metallic components under transient loads

Studies on modeling to failed fuel detection system response in LMFBR

International Nuclear Information System (INIS)

Miyazawa, T.; Saji, G.; Mitsuzuku, N.; Hikichi, T.; Odo, T.; Rindo, H.

1981-05-01

Failed Fuel Detection (FFD) system with Fission Products (FP) detection is considered to be the most promissing method, since FP provides direct information against fuel element failure. For designing FFD system and for evaluating FFD signals, some adequate FFD signal response to fuel failure have been required. But few models are available in nowadays. Thus Power Reactor and Nuclear Fuel Development Corporation (PNC) had developed FFD response model with computer codes, based on several fundamental investigations on FP release and FP behavior, and referred to foreign country experiences on fuel failure. In developing the model, noble gas and halogen FP release and behavior were considered, since FFD system would be composed of both cover gas monitoring and delayed neutron monitoring. The developed model can provide typical fuel failure response and detection limit which depends on various background signals at cover gas monitoring and delayed neutron monitoring. According to the FFD response model, we tried to assume fuel failure response and detection limit at Japan experimental fast reactor ''JOYO''. The detection limit of JOYO FFD system was estimated by measuring the background signals. Followed on the studies, a complete computer code has been now made with some improvement. On the paper, the details of the model, out line of developed computer code, status of JOYO FFD system, and trial assumption of JOYO FFD response and detection limit. (author)

Experience Report: Constraint-Based Modelling and Simulation of Railway Emergency Response Plans

DEFF Research Database (Denmark)

Debois, Søren; Hildebrandt, Thomas; Sandberg, Lene

2016-01-01

ways to proceed, including ways not necessarily anticipated in the paper-based emergency response plans. The case study was undertaken as part of a short research, ProSec, project funded by the Danish Defence Agency, with the aim of applying and developing methods for collaborative mapping of emergency...

Implementation of angular response function modeling in SPECT simulations with GATE

International Nuclear Information System (INIS)

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

2010-01-01

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

Implementation of angular response function modeling in SPECT simulations with GATE

Energy Technology Data Exchange (ETDEWEB)

Descourt, P; Visvikis, D [INSERM, U650, LaTIM, IFR SclnBioS, Universite de Brest, CHU Brest, Brest, F-29200 (France); Carlier, T; Bardies, M [CRCNA INSERM U892, Nantes (France); Du, Y; Song, X; Frey, E C; Tsui, B M W [Department of Radiology, J Hopkins University, Baltimore, MD (United States); Buvat, I, E-mail: dimitris@univ-brest.f [IMNC-UMR 8165 CNRS Universites Paris 7 et Paris 11, Orsay (France)

2010-05-07

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

Modeling Rabbit Responses to Single and Multiple Aerosol ...

Science.gov (United States)

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

Physics-based Entry, Descent and Landing Risk Model

Science.gov (United States)

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

2014-01-01

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

Characterizing Class-Specific Exposure-Viral Load Suppression Response of HIV Antiretrovirals Using A Model-Based Meta-Analysis.

Science.gov (United States)

Xu, Y; Li, Y F; Zhang, D; Dockendorf, M; Tetteh, E; Rizk, M L; Grobler, J A; Lai, M-T; Gobburu, J; Ankrom, W

2016-08-01

We applied model-based meta-analysis of viral suppression as a function of drug exposure and in vitro potency for short-term monotherapy in human immunodeficiency virus type 1 (HIV-1)-infected treatment-naïve patients to set pharmacokinetic targets for development of nonnucleoside reverse transcriptase inhibitors (NNRTIs) and integrase strand transfer inhibitors (InSTIs). We developed class-specific models relating viral load kinetics from monotherapy studies to potency normalized steady-state trough plasma concentrations. These models were integrated with a literature assessment of doses which demonstrated to have long-term efficacy in combination therapy, in order to set steady-state trough concentration targets of 6.17- and 2.15-fold above potency for NNRTIs and InSTIs, respectively. Both the models developed and the pharmacokinetic targets derived can be used to guide compound selection during preclinical development and to predict the dose-response of new antiretrovirals to inform early clinical trial design. © 2016 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

A Memory-Based Model of Hick's Law

Science.gov (United States)

Schneider, Darryl W.; Anderson, John R.

2011-01-01

We propose and evaluate a memory-based model of Hick's law, the approximately linear increase in choice reaction time with the logarithm of set size (the number of stimulus-response alternatives). According to the model, Hick's law reflects a combination of associative interference during retrieval from declarative memory and occasional savings…

A model of the radiation-induced bystander effect based on an analogy with ferromagnets. Application to modelling tissue response in a uniform field

Science.gov (United States)

Vassiliev, O. N.

2014-12-01

We propose a model of the radiation-induced bystander effect based on an analogy with magnetic systems. The main benefit of this approach is that it allowed us to apply powerful methods of statistical mechanics. The model exploits the similarity between how spin-spin interactions result in correlations of spin states in ferromagnets, and how signalling from a damaged cell reduces chances of survival of neighbour cells, resulting in correlated cell states. At the root of the model is a classical Hamiltonian, similar to that of an Ising ferromagnet with long-range interactions. The formalism is developed in the framework of the Mean Field Theory. It is applied to modelling tissue response in a uniform radiation field. In this case the results are remarkably simple and at the same time nontrivial. They include cell survival curves, expressions for the tumour control probability and effects of fractionation. The model extends beyond of what is normally considered as bystander effects. It offers an insight into low-dose hypersensitivity and into mechanisms behind threshold doses for deterministic effects.

An agent-based model of signal transduction in bacterial chemotaxis.

Directory of Open Access Journals (Sweden)

Jameson Miller

2010-05-01

Full Text Available We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

An agent-based model of signal transduction in bacterial chemotaxis.

Science.gov (United States)

Miller, Jameson; Parker, Miles; Bourret, Robert B; Giddings, Morgan C

2010-05-13

We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

Coupled vertical-rocking response of base-isolated structures

International Nuclear Information System (INIS)

Pan, T.C.; Kelly, J.M.

1984-01-01

A base-isolated building can have a small horizontal eccentricity between the center of mass of the superstructure and the center of rigidity of the supporting bearings. The structure can be modeled as a rigid block with tributary masses supported on massless rubber bearings placed at a constant elevation below the center of mass. Perturbation methods are implemented to find the dynamic characteristics for both the detuned and the perfectly tuned cases. The Green's functions for the displacement response of the system are derived for the undamped and the damped conditions. The response spectrum modal superposition method is used in estimating the maximum acceleration. A simple method, accounting for the effect of closely spaced modes, is proposed for combining modal maxima and results in an approximate single-degree-of-freedom solution. This approximate solution may be used for thepreliminary design of a base-isolated structure. Numerical results for a base-isolated building subjected to the vertical component of the El Centro earthquake of 1940 were carried out for comparison with analytical results. It is shown that the effect of rocking coupling on the vertical seismic response of baseisolated structures can generally be neglected because of the combined effects of the time lag between the maximum translational and rotational responses and the influence of damping in the isolation system

Research on Power Producer’s Bidding Behavior Based on the Best-Response Dynamic Model

Directory of Open Access Journals (Sweden)

Jingqi Sun

2014-01-01

Full Text Available As China’s electricity market is facing many problems, the research on power producer’s bidding behavior can promote the healthy and sustainable development of China’s electricity market. As a special commodity, the “electricity” possesses complicated production process. The instable market constraint condition, nonsymmetric information, and a lot of random factors make the producer’s bidding process more complex. Best-response dynamic is one of the classic dynamic mechanisms of the evolutionary game theory, which applies well in the repeated game and strategy evolution that happen among a few bounded rational players with a quick learning capability. The best-response dynamic mechanism is employed to study the power producer’s bidding behavior in this paper, the producer’s best-response dynamic model is constructed, and how the producers would engage in bidding is analyzed in detail. Taking two generating units in South China regional electricity market as the example, the producer’s bidding behavior by following the producer’s best-response dynamic model is verified. The relationships between the evolutionarily stable strategy (ESS of power producer’s bidding and the market demand, and ceiling and floor price as well as biding frequency are discussed in detail.

Researches on modeling of nuclear power plants for dynamic response analysis

International Nuclear Information System (INIS)

Watabe, M.; Fukuzawa, R.; Chiba, O.; Toritani, T.

1983-01-01

The authors tried to establish the rational and economical model due to the vertical component considering the dynamic soil-structure interaction effects and the flexibility of the mat foundation. Three types of models were introduced. 1) Finite element model. Two cases of response analyses due to harmonic excitations with the finite element model were performed in which the mat foundation was treated rigid and elastic body. The dynamic soil-structure interaction effects were evaluated based on the condition that soil was semiinfinite elastic medium. 2) Sophisticated mass-spring-dashpot model. Two cases of response analyses due to harmonic excitations were performed to simulate the dynamic characteristics of the finite element models mentioned above using the sophisticated mass-spring-dashpot model, in which the dynamic soil-structure interaction effects were evaluated with the same procedure applied to the finite element model. 3) Simplified mass-spring-dashpot model. There were introduced three types of the simplified mass-spring-dashpot model in which the dynamic soil-structure interaction effects were simplified. Response analyses due to harmonic excitations and earthquake ground motions were performed in order to establish the rational and economical model. (orig./HP)

NGC1300 dynamics - II. The response models

Science.gov (United States)

Kalapotharakos, C.; Patsis, P. A.; Grosbøl, P.

2010-10-01

We study the stellar response in a spectrum of potentials describing the barred spiral galaxy NGC1300. These potentials have been presented in a previous paper and correspond to three different assumptions as regards the geometry of the galaxy. For each potential we consider a wide range of Ωp pattern speed values. Our goal is to discover the geometries and the Ωp supporting specific morphological features of NGC1300. For this purpose we use the method of response models. In order to compare the images of NGC1300 with the density maps of our models, we define a new index which is a generalization of the Hausdorff distance. This index helps us to find out quantitatively which cases reproduce specific features of NGC1300 in an objective way. Furthermore, we construct alternative models following a Schwarzschild-type technique. By this method we vary the weights of the various energy levels, and thus the orbital contribution of each energy, in order to minimize the differences between the response density and that deduced from the surface density of the galaxy, under certain assumptions. We find that the models corresponding to Ωp ~ 16 and 22 kms-1kpc-1 are able to reproduce efficiently certain morphological features of NGC1300, with each one having its advantages and drawbacks. Based on observations collected at the European Southern Observatory, Chile: programme ESO 69.A-0021. E-mail: ckalapot@phys.uoa.gr (CK); patsis@academyofathens.gr (PAP); pgrosbol@eso.org (PG)

Generation of floor response spectra for a model structure of nuclear power plant

International Nuclear Information System (INIS)

Vaidyanathan, C.V.; Kamatchi, P.; Ravichandran, R.; Lakshmanan, N.

2003-01-01

The importance of Nuclear power plants and the consequences of a nuclear accident require that the nuclear structures be designed for the most severe environmental conditions. Earthquakes constitutes major design consideration for the system, structures and equipment of a nuclear power plant. The design of structures on ground is based on the ground response spectra. Many important parts of a nuclear power plant facility are attached to the principal parts of the structure and respond in a manner determined by the structural response rather than by the general ground motion to which the structure is supported. Hence the seismic response of equipment is generally based on the response spectrum of the floor on which it is mounted. In this paper such floor response spectra have been generated at different nodes of a chosen model structure of a nuclear power plant. In the present study a detailed nonlinear time history analysis has been carried out on the mathematical model of the chosen Nuclear Power Plant model structure with the spectrum compatible time history. The acceleration response results of the time history analysis has been used in the spectral analysis and the response spectra are generated. Further peak broadening has been done to account for uncertainties in the material properties and soil characteristics. (author)

Measuring client experiences in maternity care under change: development of a questionnaire based on the WHO Responsiveness model.

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Marisja Scheerhagen

Full Text Available Maternity care is an integrated care process, which consists of different services, involves different professionals and covers different time windows. To measure performance of maternity care based on clients' experiences, we developed and validated a questionnaire.We used the 8-domain WHO Responsiveness model, and previous materials to develop a self-report questionnaire. A dual study design was used for development and validation. Content validity of the ReproQ-version-0 was determined through structured interviews with 11 pregnant women (≥28 weeks, 10 women who recently had given birth (≤12 weeks, and 19 maternity care professionals. Structured interviews established the domain relevance to the women; all items were separately commented on. All Responsiveness domains were judged relevant, with Dignity and Communication ranking highest. Main missing topic was the assigned expertise of the health professional. After first adaptation, construct validity of the ReproQ-version-1 was determined through a web-based survey. Respondents were approached by maternity care organizations with different levels of integration of services of midwives and obstetricians. We sent questionnaires to 605 third trimester pregnant women (response 65%, and 810 women 6 weeks after delivery (response 55%. Construct validity was based on: response patterns; exploratory factor analysis; association of the overall score with a Visual Analogue Scale (VAS, known group comparisons. Median overall ReproQ score was 3.70 (range 1-4 showing good responsiveness. The exploratory factor analysis supported the assumed domain structure and suggested several adaptations. Correlation of the VAS rating and overall ReproQ score (antepartum, postpartum supported validity (r = 0.56; 0.59, p<0.001 Spearman's correlation coefficient. Pre-stated group comparisons confirmed the expected difference following a good vs. adverse birth outcome. Fully integrated organizations performed

A Judgement-Based Model of Workplace Learning

Science.gov (United States)

Athanasou, James A.

2004-01-01

The purpose of this paper is to outline a judgement-based model of adult learning. This approach is set out as a Perceptual-Judgemental-Reinforcement approach to social learning under conditions of complexity and where there is no single, clearly identified correct response. The model builds upon the Hager-Halliday thesis of workplace learning and…

Food supply and demand, a simulation model of the functional response of grazing ruminants

NARCIS (Netherlands)

Smallegange, I.M.; Brunsting, A.M.H.

2002-01-01

A dynamic model of the functional response is a first prerequisite to be able to bridge the gap between local feeding ecology and grazing rules that pertain to larger scales. A mechanistic model is presented that simulates the functional response, growth and grazing time of ruminants. It is based on

An update on modeling dose-response relationships: Accounting for correlated data structure and heterogeneous error variance in linear and nonlinear mixed models.

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Gonçalves, M A D; Bello, N M; Dritz, S S; Tokach, M D; DeRouchey, J M; Woodworth, J C; Goodband, R D

2016-05-01

Advanced methods for dose-response assessments are used to estimate the minimum concentrations of a nutrient that maximizes a given outcome of interest, thereby determining nutritional requirements for optimal performance. Contrary to standard modeling assumptions, experimental data often present a design structure that includes correlations between observations (i.e., blocking, nesting, etc.) as well as heterogeneity of error variances; either can mislead inference if disregarded. Our objective is to demonstrate practical implementation of linear and nonlinear mixed models for dose-response relationships accounting for correlated data structure and heterogeneous error variances. To illustrate, we modeled data from a randomized complete block design study to evaluate the standardized ileal digestible (SID) Trp:Lys ratio dose-response on G:F of nursery pigs. A base linear mixed model was fitted to explore the functional form of G:F relative to Trp:Lys ratios and assess model assumptions. Next, we fitted 3 competing dose-response mixed models to G:F, namely a quadratic polynomial (QP) model, a broken-line linear (BLL) ascending model, and a broken-line quadratic (BLQ) ascending model, all of which included heteroskedastic specifications, as dictated by the base model. The GLIMMIX procedure of SAS (version 9.4) was used to fit the base and QP models and the NLMIXED procedure was used to fit the BLL and BLQ models. We further illustrated the use of a grid search of initial parameter values to facilitate convergence and parameter estimation in nonlinear mixed models. Fit between competing dose-response models was compared using a maximum likelihood-based Bayesian information criterion (BIC). The QP, BLL, and BLQ models fitted on G:F of nursery pigs yielded BIC values of 353.7, 343.4, and 345.2, respectively, thus indicating a better fit of the BLL model. The BLL breakpoint estimate of the SID Trp:Lys ratio was 16.5% (95% confidence interval [16.1, 17.0]). Problems with

Time-of-use based electricity demand response for sustainable manufacturing systems

International Nuclear Information System (INIS)

Wang, Yong; Li, Lin

2013-01-01

As required by the Energy Policy Act of 2005, utility companies across the U.S. are offering TOU (time-of-use) based electricity demand response programs. The TOU rate gives consumers opportunities to manage their electricity bill by shifting use from on-peak periods to mid-peak and off-peak periods. Reducing the amount of electricity needed during the peak load times makes it possible for the power grid to meet consumers' needs without building more costly backup infrastructures and help reduce GHG (greenhouse gas) emissions. Previous research on the applications of TOU and other electricity demand response programs has been mainly focused on residential and commercial buildings while largely neglected industrial manufacturing systems. This paper proposes a systems approach for TOU based electricity demand response for sustainable manufacturing systems under the production target constraint. Key features of this approach include: (i) the electricity related costs including both consumption and demand are integrated into production system modeling; (ii) energy-efficient and demand-responsive production scheduling problems are formulated and the solution technique is provided; and (iii) the effects of various factors on the near-optimal scheduling solutions are examined. The research outcome is expected to enhance the energy efficiency, electricity demand responsiveness, and cost effectiveness of modern manufacturing systems. - Highlights: • We propose a TOU based demand response approach for manufacturing systems. • Both electricity consumption and demand are integrated into the system modeling. • Energy-efficient and demand-responsive production scheduling problems are formulated. • The meta-heuristic solution technique is provided. • The effects of various factors on the scheduling solutions are examined

A Kriging Model Based Finite Element Model Updating Method for Damage Detection

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Xiuming Yang

2017-10-01

Full Text Available Model updating is an effective means of damage identification and surrogate modeling has attracted considerable attention for saving computational cost in finite element (FE model updating, especially for large-scale structures. In this context, a surrogate model of frequency is normally constructed for damage identification, while the frequency response function (FRF is rarely used as it usually changes dramatically with updating parameters. This paper presents a new surrogate model based model updating method taking advantage of the measured FRFs. The Frequency Domain Assurance Criterion (FDAC is used to build the objective function, whose nonlinear response surface is constructed by the Kriging model. Then, the efficient global optimization (EGO algorithm is introduced to get the model updating results. The proposed method has good accuracy and robustness, which have been verified by a numerical simulation of a cantilever and experimental test data of a laboratory three-story structure.

Responsive survey design, demographic data collection, and models of demographic behavior.

Science.gov (United States)

Axinn, William G; Link, Cynthia F; Groves, Robert M

2011-08-01

To address declining response rates and rising data-collection costs, survey methodologists have devised new techniques for using process data ("paradata") to address nonresponse by altering the survey design dynamically during data collection. We investigate the substantive consequences of responsive survey design-tools that use paradata to improve the representative qualities of surveys and control costs. By improving representation of reluctant respondents, responsive design can change our understanding of the topic being studied. Using the National Survey of Family Growth Cycle 6, we illustrate how responsive survey design can shape both demographic estimates and models of demographic behaviors based on survey data. By juxtaposing measures from regular and responsive data collection phases, we document how special efforts to interview reluctant respondents may affect demographic estimates. Results demonstrate the potential of responsive survey design to change the quality of demographic research based on survey data.

Fuzzy Logic Based Set-Point Weighting Controller Tuning for an Internal Model Control Based PID Controller

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Maruthai Suresh

2009-10-01

Full Text Available Controller tuning is the process of adjusting the parameters of the selected controller to achieve optimum response for the controlled process. For many of the control problems, a satisfactory performance is obtained by using PID controllers. One of the main problems with mathematical models of physical systems is that the parameters used in the models cannot be determined with absolute accuracy. The values of the parameters may change with time or various effects. In these cases, conventional controller tuning methods suffer when trying a lot to produce optimum response. In order to overcome these difficulties a fuzzy logic based Set- Point weighting controller tuning method is proposed. The effectiveness of the proposed scheme is analyzed through computer simulation using SIMULINK software and the results are presented. The fuzzy logic based simulation results are compared with Cohen-Coon (CC, Ziegler- Nichols (ZN, Ziegler – Nichols with Set- Point weighting (ZN-SPW, Internal Model Control (IMC and Internal model based PID controller responses (IMC-PID. The effects of process modeling errors and the importance of controller tuning have been brought out using the proposed control scheme.

From the Stimulus-Response to the Person-Context Model

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Arturo Barraza Macías

2007-07-01

Full Text Available In this manuscript, an alternative reading of the field of study of the stress is made that leads to raise the existence of two models: the Stimulus-Response and the Person-Context Models about Stress. Each one of them is presented with base in four indicators: historical antecedents, postulates, development and characteristics. In the end a critical valuation is made that the author leads to recognize in the Person-Surroundings Research Program of Stress, and in its tendency to the modeling, the route of development of the field of study of stress.

SLS Model Based Design: A Navigation Perspective

Science.gov (United States)

Oliver, T. Emerson; Anzalone, Evan; Park, Thomas; Geohagan, Kevin

2018-01-01

The SLS Program has implemented a Model-based Design (MBD) and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team is responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1B design, the additional GPS Receiver hardware model is managed as a DMM at the vehicle design level. This paper describes the models, and discusses the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the navigation components.

A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means

Science.gov (United States)

Polak, Marike; De Rooij, Mark; Heiser, Willem J.

2012-01-01

In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) "criterion…

Joint Testlet Cognitive Diagnosis Modeling for Paired Local Item Dependence in Response Times and Response Accuracy

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Peida Zhan

2018-04-01

Full Text Available In joint models for item response times (RTs and response accuracy (RA, local item dependence is composed of local RA dependence and local RT dependence. The two components are usually caused by the same common stimulus and emerge as pairs. Thus, the violation of local item independence in the joint models is called paired local item dependence. To address the issue of paired local item dependence while applying the joint cognitive diagnosis models (CDMs, this study proposed a joint testlet cognitive diagnosis modeling approach. The proposed approach is an extension of Zhan et al. (2017 and it incorporates two types of random testlet effect parameters (one for RA and the other for RTs to account for paired local item dependence. The model parameters were estimated using the full Bayesian Markov chain Monte Carlo (MCMC method. The 2015 PISA computer-based mathematics data were analyzed to demonstrate the application of the proposed model. Further, a brief simulation study was conducted to demonstrate the acceptable parameter recovery and the consequence of ignoring paired local item dependence.

Biological Bases for Radiation Adaptive Responses in the Lung

Energy Technology Data Exchange (ETDEWEB)

Scott, Bobby R. [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Lin, Yong [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Wilder, Julie [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States); Belinsky, Steven [Lovelace Biomedical and Environmental Research Inst., Albuquerque, NM (United States)

2015-03-01

Our main research objective was to determine the biological bases for low-dose, radiation-induced adaptive responses in the lung, and use the knowledge gained to produce an improved risk model for radiation-induced lung cancer that accounts for activated natural protection, genetic influences, and the role of epigenetic regulation (epiregulation). Currently, low-dose radiation risk assessment is based on the linear-no-threshold hypothesis, which now is known to be unsupported by a large volume of data.

Demand response modeling considering Interruptible/Curtailable loads and capacity market programs

International Nuclear Information System (INIS)

Aalami, H.A.; Moghaddam, M. Parsa; Yousefi, G.R.

2010-01-01

Recently, a massive focus has been made on demand response (DR) programs, aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, demand response programs are divided into two main categories namely, incentive-based programs and time-based programs. The focus of this paper is on Interruptible/Curtailable service (I/C) and capacity market programs (CAP), which are incentive-based demand response programs including penalties for customers in case of no responding to load reduction. First, by using the concept of price elasticity of demand and customer benefit function, economic model of above mentioned programs is developed. The proposed model helps the independent system operator (ISO) to identify and employ relevant DR program which both improves the characteristics of the load curve and also be welcome by customers. To evaluate the performance of the model, simulation study has been conducted using the load curve of the peak day of the Iranian power system grid in 2007. In the numerical study section, the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption are shown. In addition, by using strategy success indices the results of simulation studies for different scenarios are analyzed and investigated for determination of the scenarios priority. (author)

Corporate Social Responsibility And Islamic Business Organizations: A Proposed Model

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Rusnah Muhamad

2008-01-01

Full Text Available The issue of corporate social responsibility (CSR has been of growing concern among business communities in recent years. Various corporate leaders maintain that business is considered to contribute fully to the society if it is effi cient, profi table and socially responsible. Islam is considered as addin (a way of life, thus, providing comprehensive guidelines in every aspects of the believers’ life. It is the aim of this paper to propose an Islamic model of corporate social responsibility based on human relationships with the God (hablun min’Allah; with other fellow human being (hablun min’an-nas and with the environment.Keywords : Corporate Social Responsibility, Islamic Business Organization

Single toxin dose-response models revisited

Energy Technology Data Exchange (ETDEWEB)

Demidenko, Eugene, E-mail: eugened@dartmouth.edu [Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH03756 (United States); Glaholt, SP, E-mail: sglaholt@indiana.edu [Indiana University, School of Public & Environmental Affairs, Bloomington, IN47405 (United States); Department of Biological Sciences, Dartmouth College, Hanover, NH03755 (United States); Kyker-Snowman, E, E-mail: ek2002@wildcats.unh.edu [Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH03824 (United States); Shaw, JR, E-mail: joeshaw@indiana.edu [Indiana University, School of Public & Environmental Affairs, Bloomington, IN47405 (United States); Chen, CY, E-mail: Celia.Y.Chen@dartmouth.edu [Department of Biological Sciences, Dartmouth College, Hanover, NH03755 (United States)

2017-01-01

The goal of this paper is to offer a rigorous analysis of the sigmoid shape single toxin dose-response relationship. The toxin efficacy function is introduced and four special points, including maximum toxin efficacy and inflection points, on the dose-response curve are defined. The special points define three phases of the toxin effect on mortality: (1) toxin concentrations smaller than the first inflection point or (2) larger then the second inflection point imply low mortality rate, and (3) concentrations between the first and the second inflection points imply high mortality rate. Probabilistic interpretation and mathematical analysis for each of the four models, Hill, logit, probit, and Weibull is provided. Two general model extensions are introduced: (1) the multi-target hit model that accounts for the existence of several vital receptors affected by the toxin, and (2) model with a nonzero mortality at zero concentration to account for natural mortality. Special attention is given to statistical estimation in the framework of the generalized linear model with the binomial dependent variable as the mortality count in each experiment, contrary to the widespread nonlinear regression treating the mortality rate as continuous variable. The models are illustrated using standard EPA Daphnia acute (48 h) toxicity tests with mortality as a function of NiCl or CuSO{sub 4} toxin. - Highlights: • The paper offers a rigorous study of a sigmoid dose-response relationship. • The concentration with highest mortality rate is rigorously defined. • A table with four special points for five morality curves is presented. • Two new sigmoid dose-response models have been introduced. • The generalized linear model is advocated for estimation of sigmoid dose-response relationship.

A comparison of dose-response models for death from hematological depression

International Nuclear Information System (INIS)

Morris, M.D.; Jones, T.D.

1987-01-01

Many radiation-induced lethality experiments that have been published for various mammalian species have been compiled into a database suitable to study interspecific variability of radiosensitivity, dose-rate dependence of sensitivity, dose-response behavior within each experiment, etc. The data compiled were restricted to continuous and nearly continuous exposures to photon radiations having source energies above 100 keV. Also, photon source energy, exposure geometry, and body weight considerations were used to select studies where the dose to hematopoietic marrow was nearly uniform, i.e., < +- 20%. The data base reflects 13 mammalian test species ranging from mouse to cattle. Some 211 studies were compiled but only 105 were documented in adequate detail to be useful in development and evaluation of dose-response models of interest to practical human exposures. Of the 105 studies, 70 were for various rodent species, and 35 were for nonrodent groups ranging from standard laboratory primates (body weight ∼5 kg) to cattle (body weight 375 kg). This paper considers seven different dose-response models which are tested for validity against those 105 studies. The dose-response models included: a right-skewed extreme value, a left-skewed extreme value model, log-logistic, log-probit, logistic, probit, and Weibull models. In general, the log transformed models did not improve model performance and the extreme value models did not seem consistent with the preponderance of the data. Overall, the probit and the logistic models seemed preferable over the Weibull model. 30 refs., 8 tabs

A simple non-linear model of immune response

International Nuclear Information System (INIS)

Gutnikov, Sergei; Melnikov, Yuri

2003-01-01

It is still unknown why the adaptive immune response in the natural immune system based on clonal proliferation of lymphocytes requires interaction of at least two different cell types with the same antigen. We present a simple mathematical model illustrating that the system with separate types of cells for antigen recognition and patogen destruction provides more robust adaptive immunity than the system where just one cell type is responsible for both recognition and destruction. The model is over-simplified as we did not have an intention of describing the natural immune system. However, our model provides a tool for testing the proposed approach through qualitative analysis of the immune system dynamics in order to construct more sophisticated models of the immune systems that exist in the living nature. It also opens a possibility to explore specific features of highly non-linear dynamics in nature-inspired computational paradigms like artificial immune systems and immunocomputing . We expect this paper to be of interest not only for mathematicians but also for biologists; therefore we made effort to explain mathematics in sufficient detail for readers without professional mathematical background

A Box-Cox normal model for response times.

Science.gov (United States)

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

2009-11-01

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

Modeling and prioritizing demand response programs in power markets

International Nuclear Information System (INIS)

Aalami, H.A.; Moghaddam, M. Parsa; Yousefi, G.R.

2010-01-01

One of the responsibilities of power market regulator is setting rules for selecting and prioritizing demand response (DR) programs. There are many different alternatives of DR programs for improving load profile characteristics and achieving customers' satisfaction. Regulator should find the optimal solution which reflects the perspectives of each DR stakeholder. Multi Attribute Decision Making (MADM) is a proper method for handling such optimization problems. In this paper, an extended responsive load economic model is developed. The model is based on price elasticity and customer benefit function. Prioritizing of DR programs can be realized by means of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Considerations of ISO/utility/customer regarding the weighting of attributes are encountered by entropy method. An Analytical Hierarchy Process (AHP) is used for selecting the most effective DR program. Numerical studies are conducted on the load curve of the Iranian power grid in 2007. (author)

A Model-Based Approach for Separating the Cochlear Microphonic from the Auditory Nerve Neurophonic in the Ongoing Response Using Electrocochleography

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Tatyana E. Fontenot

2017-10-01

Full Text Available Electrocochleography (ECochG is a potential clinically valuable technique for predicting speech perception outcomes in cochlear implant (CI recipients, among other uses. Current analysis is limited by an inability to quantify hair cell and neural contributions which are mixed in the ongoing part of the response to low frequency tones. Here, we used a model based on source properties to account for recorded waveform shapes and to separate the combined signal into its components. The model for the cochlear microphonic (CM was a sinusoid with parameters for independent saturation of the peaks and the troughs of the responses. The model for the auditory nerve neurophonic (ANN was the convolution of a unit potential and population cycle histogram with a parameter for spread of excitation. Phases of the ANN and CM were additional parameters. The average cycle from the ongoing response was the input, and adaptive fitting identified CM and ANN parameters that best reproduced the waveform shape. Test datasets were responses recorded from the round windows of CI recipients, from the round window of gerbils before and after application of neurotoxins, and with simulated signals where each parameter could be manipulated in isolation. Waveforms recorded from 284 CI recipients had a variety of morphologies that the model fit with an average r2 of 0.97 ± 0.058 (standard deviation. With simulated signals, small systematic differences between outputs and inputs were seen with some variable combinations, but in general there were limited interactions among the parameters. In gerbils, the CM reported was relatively unaffected by the neurotoxins. In contrast, the ANN was strongly reduced and the reduction was limited to frequencies of 1,000 Hz and lower, consistent with the range of strong neural phase-locking. Across human CI subjects, the ANN contribution was variable, ranging from nearly none to larger than the CM. Development of this model could provide a

Introduction/overview: gender-based differences in pharmacologic and toxicologic responses.

Science.gov (United States)

Christian, M S

2001-01-01

Gender may be the most important factor in mammalian development and response to exogenous agents. From believing sex-related differences required sheltering women to protect their reproductive capacity (Victorians thought exercise, education, train travel, and certain music neuro- and reprotoxic to females) to legislating a status of essential equality of the sexes may have increased women's health issues. Men and women often respond differently to drugs. Inclusion of women in phase I/II clinical trials is insufficient to identify gender-based differences in response; rather, animal models should be the basis for predicting gender-based differences in pharmacologic and toxicologic effects. Unfortunately, current animal models do not consistently demonstrate such differences. Use of commonly used species (e.g., rats and dogs) does not necessarily result in relevant evaluation of an agent in a species at appropriate development (age), physiological state, anatomy, metabolism, or kinetics for estimation of human risks. The need to test agents in relevant animal models and advances in metabolic, pharmacokinetic, and pharmacodynamic capabilities challenge us to improve methods by using the most relevant models for estimating human risk. We need to be concerned about gender-related differences and the dynamics of gender-based growth and development over the entire life cycle. We must also consider potential interactions of dietary supplements and other exogenous agents that can act as drugs or modulate the potential effects of drugs differently in men, women, and developing children of both sexes. To this end, the health benefits of genistein and the effects of this dietary agent in a multigeneration study in rats will be described. It is envisioned that this symposium will assist in re-recognition of the importance of gender-related differences in use and response to pharmaceuticals and result in optimization of nonclinical testing procedures to identify benefits and

A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence

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Edlund Stefan

2012-09-01

Full Text Available Abstract Background The role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation. Methods This study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data. The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation’s Spatiotemporal Epidemiological Modeller (STEM. Results Although the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166–2

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

Science.gov (United States)

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

2015-01-01

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

A rate equation model of stomatal responses to vapour pressure deficit and drought

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Shanahan ST

2002-08-01

Full Text Available Abstract Background Stomata respond to vapour pressure deficit (D – when D increases, stomata begin to close. Closure is the result of a decline in guard cell turgor, but the link between D and turgor is poorly understood. We describe a model for stomatal responses to increasing D based upon cellular water relations. The model also incorporates impacts of increasing levels of water stress upon stomatal responses to increasing D. Results The model successfully mimics the three phases of stomatal responses to D and also reproduces the impact of increasing plant water deficit upon stomatal responses to increasing D. As water stress developed, stomata regulated transpiration at ever decreasing values of D. Thus, stomatal sensitivity to D increased with increasing water stress. Predictions from the model concerning the impact of changes in cuticular transpiration upon stomatal responses to increasing D are shown to conform to experimental data. Sensitivity analyses of stomatal responses to various parameters of the model show that leaf thickness, the fraction of leaf volume that is air-space, and the fraction of mesophyll cell wall in contact with air have little impact upon behaviour of the model. In contrast, changes in cuticular conductance and membrane hydraulic conductivity have significant impacts upon model behaviour. Conclusion Cuticular transpiration is an important feature of stomatal responses to D and is the cause of the 3 phase response to D. Feed-forward behaviour of stomata does not explain stomatal responses to D as feedback, involving water loss from guard cells, can explain these responses.

Peak-Broadening of Floor Response Spectra for Base Isolated Nuclear Structures

International Nuclear Information System (INIS)

Ju, Heekun; Choun, Young-Sun; Kim, Min-Kyu

2015-01-01

In this paper, uncertainties in developing FRS are explained first. Then FDRS of a fixed structure is computed using a conventional method as an example. Lastly FRS of a base-isolated structure is computed and suitability of current peak-broadening method is examined. Uncertainties in the material property of structure influence FRS of fixed structures significantly, but their effect on FRS of base-isolated structures is negligible. Nuclear structures should be designed to ensure the safety of equipment and components mounted on their floors. However, coupled analysis of a structure and components is complex, so equipment is separately analyzed using floor response spectra (FRS). FRS calculated from dynamic analysis of structural model should be modified to create floor design response spectra (FDRS), the input for seismic design of equipment. For nuclear structures, smoothing and broadening peaks of FRS is required to account for uncertainties owing to material properties of structures, soil, modeling techniques, and others. The peak broadening method proposed for fixed based structures may not be appropriate for base-isolated structures because of additional uncertainties in the property of isolation bearings. For base-isolated structures, mechanical property of isolator plays a dominant role on the change of FRS. As base-isolated nuclear plants should meet the ASCE provisions, uncertainty in the isolation system would be around 10%. For the base isolated 3-storied beam model with 2.5-sec isolation period, 6.9% of broadening ratio was enough for development of FDRS at the required variation condition. Also for the models with various isolation periods, less than 10% of broadening ratio was sufficient

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

Science.gov (United States)

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

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Erick Olivares

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

Multivariate statistical modelling based on generalized linear models

CERN Document Server

Fahrmeir, Ludwig

1994-01-01

This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...

Novel biomarker-based model for the prediction of sorafenib response and overall survival in advanced hepatocellular carcinoma: a prospective cohort study.

Science.gov (United States)

Kim, Hwi Young; Lee, Dong Hyeon; Lee, Jeong-Hoon; Cho, Young Youn; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan

2018-03-20

Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P functions on tumor response (c-index, 0.825) and 12-month survival (AUC, 0.803), and good calibration functions (all P > 0.05 between expected and observed values). This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.

Decisions on Energy Demand Response Option Contracts in Smart Grids Based on Activity-Based Costing and Stochastic Programming

Directory of Open Access Journals (Sweden)

Alfred J. Hildreth

2013-01-01

Full Text Available Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.

The Mutyh base excision repair gene influences the inflammatory response in a mouse model of ulcerative colitis.

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Ida Casorelli

Full Text Available BACKGROUND: The Mutyh DNA glycosylase is involved in the repair of oxidized DNA bases. Mutations in the human MUTYH gene are responsible for colorectal cancer in familial adenomatous polyposis. Since defective DNA repair genes might contribute to the increased cancer risk associated with inflammatory bowel diseases, we compared the inflammatory response of wild-type and Mutyh(-/- mice to oxidative stress. METHODOLOGY/PRINCIPAL FINDINGS: The severity of colitis, changes in expression of genes involved in DNA repair and inflammation, DNA 8-oxoguanine levels and microsatellite instability were analysed in colon of mice treated with dextran sulfate sodium (DSS. The Mutyh(-/- phenotype was associated with a significant accumulation of 8-oxoguanine in colon DNA of treated mice. A single DSS cycle induced severe acute ulcerative colitis in wild-type mice, whereas lesions were modest in Mutyh(-/- mice, and this was associated with moderate variations in the expression of several cytokines. Eight DSS cycles caused chronic colitis in both wild-type and Mutyh(-/- mice. Lymphoid hyperplasia and a significant reduction in Foxp3(+ regulatory T cells were observed only in Mutyh(-/- mice. CONCLUSIONS: The findings indicate that, in this model of ulcerative colitis, Mutyh plays a major role in maintaining intestinal integrity by affecting the inflammatory response.

SLS Navigation Model-Based Design Approach

Science.gov (United States)

Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

2018-01-01

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

Study on vertical seismic response model of BWR-type reactor building

International Nuclear Information System (INIS)

Konno, T.; Motohashi, S.; Izumi, M.; Iizuka, S.

1993-01-01

A study on advanced seismic design for LWR has been carried out by the Nuclear Power Engineering Corporation (NUPEC), under the sponsorship of the Ministry of International Trade and Industry (MITI) of Japan. As a part of the study, it has been investigated to construct an accurate analytical model of reactor buildings for a seismic response analysis, which can reasonably represent dynamic characteristics of the building. In Japan, vibration models of reactor buildings for horizontal ground motion have been studied and examined through many simulation analyses for forced vibration tests and earthquake observations of actual buildings. And now it is possible to establish a reliable horizontal vibration model on the basis of multi-lumped mass and spring model. However, vertical vibration models have not been so much studied as horizontal models, due to less observed data for vertical motions. In this paper, the vertical seismic response models of a BWR-type reactor building including soil-structure interaction effect are numerically studied, by comparing the dynamic characteristics of (1) three dimensional finite element model, (2) multi-stick lumped mass model with a flexible base-mat, (3) multi-stick lumped mass model with a rigid base-mat and (4) single-stick lumped mass model. In particular, the BWR-type reactor building has the long span truss roof which is considered to be one of the critical members to vertical excitation. The modelings of the roof trusses are also studied

Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System

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Bo Lin

2017-10-01

Full Text Available This paper investigates how to develop a learning-based demand response approach for electric water heater in a smart home that can minimize the energy cost of the water heater while meeting the comfort requirements of energy consumers. First, a learning-based, data-driven model of an electric water heater is developed by using a nonlinear autoregressive network with external input (NARX using neural network. The model is updated daily so that it can more accurately capture the actual thermal dynamic characteristics of the water heater especially in real-life conditions. Then, an optimization problem, based on the NARX water heater model, is formulated to optimize energy management of the water heater in a day-ahead, dynamic electricity price framework. A genetic algorithm is proposed in order to solve the optimization problem more efficiently. MATLAB (R2016a is used to evaluate the proposed learning-based demand response approach through a computational experiment strategy. The proposed approach is compared with conventional method for operation of an electric water heater. Cost saving and benefits of the proposed water heater energy management strategy are explored.

An Extended System Frequency Response Model Considering Wind Power Participation in Frequency Regulation

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Yi Tang

2017-11-01

Full Text Available With increasing penetration of wind power into the power system, wind power participation in frequency regulation is regarded as a beneficial strategy to improve the dynamic frequency response characteristics of power systems. The traditional power system frequency response (SFR model, which only includes synchronous generators, is no longer suitable for power systems with high penetrated wind power. An extended SFR model, based on the reduced-order model of wind turbine generator (WTG and the traditional SFR model, is presented in this paper. In the extended SFR model, the reduced-order model of WTG with combined frequency control is deduced by employing small signal analysis theory. Afterwards, the stability analysis of a closed-loop control system for the extended SFR model is carried out. Time-domain simulations using a test system are performed to validate the effectiveness of the extended SFR model; this model can provide a simpler, clearer and faster way to analyze the dynamic frequency response characteristic for a high-wind integrated power systems. The impact of additional frequency control parameters and wind speed disturbances on the system dynamic frequency response characteristics are investigated.

Frequency response function (FRF) based updating of a laser spot welded structure

Science.gov (United States)

Zin, M. S. Mohd; Rani, M. N. Abdul; Yunus, M. A.; Sani, M. S. M.; Wan Iskandar Mirza, W. I. I.; Mat Isa, A. A.

2018-04-01

The objective of this paper is to present frequency response function (FRF) based updating as a method for matching the finite element (FE) model of a laser spot welded structure with a physical test structure. The FE model of the welded structure was developed using CQUAD4 and CWELD element connectors, and NASTRAN was used to calculate the natural frequencies, mode shapes and FRF. Minimization of the discrepancies between the finite element and experimental FRFs was carried out using the exceptional numerical capability of NASTRAN Sol 200. The experimental work was performed under free-free boundary conditions using LMS SCADAS. Avast improvement in the finite element FRF was achieved using the frequency response function (FRF) based updating with two different objective functions proposed.

Reliability Evaluation of Bridges Based on Nonprobabilistic Response Surface Limit Method

OpenAIRE

Chen, Xuyong; Chen, Qian; Bian, Xiaoya; Fan, Jianping

2017-01-01

Due to many uncertainties in nonprobabilistic reliability assessment of bridges, the limit state function is generally unknown. The traditional nonprobabilistic response surface method is a lengthy and oscillating iteration process and leads to difficultly solving the nonprobabilistic reliability index. This article proposes a nonprobabilistic response surface limit method based on the interval model. The intention of this method is to solve the upper and lower limits of the nonprobabilistic ...

Modeling for mechanical response of CICC by hierarchical approach and ABAQUS simulation

Energy Technology Data Exchange (ETDEWEB)

Li, Y.X.; Wang, X.; Gao, Y.W., E-mail: ywgao@lzu.edu.cn; Zhou, Y.H.

2013-11-15

Highlights: • We develop an analytical model based on the hierarchical approach of classical wire rope theory. • The numerical model is set up through ABAQUS to verify and enhance the theoretical model. • We calculate two concerned mechanical response: global displacement–load curve and local axial strain distribution. • Elastic–plasticity is the main character in loading curve, and the friction between adjacent strands plays a significant role in the distribution map. -- Abstract: An unexpected degradation frequently occurs in superconducting cable (CICC) due to the mechanical response (deformation) when suffering from electromagnetic load and thermal load during operation. Because of the cable's hierarchical twisted configuration, it is difficult to quantitatively model the mechanical response. In addition, the local mechanical characteristics such as strain distribution could be hardly monitored via experimental method. To address this issue, we develop an analytical model based on the hierarchical approach of classical wire rope theory. This approach follows the algorithm advancing successively from n + 1 stage (e.g. 3 × 3 × 5 subcable) to n stage (e.g. 3 × 3 subcable). There are no complicated numerical procedures required in this model. Meanwhile, the numerical model is set up through ABAQUS to verify and enhance the theoretical model. Subsequently, we calculate two concerned mechanical responses: global displacement–load curve and local axial strain distribution. We find that in the global displacement–load curve, the elastic–plasticity is the main character, and the higher-level cable shows enhanced nonlinear characteristics. As for the local distribution, the friction among adjacent strands plays a significant role in this map. The magnitude of friction strongly influences the regularity of the distribution at different twisted stages. More detailed results are presented in this paper.

Modeling for mechanical response of CICC by hierarchical approach and ABAQUS simulation

International Nuclear Information System (INIS)

Li, Y.X.; Wang, X.; Gao, Y.W.; Zhou, Y.H.

2013-01-01

Highlights: • We develop an analytical model based on the hierarchical approach of classical wire rope theory. • The numerical model is set up through ABAQUS to verify and enhance the theoretical model. • We calculate two concerned mechanical response: global displacement–load curve and local axial strain distribution. • Elastic–plasticity is the main character in loading curve, and the friction between adjacent strands plays a significant role in the distribution map. -- Abstract: An unexpected degradation frequently occurs in superconducting cable (CICC) due to the mechanical response (deformation) when suffering from electromagnetic load and thermal load during operation. Because of the cable's hierarchical twisted configuration, it is difficult to quantitatively model the mechanical response. In addition, the local mechanical characteristics such as strain distribution could be hardly monitored via experimental method. To address this issue, we develop an analytical model based on the hierarchical approach of classical wire rope theory. This approach follows the algorithm advancing successively from n + 1 stage (e.g. 3 × 3 × 5 subcable) to n stage (e.g. 3 × 3 subcable). There are no complicated numerical procedures required in this model. Meanwhile, the numerical model is set up through ABAQUS to verify and enhance the theoretical model. Subsequently, we calculate two concerned mechanical responses: global displacement–load curve and local axial strain distribution. We find that in the global displacement–load curve, the elastic–plasticity is the main character, and the higher-level cable shows enhanced nonlinear characteristics. As for the local distribution, the friction among adjacent strands plays a significant role in this map. The magnitude of friction strongly influences the regularity of the distribution at different twisted stages. More detailed results are presented in this paper

One-dimensional map-based neuron model: A logistic modification

International Nuclear Information System (INIS)

Mesbah, Samineh; Moghtadaei, Motahareh; Hashemi Golpayegani, Mohammad Reza; Towhidkhah, Farzad

2014-01-01

A one-dimensional map is proposed for modeling some of the neuronal activities, including different spiking and bursting behaviors. The model is obtained by applying some modifications on the well-known Logistic map and is named the Modified and Confined Logistic (MCL) model. Map-based neuron models are known as phenomenological models and recently, they are widely applied in modeling tasks due to their computational efficacy. Most of discrete map-based models involve two variables representing the slow-fast prototype. There are also some one-dimensional maps, which can replicate some of the neuronal activities. However, the existence of four bifurcation parameters in the MCL model gives rise to reproduction of spiking behavior with control over the frequency of the spikes, and imitation of chaotic and regular bursting responses concurrently. It is also shown that the proposed model has the potential to reproduce more realistic bursting activity by adding a second variable. Moreover the MCL model is able to replicate considerable number of experimentally observed neuronal responses introduced in Izhikevich (2004) [23]. Some analytical and numerical analyses of the MCL model dynamics are presented to explain the emersion of complex dynamics from this one-dimensional map

WE-AB-202-11: Radiobiological Modeling of Tumor Response During Radiotherapy Based On Pre-Treatment Dynamic PET Imaging Data

Energy Technology Data Exchange (ETDEWEB)

Crispin-Ortuzar, M; Grkovski, M; Beattie, B; Lee, N; Riaz, N; Humm, J; Jeong, J; Fontanella, A; Deasy, J [Memorial Sloan Kettering Cancer Center, New York, NY (United States)

2016-06-15

Purpose: To evaluate the ability of a multiscale radiobiological model of tumor response to predict mid-treatment hypoxia images, based on pretreatment imaging of perfusion and hypoxia with [18-F]FMISO dynamic PET and glucose metabolism with [18-F]FDG PET. Methods: A mechanistic tumor control probability (TCP) radiobiological model describing the interplay between tumor cell proliferation and hypoxia (Jeong et al., PMB 2013) was extended to account for intra-tumor nutrient heterogeneity, dynamic cell migration due to nutrient gradients, and stromal cells. This extended model was tested on 10 head and neck cancer patients treated with chemoradiotherapy, randomly drawn from a larger MSKCC protocol involving baseline and mid-therapy dynamic PET scans. For each voxel, initial fractions of proliferative and hypoxic tumor cells were obtained by finding an approximate solution to a system of linear equations relating cell fractions to voxel-level FDG uptake, perfusion (FMISO K{sub 1}) and hypoxia (FMISO k{sub 3}). The TCP model then predicted their evolution over time up until the mid treatment scan. Finally, the linear model was reapplied to predict each lesion’s median hypoxia level (k{sub 3}[med,sim]) which in turn was compared to the FMISO k{sub 3}[med] measured at mid-therapy. Results: The average k3[med] of the tumors in pre-treatment scans was 0.0035 min{sup −1}, with an inter-tumor standard deviation of σ[pre]=0.0034 min{sup −1}. The initial simulated k{sub 3}[med,sim] of each tumor agreed with the corresponding measurements within 0.1σ[pre]. In 7 out of 10 lesions, the mid-treatment k{sub 3}[med,sim] prediction agreed with the data within 0.3σ[pre]. The remaining cases corresponded to the most extreme relative changes in k{sub 3}[med]. Conclusion: This work presents a method to personalize the prediction of a TCP model using pre-treatment kinetic imaging data, and validates the modeling of radiotherapy response by predicting changes in median hypoxia

An Economic Customer-Oriented Demand Response Model in Electricity Markets

DEFF Research Database (Denmark)

Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

2018-01-01

Consumer choice theory is a branch of microeconomics. This theory relates to adjusting consumption expenditures and consumer demand curve. Consumer choice science is trying to realize the buyer's decision-making process. This science studies customer characteristics, such as behavioral criteria......, to understand the consumer’s need. The concept of price elasticity of demand (PED) has also been derived from this theory. In fact, the PED is the percentage of changes in the amount of demand relative to the price changes. In consumer choice theory, for each consumer according to behavioral criteria, a unique...... demand response (DR) models have been developed based on this concept, this will also be deemed as a disadvantage for them. In this paper, we propose an economic DR model based on economic theories and mathematical methods. In addition to abate the defects of price-elasticity based DR models...

A Multiagent Based Model for Tactical Planning

Science.gov (United States)

2002-10-01

Pub. Co. 1985. [10] Castillo, J.M. Aproximación mediante procedimientos de Inteligencia Artificial al planeamiento táctico. Doctoral Thesis...been developed under the same conceptual model and using similar Artificial Intelligence Tools. We use four different stimulus/response agents in...The conceptual model is built on base of the Agents theory. To implement the different agents we have used Artificial Intelligence techniques such

Randomized Item Response Theory Models

NARCIS (Netherlands)

Fox, Gerardus J.A.

2005-01-01

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

Towards longitudinal activity-based models of travel demand

NARCIS (Netherlands)

Arentze, T.A.; Timmermans, H.J.P.; Lo, H.P.; Leung, Stephen C.H.; Tan, Susanna M.L.

2008-01-01

Existing activity-based models of travel demand consider a day as the time unit of observation and predict activity patterns of inhviduals for a typical or average day. In this study we argue that the use of a time span of one day severely limits the ability of the models to predict responsive

Is harm reduction profitable? An analytical framework for corporate social responsibility based on an epidemic model of addictive consumption.

Science.gov (United States)

Massin, Sophie

2012-06-01

This article aims to help resolve the apparent paradox of producers of addictive goods who claim to be socially responsible while marketing a product clearly identified as harmful. It advances that reputation effects are crucial in this issue and that determining whether harm reduction practices are costly or profitable for the producers can help to assess the sincerity of their discourse. An analytical framework based on an epidemic model of addictive consumption that includes a deterrent effect of heavy use on initiation is developed. This framework enables us to establish a clear distinction between a simple responsible discourse and genuine harm reduction practices and, among harm reduction practices, between use reduction practices and micro harm reduction practices. Using simulations based on tobacco sales in France from 1950 to 2008, we explore the impact of three corresponding types of actions: communication on damage, restraining selling practices and development of safer products on total sales and on the social cost. We notably find that restraining selling practices toward light users, that is, preventing light users from escalating to heavy use, can be profitable for the producer, especially at early stages of the epidemic, but that such practices also contribute to increase the social cost. These results suggest that the existence of a deterrent effect of heavy use on the initiation of the consumption of an addictive good can shed new light on important issues, such as the motivations for corporate social responsibility and the definition of responsible actions in the particular case of harm reduction. Copyright © 2012 Elsevier Ltd. All rights reserved.

Model for Managing Corporate Social Responsibility

Directory of Open Access Journals (Sweden)

Tamara Vlastelica Bakić

2015-05-01

Full Text Available As a crossfuncional process in the organization, effective management of corporate social responsibility requires a definition of strategies, programs and an action plan that structures this process from its initiation to the measurement of end effects. Academic literature on the topic of corporate social responsibility is mainly focused on the exploration of the business case for the concept, i.e., the determination of effects of social responsibility on individual aspects of the business. Scientific research so far has shown not to have been committed to formalizing management concept in this domain to a satisfactory extent; it is for this reason that this paper attempts to present one model for managing corporate social responsibility. The model represents a contribution to the theory and business practice of corporate social responsibility, as it offers a strategic framework for systematic planning, implementation and evaluation of socially responsible activities and programs.

Adopting a Models-Based Approach to Teaching Physical Education

Science.gov (United States)

Casey, Ashley; MacPhail, Ann

2018-01-01

Background: The popularised notion of models-based practice (MBP) is one that focuses on the delivery of a model, e.g. Cooperative Learning, Sport Education, Teaching Personal and Social Responsibility, Teaching Games for Understanding. Indeed, while an abundance of research studies have examined the delivery of a single model and some have…

Model-Based Reconstructive Elasticity Imaging Using Ultrasound

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Salavat R. Aglyamov

2007-01-01

Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

Predictive computational modeling of the mucosal immune responses during Helicobacter pylori infection.

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Adria Carbo

Full Text Available T helper (Th cells play a major role in the immune response and pathology at the gastric mucosa during Helicobacter pylori infection. There is a limited mechanistic understanding regarding the contributions of CD4+ T cell subsets to gastritis development during H. pylori colonization. We used two computational approaches: ordinary differential equation (ODE-based and agent-based modeling (ABM to study the mechanisms underlying cellular immune responses to H. pylori and how CD4+ T cell subsets influenced initiation, progression and outcome of disease. To calibrate the model, in vivo experimentation was performed by infecting C57BL/6 mice intragastrically with H. pylori and assaying immune cell subsets in the stomach and gastric lymph nodes (GLN on days 0, 7, 14, 30 and 60 post-infection. Our computational model reproduced the dynamics of effector and regulatory pathways in the gastric lamina propria (LP in silico. Simulation results show the induction of a Th17 response and a dominant Th1 response, together with a regulatory response characterized by high levels of mucosal Treg cells. We also investigated the potential role of peroxisome proliferator-activated receptor γ (PPARγ activation on the modulation of host responses to H. pylori by using loss-of-function approaches. Specifically, in silico results showed a predominance of Th1 and Th17 cells in the stomach of the cell-specific PPARγ knockout system when compared to the wild-type simulation. Spatio-temporal, object-oriented ABM approaches suggested similar dynamics in induction of host responses showing analogous T cell distributions to ODE modeling and facilitated tracking lesion formation. In addition, sensitivity analysis predicted a crucial contribution of Th1 and Th17 effector responses as mediators of histopathological changes in the gastric mucosa during chronic stages of infection, which were experimentally validated in mice. These integrated immunoinformatics approaches

Modeling listeners' emotional response to music.

Science.gov (United States)

Eerola, Tuomas

2012-10-01

An overview of the computational prediction of emotional responses to music is presented. Communication of emotions by music has received a great deal of attention during the last years and a large number of empirical studies have described the role of individual features (tempo, mode, articulation, timbre) in predicting the emotions suggested or invoked by the music. However, unlike the present work, relatively few studies have attempted to model continua of expressed emotions using a variety of musical features from audio-based representations in a correlation design. The construction of the computational model is divided into four separate phases, with a different focus for evaluation. These phases include the theoretical selection of relevant features, empirical assessment of feature validity, actual feature selection, and overall evaluation of the model. Existing research on music and emotions and extraction of musical features is reviewed in terms of these criteria. Examples drawn from recent studies of emotions within the context of film soundtracks are used to demonstrate each phase in the construction of the model. These models are able to explain the dominant part of the listeners' self-reports of the emotions expressed by music and the models show potential to generalize over different genres within Western music. Possible applications of the computational models of emotions are discussed. Copyright © 2012 Cognitive Science Society, Inc.

Parameter Estimation in Probit Model for Multivariate Multinomial Response Using SMLE

Directory of Open Access Journals (Sweden)

Jaka Nugraha

2012-02-01

Full Text Available In  the  research  field  of  transportation,  market  research and  politics,  often involving  the  response  of  the multinomial multivariate  observations.  In  this  paper, we discused  a  modeling  of  multivariate  multinomial  responses  using  probit  model.  The estimated  parameters  were  calculated  using Maximum  Likelihood  Estimations  (MLE based  on  the  GHK  simulation.  method  known  as Simulated  Maximum  Likelihood Estimations (SMLE. Likelihood function on the Probit model contains probability values that must be resolved by simulation. By using  the GHK simulation algorithm,  the estimator equation has been obtained for the parameters in the model Probit  Keywords : Probit Model, Newton-Raphson Iteration,  GHK simulator, MLE, simulated log-likelihood

The transfer function model for dynamic response of wet cooling coils

International Nuclear Information System (INIS)

Yao Ye; Liu Shiqing

2008-01-01

This paper mainly concerned about the dynamic response model of wet cooling coils that is developed by the Laplace transform method. The theoretic equations are firstly established based on the theory of energy conservation. Then, the transfer functions on the transient responses of wet cooling coils have been deduced using the method of Laplace transform. The transfer functions reveal the dynamic relationships between the inlet variables and the outlet ones of the cooling coils. Partial-fraction method and Newton-Raphson method are both used in the inversion of the transfer functions from the s-domain to τ-domain. To make the dynamic model of wet cooling coils more adaptive, RBFNN method is employed to determine the coefficients of heat and mass transfer. Experiments have been done and manifested that the coefficients of heat and mass transfer by RBFNN will be of great value to the validity of the transient response model of wet cooling coils in this study

Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry

Science.gov (United States)

Kan, Andrey; Pavlyshyn, Damian; Markham, John F.; Dowling, Mark R.; Heinzel, Susanne; Zhou, Jie H. S.; Marchingo, Julia M.; Hodgkin, Philip D.

2016-01-01

Adaptive immune responses are complex dynamic processes whereby B and T cells undergo division and differentiation triggered by pathogenic stimuli. Deregulation of the response can lead to severe consequences for the host organism ranging from immune deficiencies to autoimmunity. Tracking cell division and differentiation by flow cytometry using fluorescent probes is a major method for measuring progression of lymphocyte responses, both in vitro and in vivo. In turn, mathematical modeling of cell numbers derived from such measurements has led to significant biological discoveries, and plays an increasingly important role in lymphocyte research. Fitting an appropriate parameterized model to such data is the goal of these studies but significant challenges are presented by the variability in measurements. This variation results from the sum of experimental noise and intrinsic probabilistic differences in cells and is difficult to characterize analytically. Current model fitting methods adopt different simplifying assumptions to describe the distribution of such measurements and these assumptions have not been tested directly. To help inform the choice and application of appropriate methods of model fitting to such data we studied the errors associated with flow cytometry measurements from a wide variety of experiments. We found that the mean and variance of the noise were related by a power law with an exponent between 1.3 and 1.8 for different datasets. This violated the assumptions inherent to commonly used least squares, linear variance scaling and log-transformation based methods. As a result of these findings we propose a new measurement model that we justify both theoretically, from the maximum entropy standpoint, and empirically using collected data. Our evaluation suggests that the new model can be reliably used for model fitting across a variety of conditions. Our work provides a foundation for modeling measurements in flow cytometry experiments thus

Atmospheric dispersion modeling: Challenges of the Fukushima Daiichi response

Energy Technology Data Exchange (ETDEWEB)

Sugiyama, Gayle [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Nasstrom, John [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pobanz, Brenda [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Foster, Kevin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Simpson, Matthew [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Vogt, Phil [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Aluzzi, Fernando [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Homann, Steve [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2012-05-01

In this research, the U.S. Department of Energy’s (DOE) National Atmospheric Release Advisory Center (NARAC) provided a wide range of predictions and analyses as part of the response to the Fukushima Daiichi Nuclear Power Plant accident including: daily Japanese weather forecasts and atmospheric transport predictions to inform planning for field monitoring operations and to provide U.S. government agencies with ongoing situational awareness of meteorological conditions; estimates of possible dose in Japan based on hypothetical U.S. Nuclear Regulatory Commission scenarios of potential radionuclide releases to support protective action planning for U.S. citizens; predictions of possible plume arrival times and dose levels at U.S. locations; and source estimation and plume model refinement based on atmospheric dispersion modeling and available monitoring data.

Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach

Science.gov (United States)

Smith, James A.

2010-01-01

The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.

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

Science.gov (United States)

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

2018-03-08

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

STRESS RESPONSE STUDIES USING ANIMAL MODELS

Science.gov (United States)

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

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

Science.gov (United States)

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

PD/PID controller tuning based on model approximations: Model reduction of some unstable and higher order nonlinear models

Directory of Open Access Journals (Sweden)

Christer Dalen

2017-10-01

Full Text Available A model reduction technique based on optimization theory is presented, where a possible higher order system/model is approximated with an unstable DIPTD model by using only step response data. The DIPTD model is used to tune PD/PID controllers for the underlying possible higher order system. Numerous examples are used to illustrate the theory, i.e. both linear and nonlinear models. The Pareto Optimal controller is used as a reference controller.

Dynamic simulation of perturbation responses in a closed-loop virtual arm model.

Science.gov (United States)

Du, Yu-Fan; He, Xin; Lan, Ning

2010-01-01

A closed-loop virtual arm (VA) model has been developed in SIMULINK environment by adding spinal reflex circuits and propriospinal neural networks to the open-loop VA model developed in early study [1]. An improved virtual muscle model (VM4.0) is used to speed up simulation and to generate more precise recruitment of muscle force at low levels of muscle activation. Time delays in the reflex loops are determined by their synaptic connections and afferent transmission back to the spinal cord. Reflex gains are properly selected so that closed-loop responses are stable. With the closed-loop VA model, we are developing an approach to evaluate system behaviors by dynamic simulation of perturbation responses. Joint stiffness is calculated based on simulated perturbation responses by a least-squares algorithm in MATLAB. This method of dynamic simulation will be essential for further evaluation of feedforward and reflex control of arm movement and position.

Corporate Responsibility under the ECSI model: An application in the hotel sector

Directory of Open Access Journals (Sweden)

María-Ángeles Revilla-Camacho

2017-01-01

Full Text Available This article deals with the study of Corporate Responsibility (CR under the European Customer Satisfaction Index (ECSI. The methodology of this empirical study, conducted among 629 customers staying at hotels in the city of Seville, is based on structural equation modeling (PLS. The results obtained demonstrate the applicability of the European model to the hotel sector, although not all the relationships from the original model have been proven. The main contributions are derived from a better understanding of the model's components, a variable not studied before having been incorporated: the importance of Corporate Responsibility (CR. Moreover, it means to contribute to the field of research on CR as, despite the growing interest in the subject, the effects of this construct are still poorly understood.

Towards a model-based cognitive neuroscience of stopping - a neuroimaging perspective.

Science.gov (United States)

Sebastian, Alexandra; Forstmann, Birte U; Matzke, Dora

2018-07-01

Our understanding of the neural correlates of response inhibition has greatly advanced over the last decade. Nevertheless the specific function of regions within this stopping network remains controversial. The traditional neuroimaging approach cannot capture many processes affecting stopping performance. Despite the shortcomings of the traditional neuroimaging approach and a great progress in mathematical and computational models of stopping, model-based cognitive neuroscience approaches in human neuroimaging studies are largely lacking. To foster model-based approaches to ultimately gain a deeper understanding of the neural signature of stopping, we outline the most prominent models of response inhibition and recent advances in the field. We highlight how a model-based approach in clinical samples has improved our understanding of altered cognitive functions in these disorders. Moreover, we show how linking evidence-accumulation models and neuroimaging data improves the identification of neural pathways involved in the stopping process and helps to delineate these from neural networks of related but distinct functions. In conclusion, adopting a model-based approach is indispensable to identifying the actual neural processes underlying stopping. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Study on the Response Characteristics of a Fiber-Optic Radiation Sensor Model Based on Cerenkov Principle

Energy Technology Data Exchange (ETDEWEB)

Han, Hwa Jeong; Kim, Beom Kyu; Park, Byung Gi [Soonchunhyang Univ., Asan (Korea, Republic of)

2016-10-15

In recent year, various fiber-optic radiation sensors using Cerenkov principle have been developed without employing any scintillators for measuring high-energy photon, electron, etc. The main advantages of the optical fibers are the remote transmission of the light signal and immunity to pressure and electromagnetic waves. Therefore, the sensors utilizing the optical fibers can be used in hazardous radiation environments, such as the high-level radiation areas of a nuclear facility. The study to be simulated a fiber-optic radiation sensor based on Cerenkov principle and to be analyzed the response characteristics of the sensor. For the aforementioned study, the GEANT simulation toolkit was used. It is able to take into all the optical properties of fibers and is found to be appropriate to realistically describe the response of fiber-optic radiation sensor. In the recently, the fiber-optic radiation sensor have been developed in nuclear industry. Because sensor can detect gamma ray in harsh nuclear environments. In this study, we analyzed response characteristics of the fiber-optic radiation sensor. We have simulated the Monte Carlo model, for detecting the Cerenkov radiation using the fiber-optic radiation sensor. And the y-axis distribution of Cerenkov photons was obtained using output file. Simulation is performed with reference to the method of the previous research, and then the simulation results exhibited a good agreement with the previous research.

A Study on the Response Characteristics of a Fiber-Optic Radiation Sensor Model Based on Cerenkov Principle

International Nuclear Information System (INIS)

Han, Hwa Jeong; Kim, Beom Kyu; Park, Byung Gi

2016-01-01

In recent year, various fiber-optic radiation sensors using Cerenkov principle have been developed without employing any scintillators for measuring high-energy photon, electron, etc. The main advantages of the optical fibers are the remote transmission of the light signal and immunity to pressure and electromagnetic waves. Therefore, the sensors utilizing the optical fibers can be used in hazardous radiation environments, such as the high-level radiation areas of a nuclear facility. The study to be simulated a fiber-optic radiation sensor based on Cerenkov principle and to be analyzed the response characteristics of the sensor. For the aforementioned study, the GEANT simulation toolkit was used. It is able to take into all the optical properties of fibers and is found to be appropriate to realistically describe the response of fiber-optic radiation sensor. In the recently, the fiber-optic radiation sensor have been developed in nuclear industry. Because sensor can detect gamma ray in harsh nuclear environments. In this study, we analyzed response characteristics of the fiber-optic radiation sensor. We have simulated the Monte Carlo model, for detecting the Cerenkov radiation using the fiber-optic radiation sensor. And the y-axis distribution of Cerenkov photons was obtained using output file. Simulation is performed with reference to the method of the previous research, and then the simulation results exhibited a good agreement with the previous research

Simulating residential demand response: Improving socio-technical assumptions in activity-based models of energy demand

OpenAIRE

McKenna, E.; Higginson, S.; Grunewald, P.; Darby, S. J.

2017-01-01

Demand response is receiving increasing interest as a new form of flexibility within low-carbon power systems. Energy models are an important tool to assess the potential capability of demand side contributions. This paper critically reviews the assumptions in current models and introduces a new conceptual framework to better facilitate such an assessment. We propose three dimensions along which change could occur, namely technology, activities and service expectations. Using this framework, ...

A computational model of inferior colliculus responses to amplitude modulated sounds in young and aged rats

Directory of Open Access Journals (Sweden)

Cal Francis Rabang

2012-11-01

Full Text Available The inferior colliculus (IC receives ascending excitatory and inhibitory inputs from multiple sources, but how these auditory inputs converge to generate IC spike patterns is poorly understood. Simulating patterns of in vivo spike train data from cellular and synaptic models creates a powerful framework to identify factors that contribute to changes in IC responses, such as those resulting in age-related loss of temporal processing. A conductance-based single neuron IC model was constructed, and its responses were compared to those observed during in vivo IC recordings in rats. IC spike patterns were evoked using amplitude-modulated (AM tone or noise carriers at 20-40 dB above threshold and were classified as low-pass, band-pass, band-reject, all-pass, or complex based on their rate modulation transfer function (rMTF tuning shape. Their temporal modulation transfer functions (tMTFs were also measured. These spike patterns provided experimental measures of rate, vector strength and firing pattern for comparison with model outputs. Patterns of excitatory and inhibitory synaptic convergence to IC neurons were based on anatomical studies and generalized input tuning for modulation frequency. Responses of modeled ascending inputs were derived from experimental data from previous studies. Adapting and sustained IC intrinsic models were created, with adaptation created via calcium-activated potassium currents. Short-term synaptic plasticity was incorporated into the model in the form of synaptic depression, which was shown to have a substantial effect on the magnitude and time course of the IC response. The most commonly observed IC response subtypes were recreated and enabled dissociation of inherited response properties from those that were generated in IC. Furthermore, the model was used to make predictions about the consequences of reduction in inhibition for age-related loss of temporal processing due to a reduction in GABA seen anatomically with

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

Science.gov (United States)

Su, Shiyang

2017-01-01

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

STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL

Directory of Open Access Journals (Sweden)

N. Nukavarapu

2016-06-01

Full Text Available The Healthcare Critical Infrastructure (HCI protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in response and recovery across all other sectors in the event of a natural or manmade disaster. However, for its continuity of operations and service delivery HCI is dependent on other interdependent Critical Infrastructures (CI such as Communications, Electric Supply, Emergency Services, Transportation Systems, and Water Supply System. During a mass casualty due to disasters such as floods, a major challenge that arises for the HCI is to respond to the crisis in a timely manner in an uncertain and variable environment. To address this issue the HCI should be disaster prepared, by fully understanding the complexities and interdependencies that exist in a hospital, emergency department or emergency response event. Modelling and simulation of a disaster scenario with these complexities would help in training and providing an opportunity for all the stakeholders to work together in a coordinated response to a disaster. The paper would present interdependencies related to HCI based on Stochastic Coloured Petri Nets (SCPN modelling and simulation approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The entire model would be integrated with Geographic information based decision support system to visualize the dynamic behaviour of the interdependency of the Healthcare and related CI network in a geographically based environment.

Stochastic Coloured Petrinet Based Healthcare Infrastructure Interdependency Model

Science.gov (United States)

Nukavarapu, Nivedita; Durbha, Surya

2016-06-01

The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in response and recovery across all other sectors in the event of a natural or manmade disaster. However, for its continuity of operations and service delivery HCI is dependent on other interdependent Critical Infrastructures (CI) such as Communications, Electric Supply, Emergency Services, Transportation Systems, and Water Supply System. During a mass casualty due to disasters such as floods, a major challenge that arises for the HCI is to respond to the crisis in a timely manner in an uncertain and variable environment. To address this issue the HCI should be disaster prepared, by fully understanding the complexities and interdependencies that exist in a hospital, emergency department or emergency response event. Modelling and simulation of a disaster scenario with these complexities would help in training and providing an opportunity for all the stakeholders to work together in a coordinated response to a disaster. The paper would present interdependencies related to HCI based on Stochastic Coloured Petri Nets (SCPN) modelling and simulation approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The entire model would be integrated with Geographic information based decision support system to visualize the dynamic behaviour of the interdependency of the Healthcare and related CI network in a geographically based environment.

Modeling the frequency response of microwave radiometers with QUCS

International Nuclear Information System (INIS)

Zonca, A; Williams, B; Rubin, I; Meinhold, P; Lubin, P; Roucaries, B; D'Arcangelo, O; Franceschet, C; Mennella, A; Bersanelli, M; Jahn, S

2010-01-01

Characterization of the frequency response of coherent radiometric receivers is a key element in estimating the flux of astrophysical emissions, since the measured signal depends on the convolution of the source spectral emission with the instrument band shape. Laboratory Radio Frequency (RF) measurements of the instrument bandpass often require complex test setups and are subject to a number of systematic effects driven by thermal issues and impedance matching, particularly if cryogenic operation is involved. In this paper we present an approach to modeling radiometers bandpasses by integrating simulations and RF measurements of individual components. This method is based on QUCS (Quasi Universal Circuit Simulator), an open-source circuit simulator, which gives the flexibility of choosing among the available devices, implementing new analytical software models or using measured S-parameters. Therefore an independent estimate of the instrument bandpass is achieved using standard individual component measurements and validated analytical simulations. In order to automate the process of preparing input data, running simulations and exporting results we developed the Python package python-qucs and released it under GNU Public License. We discuss, as working cases, bandpass response modeling of the COFE and Planck Low Frequency Instrument (LFI) radiometers and compare results obtained with QUCS and with a commercial circuit simulator software. The main purpose of bandpass modeling in COFE is to optimize component matching, while in LFI they represent the best estimation of frequency response, since end-to-end measurements were strongly affected by systematic effects.

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

Science.gov (United States)

Molenaar, Dylan; Bolsinova, Maria

2017-05-01

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

New flux based dose–response relationships for ozone for European forest tree species

International Nuclear Information System (INIS)

Büker, P.; Feng, Z.; Uddling, J.; Briolat, A.; Alonso, R.; Braun, S.; Elvira, S.; Gerosa, G.; Karlsson, P.E.; Le Thiec, D.

2015-01-01

To derive O 3 dose–response relationships (DRR) for five European forest trees species and broadleaf deciduous and needleleaf tree plant functional types (PFTs), phytotoxic O 3 doses (PODy) were related to biomass reductions. PODy was calculated using a stomatal flux model with a range of cut-off thresholds (y) indicative of varying detoxification capacities. Linear regression analysis showed that DRR for PFT and individual tree species differed in their robustness. A simplified parameterisation of the flux model was tested and showed that for most non-Mediterranean tree species, this simplified model led to similarly robust DRR as compared to a species- and climate region-specific parameterisation. Experimentally induced soil water stress was not found to substantially reduce PODy, mainly due to the short duration of soil water stress periods. This study validates the stomatal O 3 flux concept and represents a step forward in predicting O 3 damage to forests in a spatially and temporally varying climate. - Highlights: • We present new ozone flux based dose–response relationships for European trees. • The model-based study accounted for the soil water effect on stomatal flux. • Different statistically derived ozone flux thresholds were applied. • Climate region specific parameterisation often outperformed simplified parameterisation. • Findings could help redefining critical levels for ozone effects on trees. - New stomatal flux based ozone dose–response relationships for tree species are derived for the regional risk assessment of ozone effects on European forest ecosystems.

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

Energy Technology Data Exchange (ETDEWEB)

Song, Hyun-Seob; Thomas, Dennis G.; Stegen, James C.; Li, Minjing; Liu, Chongxuan; Song, Xuehang; Chen, Xingyuan; Fredrickson, Jim K.; Zachara, John M.; Scheibe, Timothy D.

2017-09-29

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.

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

International Nuclear Information System (INIS)

Chassin, David P.; Rondeau, Daniel

2016-01-01

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

Climate Shocks and Migration: An Agent-Based Modeling Approach

Science.gov (United States)

Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

2016-01-01

This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725

Profile-likelihood Confidence Intervals in Item Response Theory Models.

Science.gov (United States)

Chalmers, R Philip; Pek, Jolynn; Liu, Yang

2017-01-01

Confidence intervals (CIs) are fundamental inferential devices which quantify the sampling variability of parameter estimates. In item response theory, CIs have been primarily obtained from large-sample Wald-type approaches based on standard error estimates, derived from the observed or expected information matrix, after parameters have been estimated via maximum likelihood. An alternative approach to constructing CIs is to quantify sampling variability directly from the likelihood function with a technique known as profile-likelihood confidence intervals (PL CIs). In this article, we introduce PL CIs for item response theory models, compare PL CIs to classical large-sample Wald-type CIs, and demonstrate important distinctions among these CIs. CIs are then constructed for parameters directly estimated in the specified model and for transformed parameters which are often obtained post-estimation. Monte Carlo simulation results suggest that PL CIs perform consistently better than Wald-type CIs for both non-transformed and transformed parameters.

Modelling an exploited marine fish community with 15 parameters - results from a simple size-based model

NARCIS (Netherlands)

Pope, J.G.; Rice, J.C.; Daan, N.; Jennings, S.; Gislason, H.

2006-01-01

To measure and predict the response of fish communities to exploitation, it is necessary to understand how the direct and indirect effects of fishing interact. Because fishing and predation are size-selective processes, the potential response can be explored with size-based models. We use a

Entropy model of dissipative structure on corporate social responsibility

Science.gov (United States)

Li, Zuozhi; Jiang, Jie

2017-06-01

Enterprise is prompted to fulfill the social responsibility requirement by the internal and external environment. In this complex system, some studies suggest that firms have an orderly or chaotic entropy exchange behavior. Based on the theory of dissipative structure, this paper constructs the entropy index system of corporate social responsibility(CSR) and explores the dissipative structure of CSR through Brusselator model criterion. Picking up listed companies of the equipment manufacturing, the research shows that CSR has positive incentive to negative entropy and promotes the stability of dissipative structure. In short, the dissipative structure of CSR has a positive impact on the interests of stakeholders and corporate social images.

Police Mental Health Partnership project: Police Ambulance Crisis Emergency Response (PACER) model development.

Science.gov (United States)

Huppert, David; Griffiths, Matthew

2015-10-01

To review internationally recognized models of police interactions with people experiencing mental health crises that are sometimes complex and associated with adverse experience for the person in crisis, their family and emergency service personnel. To develop, implement and review a partnership model trial between mental health and emergency services that offers alternative response pathways with improved outcomes in care. Three unique models of police and mental health partnership in the USA were reviewed and used to develop the PACER (Police Ambulance Crisis Emergency Response) model. A three month trial of the model was implemented and evaluated. Significant improvements in response times, the interactions with and the outcomes for people in crisis were some of the benefits shown when compared with usual services. The pilot showed that a partnership involving mental health and police services in Melbourne, Australia could be replicated based on international models. Initial data supported improvements compared with usual care. Further data collection regarding usual care and this new model is required to confirm observed benefits. © The Royal Australian and New Zealand College of Psychiatrists 2015.

Bayes factor covariance testing in item response models

NARCIS (Netherlands)

Fox, J.P.; Mulder, J.; Sinharay, Sandip

2017-01-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning

Bayes Factor Covariance Testing in Item Response Models

NARCIS (Netherlands)

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-01-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning

An approach to model validation and model-based prediction -- polyurethane foam case study.

Energy Technology Data Exchange (ETDEWEB)

Dowding, Kevin J.; Rutherford, Brian Milne

2003-07-01

analyses and hypothesis tests as a part of the validation step to provide feedback to analysts and modelers. Decisions on how to proceed in making model-based predictions are made based on these analyses together with the application requirements. Updating modifying and understanding the boundaries associated with the model are also assisted through this feedback. (4) We include a ''model supplement term'' when model problems are indicated. This term provides a (bias) correction to the model so that it will better match the experimental results and more accurately account for uncertainty. Presumably, as the models continue to develop and are used for future applications, the causes for these apparent biases will be identified and the need for this supplementary modeling will diminish. (5) We use a response-modeling approach for our predictions that allows for general types of prediction and for assessment of prediction uncertainty. This approach is demonstrated through a case study supporting the assessment of a weapons response when subjected to a hydrocarbon fuel fire. The foam decomposition model provides an important element of the response of a weapon system in this abnormal thermal environment. Rigid foam is used to encapsulate critical components in the weapon system providing the needed mechanical support as well as thermal isolation. Because the foam begins to decompose at temperatures above 250 C, modeling the decomposition is critical to assessing a weapons response. In the validation analysis it is indicated that the model tends to ''exaggerate'' the effect of temperature changes when compared to the experimental results. The data, however, are too few and to restricted in terms of experimental design to make confident statements regarding modeling problems. For illustration, we assume these indications are correct and compensate for this apparent bias by constructing a model supplement term for use in the model-based

Dynamic response modelling and characterization of a vertical electrothermal actuator

International Nuclear Information System (INIS)

Li, Lijie; Uttamchandani, Deepak

2009-01-01

Mathematical modelling and characterization of the dynamic response of a microelectromechanical system (MEMS) electrothermal actuator are presented in this paper. The mathematical model is based on a second-order partial differential equation (one-dimensional heat transfer) and a second-order ordinary differential equation (mechanical dynamic equation). The simulations are implemented using the piecewise finite difference method and the Runge–Kutta algorithm. The electrothermal modelling includes thermal conduction, convective thermal loss and radiation effects. The temperature dependence of resistivity and thermal conductivity of single crystal silicon have also been taken into consideration in the electrothermal modelling. It is calculated from the simulation results that the 'cold' beam of the electrothermal actuator is not only a mechanical constraint but also a thermal response compensation structure. The 0–90% electrothermal rise times for the individual 'hot' and 'cold' beams are calculated to be 32.9 ms and 42.8 ms, respectively, while the 0–90% electrothermal rise time for the whole actuator is calculated to be 17.3 ms. Nonlinear cubic stiffness has been considered in the thermal-mechanical modelling. Dynamic performances of the device have been characterized using a laser vibrometer, and the 0–90% thermal response time of the whole structure has been measured to be 16.8 ms, which matches well with the modelling results. The displacements of the device under different driving conditions and at resonant frequency have been modelled and measured, and the results from both modelling and experiment agree reasonably well. This work provides a comprehensive understanding of the dynamic behaviour of the electrothermal actuation mechanism. The model will be useful for designing control systems for microelectrothermal actuated devices

Climate responses to SATIRE and SIM-based spectral solar forcing in a 3D atmosphere-ocean coupled GCM

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Wen Guoyong

2017-01-01

Full Text Available We apply two reconstructed spectral solar forcing scenarios, one SIM (Spectral Irradiance Monitor based, the other the SATIRE (Spectral And Total Irradiance REconstruction modeled, as inputs to the GISS (Goddard Institute for Space Studies GCMAM (Global Climate Middle Atmosphere Model to examine climate responses on decadal to centennial time scales, focusing on quantifying the difference of climate response between the two solar forcing scenarios. We run the GCMAM for about 400 years with present day trace gas and aerosol for the two solar forcing inputs. We find that the SIM-based solar forcing induces much larger long-term response and 11-year variation in global averaged stratospheric temperature and column ozone. We find significant decreasing trends of planetary albedo for both forcing scenarios in the 400-year model runs. However the mechanisms for the decrease are very different. For SATIRE solar forcing, the decreasing trend of planetary albedo is associated with changes in cloud cover. For SIM-based solar forcing, without significant change in cloud cover on centennial and longer time scales, the apparent decreasing trend of planetary albedo is mainly due to out-of-phase variation in shortwave radiative forcing proxy (downwelling flux for wavelength >330 nm and total solar irradiance (TSI. From the Maunder Minimum to present, global averaged annual mean surface air temperature has a response of ~0.1 °C to SATIRE solar forcing compared to ~0.04 °C to SIM-based solar forcing. For 11-year solar cycle, the global surface air temperature response has 3-year lagged response to either forcing scenario. The global surface air 11-year temperature response to SATIRE forcing is about 0.12 °C, similar to recent multi-model estimates, and comparable to the observational-based evidence. However, the global surface air temperature response to 11-year SIM-based solar forcing is insignificant and inconsistent with observation-based evidence.

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

Science.gov (United States)

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

2012-09-01

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

Response Modelling of Bitumen, Bituminous Mastic and Mortar

NARCIS (Netherlands)

Woldekidan, M.F.

2011-01-01

This research focuses on testing and modelling the viscoelastic response of bituminous binders. The main goal is to find an appropriate response model for bituminous binders. The desired model should allow implementation into numerical environments such as ABAQUS. On the basis of such numerical

Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response

International Nuclear Information System (INIS)

Zheng, Menglian; Meinrenken, Christoph J.; Lackner, Klaus S.

2014-01-01

Highlights: • Storage-based demand response (loadshifting) is underutilized in residential sector. • Economics (arbitrage savings versus equipment cost) are not well understood. • Stochastic demand models and real-life tariffs can illuminate economic viability. • A range of available storage options provide economically viable DR. • Daily/seasonal stochastic demand variations crucial to understanding optimum capacity. - Abstract: Demand response (DR) is one of many approaches to address temporal mismatches in demand and supply of grid electricity. More common in the commercial sector, DR usually refers to reducing consumption at certain hours or seasons, thus reducing peak demand from the grid. In the residential sector, where sophisticated appliance-level controls such as automatic dimming of lights or on-demand lowering of air conditioning are less common, building-based electricity storage to shift grid consumption from peak to off-peak times could provide DR without requiring consumers to operate their appliances on shifted or reduced schedules: Storage would be dispatched to appliances as needed while still shaving peaks on the grid. Technologically, storage and two-way-inverters are readily available to enable such residential DR. Economically, however, the situation is less clear. Specifically, are time-varying electricity tariffs available such that electricity cost reduction via arbitrage could offset manufacturing, financing, and installation costs of the required storage? To address this question we (i) devise an agent-based appliance-level stochastic model to simulate the electricity demand of an average U.S. household; (ii) loadshift the demand via simple dispatch strategies; and (iii) determine potential profits to the building owner, i.e. reduced electricity cost of the modified demand with realistic tariffs (Con Edison, NY) minus storage cost. We determine the economic viability for a range of traditional and advanced storage technologies

Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load

Directory of Open Access Journals (Sweden)

Shengchun Yang

2016-01-01

Full Text Available Demand response (DR programs provide an effective approach for dealing with the challenge of wind power output fluctuations. Given that uncertain DR, such as price elastic load (PEL, plays an important role, the uncertainty of demand response behavior must be studied. In this paper, a multi-objective stochastic optimization problem of PEL is proposed on the basis of the analysis of the relationship between price elasticity and probabilistic characteristic, which is about stochastic demand models for consumer loads. The analysis aims to improve the capability of accommodating wind output uncertainty. In our approach, the relationship between the amount of demand response and interaction efficiency is developed by actively participating in power grid interaction. The probabilistic representation and uncertainty range of the PEL demand response amount are formulated differently compared with those of previous research. Based on the aforementioned findings, a stochastic optimization model with the combined uncertainties from the wind power output and the demand response scenario is proposed. The proposed model analyzes the demand response behavior of PEL by maximizing the electricity consumption satisfaction and interaction benefit satisfaction of PEL. Finally, a case simulation on the provincial power grid with a 151-bus system verifies the effectiveness and feasibility of the proposed mechanism and models.

Jesuit universities and social responsibility: a proposal based on solidarity justice

Directory of Open Access Journals (Sweden)

Cristina de la Cruz Ayuso

2017-04-01

Full Text Available The aim of this article is to analyze the concept of responsibility and its institutionalization processes promoted by the Jesuit universities, emphasizing their uniqueness and value compared to other models and strategies of university social responsibility. This responsibility approach is rooted in a notion of justice conceived in global terms and based on solidarity and that, without rejecting it, highlights the inadequacy of the approach to responsibility as an obligation. Its emphasis is directed towards a shared political responsibility that aspires to transform structural injustices. This is one of the distinctive features of the Identity and Mission of Jesuit universities that define their social status. The article outlines this proposal of responsibility embodied in the social field and examines its distinguishing character compared with other proposals promoted by the universities to define their commitment to the environment.

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

Science.gov (United States)

Leventhal, Brian C.; Stone, Clement A.

2018-01-01

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

A Fuzzy Modeling Approach for Replicated Response Measures Based on Fuzzification of Replications with Descriptive Statistics and Golden Ratio

Directory of Open Access Journals (Sweden)

Özlem TÜRKŞEN

2018-03-01

Full Text Available Some of the experimental designs can be composed of replicated response measures in which the replications cannot be identified exactly and may have uncertainty different than randomness. Then, the classical regression analysis may not be proper to model the designed data because of the violation of probabilistic modeling assumptions. In this case, fuzzy regression analysis can be used as a modeling tool. In this study, the replicated response values are newly formed to fuzzy numbers by using descriptive statistics of replications and golden ratio. The main aim of the study is obtaining the most suitable fuzzy model for replicated response measures through fuzzification of the replicated values by taking into account the data structure of the replications in statistical framework. Here, the response and unknown model coefficients are considered as triangular type-1 fuzzy numbers (TT1FNs whereas the inputs are crisp. Predicted fuzzy models are obtained according to the proposed fuzzification rules by using Fuzzy Least Squares (FLS approach. The performances of the predicted fuzzy models are compared by using Root Mean Squared Error (RMSE criteria. A data set from the literature, called wheel cover component data set, is used to illustrate the performance of the proposed approach and the obtained results are discussed. The calculation results show that the combined formulation of the descriptive statistics and the golden ratio is the most preferable fuzzification rule according to the well-known decision making method, called TOPSIS, for the data set.

INDIVIDUAL-BASED MODELS: POWERFUL OR POWER STRUGGLE?

Science.gov (United States)

Willem, L; Stijven, S; Hens, N; Vladislavleva, E; Broeckhove, J; Beutels, P

2015-01-01

Individual-based models (IBMs) offer endless possibilities to explore various research questions but come with high model complexity and computational burden. Large-scale IBMs have become feasible but the novel hardware architectures require adapted software. The increased model complexity also requires systematic exploration to gain thorough system understanding. We elaborate on the development of IBMs for vaccine-preventable infectious diseases and model exploration with active learning. Investment in IBM simulator code can lead to significant runtime reductions. We found large performance differences due to data locality. Sorting the population once, reduced simulation time by a factor two. Storing person attributes separately instead of using person objects also seemed more efficient. Next, we improved model performance up to 70% by structuring potential contacts based on health status before processing disease transmission. The active learning approach we present is based on iterative surrogate modelling and model-guided experimentation. Symbolic regression is used for nonlinear response surface modelling with automatic feature selection. We illustrate our approach using an IBM for influenza vaccination. After optimizing the parameter spade, we observed an inverse relationship between vaccination coverage and the clinical attack rate reinforced by herd immunity. These insights can be used to focus and optimise research activities, and to reduce both dimensionality and decision uncertainty.

Analyzing Cyber Security Threats on Cyber-Physical Systems Using Model-Based Systems Engineering

Science.gov (United States)

Kerzhner, Aleksandr; Pomerantz, Marc; Tan, Kymie; Campuzano, Brian; Dinkel, Kevin; Pecharich, Jeremy; Nguyen, Viet; Steele, Robert; Johnson, Bryan

2015-01-01

The spectre of cyber attacks on aerospace systems can no longer be ignored given that many of the components and vulnerabilities that have been successfully exploited by the adversary on other infrastructures are the same as those deployed and used within the aerospace environment. An important consideration with respect to the mission/safety critical infrastructure supporting space operations is that an appropriate defensive response to an attack invariably involves the need for high precision and accuracy, because an incorrect response can trigger unacceptable losses involving lives and/or significant financial damage. A highly precise defensive response, considering the typical complexity of aerospace environments, requires a detailed and well-founded understanding of the underlying system where the goal of the defensive response is to preserve critical mission objectives in the presence of adversarial activity. In this paper, a structured approach for modeling aerospace systems is described. The approach includes physical elements, network topology, software applications, system functions, and usage scenarios. We leverage Model-Based Systems Engineering methodology by utilizing the Object Management Group's Systems Modeling Language to represent the system being analyzed and also utilize model transformations to change relevant aspects of the model into specialized analyses. A novel visualization approach is utilized to visualize the entire model as a three-dimensional graph, allowing easier interaction with subject matter experts. The model provides a unifying structure for analyzing the impact of a particular attack or a particular type of attack. Two different example analysis types are demonstrated in this paper: a graph-based propagation analysis based on edge labels, and a graph-based propagation analysis based on node labels.

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

Science.gov (United States)

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

2012-01-01

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

Models for the field-based toxicity of copper and zinc salts to wheat in 11 Australian soils and comparison to laboratory-based models

International Nuclear Information System (INIS)

Warne, Michael St.J.; Heemsbergen, Diane; McLaughlin, Mike; Bell, Mike; Broos, Kris; Whatmuff, Mark; Barry, Glenn; Nash, David; Pritchard, Deb; Penney, Nancy

2008-01-01

Laboratory-based relationships that model the phytotoxicity of metals using soil properties have been developed. This paper presents the first field-based phytotoxicity relationships. Wheat (Triticum aestivum L.) was grown at 11 Australian field sites at which soil was spiked with copper (Cu) and zinc (Zn) salts. Toxicity was measured as inhibition of plant growth at 8 weeks and grain yield at harvest. The added Cu and Zn EC10 values for both endpoints ranged from approximately 3 to 4760 mg/kg. There were no relationships between field-based 8-week biomass and grain yield toxicity values for either metal. Cu toxicity was best modelled using pH and organic carbon content while Zn toxicity was best modelled using pH and the cation exchange capacity. The best relationships estimated toxicity within a factor of two of measured values. Laboratory-based phytotoxicity relationships could not accurately predict field-based phytotoxicity responses. - Field-based toxicity of Cu and Zn to wheat can be modelled using soil properties. Laboratory-based models should not be used to estimate toxicity in the field

Search-based model identification of smart-structure damage

Science.gov (United States)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

Development of a theoretical model for measuring the perceived value of social responsibility of IPEN

International Nuclear Information System (INIS)

Mutarelli, Rita de Cassia; Lima, Ana Cecilia de Souza; Sabundjian, Gaiane

2015-01-01

Social responsibility has been one of the great discussions in institutional management, and that is an important variable in the strategy and performance of the institutions. The Instituto de Pesquisas Energeticas e Nucleares (IPEN) has worked for the development of environmental and social issues, converging mainly to the benefit of the population. The theory that guides the social responsibility practices is always difficult to measure for several reasons. One reason for this difficulty is that social responsibility involves a variety of issues that are converted in rights, obligations and expectations of different audiences that could be internal and external to the organization. In addition, the different understanding of the institutions about social and environmental issues is another source of complexity. Based on the study context including: the topic being researched, the chosen institute and the questions resulting from the research, the aim of this paper is to propose a theoretical model to describe and analyze the social responsibility of IPEN. The main contribution of this study is to develop a model that integrates the dimensions of social responsibility. These dimensions - also called constructs - are composed of indexes and indicators that were previously used in various contexts of empirical research, combined with the theoretical and conceptual review of social responsibility. The construction of the proposed theoretical model was based on the research of various methodologies and various indicators for measuring social responsibility. This model was statistically tested, analyzed, adjusted, and the end result is a consistent model to measure the perceived value of social responsibility of IPEN. This work could also be applied to other institutions. Moreover, it may be improved and become a tool that will serve as a thermometer to measure social and environmental issues, and will support decision making in various management processes. (author)

Development of a theoretical model for measuring the perceived value of social responsibility of IPEN

Energy Technology Data Exchange (ETDEWEB)

Mutarelli, Rita de Cassia; Lima, Ana Cecilia de Souza; Sabundjian, Gaiane, E-mail: rmutarelli@gmail.com, E-mail: aclima@ipen.br, E-mail: gdjian@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2015-07-01

Social responsibility has been one of the great discussions in institutional management, and that is an important variable in the strategy and performance of the institutions. The Instituto de Pesquisas Energeticas e Nucleares (IPEN) has worked for the development of environmental and social issues, converging mainly to the benefit of the population. The theory that guides the social responsibility practices is always difficult to measure for several reasons. One reason for this difficulty is that social responsibility involves a variety of issues that are converted in rights, obligations and expectations of different audiences that could be internal and external to the organization. In addition, the different understanding of the institutions about social and environmental issues is another source of complexity. Based on the study context including: the topic being researched, the chosen institute and the questions resulting from the research, the aim of this paper is to propose a theoretical model to describe and analyze the social responsibility of IPEN. The main contribution of this study is to develop a model that integrates the dimensions of social responsibility. These dimensions - also called constructs - are composed of indexes and indicators that were previously used in various contexts of empirical research, combined with the theoretical and conceptual review of social responsibility. The construction of the proposed theoretical model was based on the research of various methodologies and various indicators for measuring social responsibility. This model was statistically tested, analyzed, adjusted, and the end result is a consistent model to measure the perceived value of social responsibility of IPEN. This work could also be applied to other institutions. Moreover, it may be improved and become a tool that will serve as a thermometer to measure social and environmental issues, and will support decision making in various management processes. (author)

Pavement Aging Model by Response Surface Modeling

Directory of Open Access Journals (Sweden)

Manzano-Ramírez A.

2011-10-01

Full Text Available In this work, surface course aging was modeled by Response Surface Methodology (RSM. The Marshall specimens were placed in a conventional oven for time and temperature conditions established on the basis of the environment factors of the region where the surface course is constructed by AC-20 from the Ing. Antonio M. Amor refinery. Volatilized material (VM, load resistance increment (ΔL and flow resistance increment (ΔF models were developed by the RSM. Cylindrical specimens with real aging were extracted from the surface course pilot to evaluate the error of the models. The VM model was adequate, in contrast (ΔL and (ΔF models were almost adequate with an error of 20 %, that was associated with the other environmental factors, which were not considered at the beginning of the research.

Modeling and non-linear responses of MEMS capacitive accelerometer

Directory of Open Access Journals (Sweden)

Sri Harsha C.

2014-01-01

Full Text Available A theoretical investigation of an electrically actuated beam has been illustrated when the electrostatic-ally actuated micro-cantilever beam is separated from the electrode by a moderately large gap for two distinct types of geometric configurations of MEMS accelerometer. Higher order nonlinear terms have been taken into account for studying the pull in voltage analysis. A nonlinear model of gas film squeezing damping, another source of nonlinearity in MEMS devices is included in obtaining the dynamic responses. Moreover, in the present work, the possible source of nonlinearities while formulating the mathematical model of a MEMS accelerometer and their influences on the dynamic responses have been investigated. The theoretical results obtained by using MATLAB has been verified with the results obtained in FE software and has been found in good agreement. Criterion towards stable micro size accelerometer for each configuration has been investigated. This investigation clearly provides an understanding of nonlinear static and dynamics characteristics of electrostatically micro cantilever based device in MEMS.

Inverse modeling of cloud-aerosol interactions -- Part 1: Detailed response surface analysis

NARCIS (Netherlands)

Partridge, D.G.; Vrugt, J.A.; Tunved, P.; Ekman, A.M.L.; Gorea, D.; Sooroshian, A.

2011-01-01

New methodologies are required to probe the sensitivity of parameters describing cloud droplet activation. This paper presents an inverse modeling-based method for exploring cloud-aerosol interactions via response surfaces. The objective function, containing the difference between the measured and

Regularization of a massless dirac model to describe anomalous electromagnetic response of Weyl semimetals

International Nuclear Information System (INIS)

Takane, Yoshitake

2016-01-01

An unbounded massless Dirac model with two nondegenerate Dirac cones is the simplest model for Weyl semimetals, which show the anomalous electromagnetic response of chiral magnetic effect (CME) and anomalous Hall effect (AHE). However, if this model is naively used to analyze the electromagnetic response within a linear response theory, it gives the result apparently inconsistent with the persuasive prediction based on a lattice model. We show that this serious difficulty is related to the breaking of current conservation in the Dirac model due to quantum anomaly and can be removed if current and charge operators are redefined to include the contribution from the anomaly. We demonstrate that the CME as well as the AHE can be properly described using newly defined operators, and clarify that the CME is determined by the competition between the contribution from the anomaly and that from low-energy electrons. (author)

Modeling adaptive and non-adaptive responses to environmental change

DEFF Research Database (Denmark)

Coulson, Tim; Kendall, Bruce E; Barthold, Julia A.

2017-01-01

, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we...... construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive....... Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full...

Mesoscopic model of actin-based propulsion.

Directory of Open Access Journals (Sweden)

Jie Zhu

Full Text Available Two theoretical models dominate current understanding of actin-based propulsion: microscopic polymerization ratchet model predicts that growing and writhing actin filaments generate forces and movements, while macroscopic elastic propulsion model suggests that deformation and stress of growing actin gel are responsible for the propulsion. We examine both experimentally and computationally the 2D movement of ellipsoidal beads propelled by actin tails and show that neither of the two models can explain the observed bistability of the orientation of the beads. To explain the data, we develop a 2D hybrid mesoscopic model by reconciling these two models such that individual actin filaments undergoing nucleation, elongation, attachment, detachment and capping are embedded into the boundary of a node-spring viscoelastic network representing the macroscopic actin gel. Stochastic simulations of this 'in silico' actin network show that the combined effects of the macroscopic elastic deformation and microscopic ratchets can explain the observed bistable orientation of the actin-propelled ellipsoidal beads. To test the theory further, we analyze observed distribution of the curvatures of the trajectories and show that the hybrid model's predictions fit the data. Finally, we demonstrate that the model can explain both concave-up and concave-down force-velocity relations for growing actin networks depending on the characteristic time scale and network recoil. To summarize, we propose that both microscopic polymerization ratchets and macroscopic stresses of the deformable actin network are responsible for the force and movement generation.

A New Method for a Virtue-Based Responsible Conduct of Research Curriculum: Pilot Test Results.

Science.gov (United States)

Berling, Eric; McLeskey, Chet; O'Rourke, Michael; Pennock, Robert T

2018-02-03

Drawing on Pennock's theory of scientific virtues, we are developing an alternative curriculum for training scientists in the responsible conduct of research (RCR) that emphasizes internal values rather than externally imposed rules. This approach focuses on the virtuous characteristics of scientists that lead to responsible and exemplary behavior. We have been pilot-testing one element of such a virtue-based approach to RCR training by conducting dialogue sessions, modeled upon the approach developed by Toolbox Dialogue Initiative, that focus on a specific virtue, e.g., curiosity and objectivity. During these structured discussions, small groups of scientists explore the roles they think the focus virtue plays and should play in the practice of science. Preliminary results have shown that participants strongly prefer this virtue-based model over traditional methods of RCR training. While we cannot yet definitively say that participation in these RCR sessions contributes to responsible conduct, these pilot results are encouraging and warrant continued development of this virtue-based approach to RCR training.

Bridge Condition Assessment based on Vibration Responses of Passenger Vehicle

International Nuclear Information System (INIS)

Miyamoto, Ayaho; Yabe, Akito

2011-01-01

In this paper, we propose a new method of assessing the condition of existing short- and medium-span reinforced/prestressed concrete bridges based on vibration monitoring data obtained from a public bus. This paper not only describes details of a prototype monitoring system that uses information technology and sensors capable of providing more accurate knowledge of bridge performance than conventional ways but also shows a few specific examples of bridge condition assessment based on vehicle vibrations measured by using an in-service public bus equipped with vibration measurement instrumentation. This paper also describes a sensitivity analysis of deteriorating bridges based on simulation of the acceleration response of buses conducted by the 'substructure method' employing a finite element model to verify the above bridge performance results. The main conclusions obtained in this study can be summarized as follows: (1) Because the vibration responses of passenger vehicles, such as buses, have a good linear relationship with the vibration responses of the target bridges, the proposed system can be used as a practical monitoring system for bridge condition assessment. (2) The results of sensitivity analysis performed by the substructure method show that bus vibration responses are useful for evaluating target bridge performance. (3) The proposed method was applied to a network of real bridges in a local area to evaluate its effectiveness. The results indicate that the proposed method can be used to prioritize the repair/strengthening works of existing bridges based on various vibration information in order to help bridge administrators establish rational maintenance strategies.

Instrument Response Modeling and Simulation for the GLAST Burst Monitor

International Nuclear Information System (INIS)

Kippen, R. M.; Hoover, A. S.; Wallace, M. S.; Pendleton, G. N.; Meegan, C. A.; Fishman, G. J.; Wilson-Hodge, C. A.; Kouveliotou, C.; Lichti, G. G.; Kienlin, A. von; Steinle, H.; Diehl, R.; Greiner, J.; Preece, R. D.; Connaughton, V.; Briggs, M. S.; Paciesas, W. S.; Bhat, P. N.

2007-01-01

The GLAST Burst Monitor (GBM) is designed to provide wide field of view observations of gamma-ray bursts and other fast transient sources in the energy range 10 keV to 30 MeV. The GBM is composed of several unshielded and uncollimated scintillation detectors (twelve NaI and two BGO) that are widely dispersed about the GLAST spacecraft. As a result, reconstructing source locations, energy spectra, and temporal properties from GBM data requires detailed knowledge of the detectors' response to both direct radiation as well as that scattered from the spacecraft and Earth's atmosphere. This full GBM instrument response will be captured in the form of a response function database that is derived from computer modeling and simulation. The simulation system is based on the GEANT4 Monte Carlo radiation transport simulation toolset, and is being extensively validated against calibrated experimental GBM data. We discuss the architecture of the GBM simulation and modeling system and describe how its products will be used for analysis of observed GBM data. Companion papers describe the status of validating the system

Risk-based approach to appraise valve closure in the clam Corbicula fluminea in response to waterborne metals

International Nuclear Information System (INIS)

Liao, C.-M.; Jou, L.-J.; Chen, B.-C.

2005-01-01

We developed a risk-based approach to assess how the valve closure behavior of Asiatic clam Corbicula fluminea responds to waterborne copper (Cu) and cadmium (Cd). We reanalyzed the valve closure response data from published literature to reconstruct the response time-dependent dose-response profiles based on an empirical three-parameter Hill equation model. We integrated probabilistic exposure profiles of measured environmental Cu and Cd concentrations in the western coastal areas of Taiwan with the reconstructed dose-response relationships at different integration times of response to quantitatively estimate the valve response risk. The risk assessment results implicate exposure to waterborne Cu and Cd may pose no significant risk to clam valve activity in the short-time response periods (e.g., <30 min), yet a relative high risk for valve closure response to waterborne Cu at response times greater than 120 min is alarming. We successfully linked reconstructed dose-response profiles and EC50-time relationships associated with the fitted daily valve opening/closing rhythm characterized by a three-parameter lognormal function to predict the time-varying bivalve closure rhythm response to waterborne metals. We parameterized the proposed predictive model that should encourage a risk-management framework for discussion of future design of biological monitoring systems. - A model was developed to link valve closure in clams to concentrations of metals in water

A novel polar-based human face recognition computational model

Directory of Open Access Journals (Sweden)

Y. Zana

2009-07-01

Full Text Available Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.

Discrete-Slots Models of Visual Working-Memory Response Times

Science.gov (United States)

Donkin, Christopher; Nosofsky, Robert M.; Gold, Jason M.; Shiffrin, Richard M.

2014-01-01

Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a guessing-based accumulation process operates. Observed RT distributions are therefore theorized to arise as probabilistic mixtures of the memory-based and guessing distributions. We formalize an analogous set of continuous shared-resources models. The model classes are tested on individual subjects with both qualitative contrasts and quantitative fits to RT-distribution data. The discrete-slots models provide much better qualitative and quantitative accounts of the RT and choice data than do the shared-resources models, although there is some evidence for “slots plus resources” when memory set size is very small. PMID:24015956

Modelling command and control for emergency response scenarios: A marine oil spills perspective

International Nuclear Information System (INIS)

Weisman, R.

1993-01-01

Commanders in emergency response scenarios have to rapidly formulate viable plans of action in the face of uncertainty, and on the basis of incomplete information and a constantly changing situation. Automated intelligent decision support systems may be a means of helping the commander to elaborate a plan, producing the operations order, and monitoring the plan's execution. The latter aspect would permit the system to advise a commander when key assumptions upon which the plan is based are no longer valid. Any such system will invariably be complex. The first step is the development of a conceptual model which will provide a sound structure to contain all of the requisite knowledge and information. The subject model is relatively simple and includes a metric for evaluating plans, a practical means of handling uncertainty, and a constraint language to capture expert knowledge precisely. Aspects of the model are illustrated using practical examples from the domain of maritime oil spill response. Results from several computer-based implementations of parts of the model are also discussed. 13 refs., 17 figs

Considering Affective Responses towards Environments for Enhancing Location Based Services

Science.gov (United States)

Huang, H.; Gartner, G.; Klettner, S.; Schmidt, M.

2014-04-01

A number of studies in the field of environmental psychology show that humans perceive and evaluate their surroundings affectively. Some places are experienced as unsafe, while some others as attractive and interesting. Experiences from daily life show that many of our daily behaviours and decision-making are often influenced by this kind of affective responses towards environments. Location based services (LBS) are often designed to assist and support people's behaviours and decision-making in space. In order to provide services with high usefulness (usability and utility), LBS should consider these kinds of affective responses towards environments. This paper reports on the results of a research project, which studies how people's affective responses towards environments can be modelled and acquired, as well as how LBS can benefit by considering these affective responses. As one of the most popular LBS applications, mobile pedestrian navigation systems are used as an example for illustration.

Preisach modeling of temperature-dependent ferroelectric response of piezoceramics at sub-switching regime

Science.gov (United States)

Ochoa, Diego Alejandro; García, Jose Eduardo

2016-04-01

The Preisach model is a classical method for describing nonlinear behavior in hysteretic systems. According to this model, a hysteretic system contains a collection of simple bistable units which are characterized by an internal field and a coercive field. This set of bistable units exhibits a statistical distribution that depends on these fields as parameters. Thus, nonlinear response depends on the specific distribution function associated with the material. This model is satisfactorily used in this work to describe the temperature-dependent ferroelectric response in PZT- and KNN-based piezoceramics. A distribution function expanded in Maclaurin series considering only the first terms in the internal field and the coercive field is proposed. Changes in coefficient relations of a single distribution function allow us to explain the complex temperature dependence of hard piezoceramic behavior. A similar analysis based on the same form of the distribution function shows that the KNL-NTS properties soften around its orthorhombic to tetragonal phase transition.

PRESS-based EFOR algorithm for the dynamic parametrical modeling of nonlinear MDOF systems

Science.gov (United States)

Liu, Haopeng; Zhu, Yunpeng; Luo, Zhong; Han, Qingkai

2017-09-01

In response to the identification problem concerning multi-degree of freedom (MDOF) nonlinear systems, this study presents the extended forward orthogonal regression (EFOR) based on predicted residual sums of squares (PRESS) to construct a nonlinear dynamic parametrical model. The proposed parametrical model is based on the non-linear autoregressive with exogenous inputs (NARX) model and aims to explicitly reveal the physical design parameters of the system. The PRESS-based EFOR algorithm is proposed to identify such a model for MDOF systems. By using the algorithm, we built a common-structured model based on the fundamental concept of evaluating its generalization capability through cross-validation. The resulting model aims to prevent over-fitting with poor generalization performance caused by the average error reduction ratio (AERR)-based EFOR algorithm. Then, a functional relationship is established between the coefficients of the terms and the design parameters of the unified model. Moreover, a 5-DOF nonlinear system is taken as a case to illustrate the modeling of the proposed algorithm. Finally, a dynamic parametrical model of a cantilever beam is constructed from experimental data. Results indicate that the dynamic parametrical model of nonlinear systems, which depends on the PRESS-based EFOR, can accurately predict the output response, thus providing a theoretical basis for the optimal design of modeling methods for MDOF nonlinear systems.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

Science.gov (United States)

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

2016-01-01

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

Model-based Quantile Regression for Discrete Data

KAUST Repository

Padellini, Tullia

2018-04-10

Quantile regression is a class of methods voted to the modelling of conditional quantiles. In a Bayesian framework quantile regression has typically been carried out exploiting the Asymmetric Laplace Distribution as a working likelihood. Despite the fact that this leads to a proper posterior for the regression coefficients, the resulting posterior variance is however affected by an unidentifiable parameter, hence any inferential procedure beside point estimation is unreliable. We propose a model-based approach for quantile regression that considers quantiles of the generating distribution directly, and thus allows for a proper uncertainty quantification. We then create a link between quantile regression and generalised linear models by mapping the quantiles to the parameter of the response variable, and we exploit it to fit the model with R-INLA. We extend it also in the case of discrete responses, where there is no 1-to-1 relationship between quantiles and distribution\\'s parameter, by introducing continuous generalisations of the most common discrete variables (Poisson, Binomial and Negative Binomial) to be exploited in the fitting.

Response surface and neural network based predictive models of cutting temperature in hard turning

Directory of Open Access Journals (Sweden)

Mozammel Mia

2016-11-01

Full Text Available The present study aimed to develop the predictive models of average tool-workpiece interface temperature in hard turning of AISI 1060 steels by coated carbide insert. The Response Surface Methodology (RSM and Artificial Neural Network (ANN were employed to predict the temperature in respect of cutting speed, feed rate and material hardness. The number and orientation of the experimental trials, conducted in both dry and high pressure coolant (HPC environments, were planned using full factorial design. The temperature was measured by using the tool-work thermocouple. In RSM model, two quadratic equations of temperature were derived from experimental data. The analysis of variance (ANOVA and mean absolute percentage error (MAPE were performed to suffice the adequacy of the models. In ANN model, 80% data were used to train and 20% data were employed for testing. Like RSM, herein, the error analysis was also conducted. The accuracy of the RSM and ANN model was found to be ⩾99%. The ANN models exhibit an error of ∼5% MAE for testing data. The regression coefficient was found to be greater than 99.9% for both dry and HPC. Both these models are acceptable, although the ANN model demonstrated a higher accuracy. These models, if employed, are expected to provide a better control of cutting temperature in turning of hardened steel.

Vehicle-specific emissions modeling based upon on-road measurements.

Science.gov (United States)

Frey, H Christopher; Zhang, Kaishan; Rouphail, Nagui M

2010-05-01

Vehicle-specific microscale fuel use and emissions rate models are developed based upon real-world hot-stabilized tailpipe measurements made using a portable emissions measurement system. Consecutive averaging periods of one to three multiples of the response time are used to compare two semiempirical physically based modeling schemes. One scheme is based on internally observable variables (IOVs), such as engine speed and manifold absolute pressure, while the other is based on externally observable variables (EOVs), such as speed, acceleration, and road grade. For NO, HC, and CO emission rates, the average R(2) ranged from 0.41 to 0.66 for the former and from 0.17 to 0.30 for the latter. The EOV models have R(2) for CO(2) of 0.43 to 0.79 versus 0.99 for the IOV models. The models are sensitive to episodic events in driving cycles such as high acceleration. Intervehicle and fleet average modeling approaches are compared; the former account for microscale variations that might be useful for some types of assessments. EOV-based models have practical value for traffic management or simulation applications since IOVs usually are not available or not used for emission estimation.

Selection bias in species distribution models: An econometric approach on forest trees based on structural modeling

Science.gov (United States)

Martin-StPaul, N. K.; Ay, J. S.; Guillemot, J.; Doyen, L.; Leadley, P.

2014-12-01

Species distribution models (SDMs) are widely used to study and predict the outcome of global changes on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of applications on forest trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8km). We also compared the outputs of the SSDM with outputs of a classical SDM (i.e. Biomod ensemble modelling) in terms of bioclimatic response curves and potential distributions under current climate and climate change scenarios. The shapes of the bioclimatic response curves and the modelled species distribution maps differed markedly between SSDM and classical SDMs, with contrasted patterns according to species and spatial resolutions. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents

Research toward the development of a biologically based dose response assessment for inorganic arsenic carcinogenicity: A progress report

International Nuclear Information System (INIS)

Clewell, Harvey J.; Thomas, Russell S.; Gentry, P. Robinan; Crump, Kenny S.; Kenyon, Elaina M.; El-Masri, Hisham A.; Yager, Janice W.

2007-01-01

Cancer risk assessments for inorganic arsenic have been based on human epidemiological data, assuming a linear dose response below the range of observation of tumors. Part of the reason for the continued use of the linear approach in arsenic risk assessments is the lack of an adequate biologically based dose response (BBDR) model that could provide a quantitative basis for an alternative nonlinear approach. This paper describes elements of an ongoing collaborative research effort between the CIIT Centers for Health Research, the U.S. Environmental Protection Agency, ENVIRON International, and EPRI to develop BBDR modeling approaches that could be used to inform a nonlinear cancer dose response assessment for inorganic arsenic. These efforts are focused on: (1) the refinement of physiologically based pharmacokinetic (PBPK) models of the kinetics of inorganic arsenic and its metabolites in the mouse and human; (2) the investigation of mathematical solutions for multi-stage cancer models involving multiple pathways of cell transformation; (3) the review and evaluation of the literature on the dose response for the genomic effects of arsenic; and (4) the collection of data on the dose response for genomic changes in the urinary bladder (a human target tissue for arsenic carcinogenesis) associated with in vivo drinking water exposures in the mouse as well as in vitro exposures of both mouse and human cells. An approach is proposed for conducting a biologically based margin of exposure risk assessment for inorganic arsenic using the in vitro dose response for the expression of genes associated with the obligatory precursor events for arsenic tumorigenesis

Testing a bioenergetics-based habitat choice model: bluegill (Lepomis macrochirus) responses to food availability and temperature

Science.gov (United States)

2011-01-01

Using an automated shuttlebox system, we conducted patch choice experiments with 32, 8–12 g bluegill sunfish (Lepomis macrochirus) to test a behavioral energetics hypothesis of habitat choice. When patch temperature and food levels were held constant within patches but different between patches, we expected bluegill to choose patches that maximized growth based on the bioenergetic integration of food and temperature as predicted by a bioenergetics model. Alternative hypotheses were that bluegill may choose patches based only on food (optimal foraging) or temperature (behavioral thermoregulation). The behavioral energetics hypothesis was not a good predictor of short-term (from minutes to weeks) patch choice by bluegill; the behavioral thermoregulation hypothesis was the best predictor. In the short-term, food and temperature appeared to affect patch choice hierarchically; temperature was more important, although food can alter temperature preference during feeding periods. Over a 19-d experiment, mean temperatures occupied by fish offered low rations did decline as predicted by the behavioral energetics hypothesis, but the decline was less than 1.0 °C as opposed to a possible 5 °C decline. A short-term, bioenergetic response to food and temperature may be precluded by physiological costs of acclimation not considered explicitly in the behavioral energetics hypothesis.

Testing and modeling the dynamic response of foam materials for blast protection

Science.gov (United States)

Fitek, John H.

The pressure wave released from an explosion can cause injury to the lungs. A personal armor system concept for blast lung injury protection consists of a polymer foam layer behind a rigid armor plate to be worn over the chest. This research develops a method for testing and modeling the dynamic response of foam materials to be used for down-selection of materials for this application. Constitutive equations for foam materials are incorporated into a lumped parameter model of the combined armor plate and foam system. Impact testing and shock tube testing are used to measure the foam model parameters and validate the model response to a pressure wave load. The plate and foam armor model is then coupled to a model of the human thorax. With a blast pressure wave input, the armor model is evaluated based on how it affects the injury-causing mechanism of chest wall motion. Results show that to reduce chest wall motion, the foam must compress at a relatively constant stress level, which requires a sufficient foam thickness.

Model cortical responses for the detection of perceptual onsets and beat tracking in singing

NARCIS (Netherlands)

Coath, M.; Denham, S.L.; Smith, L.M.; Honing, H.; Hazan, A.; Holonowicz, P.; Purwins, H.

2009-01-01

We describe a biophysically motivated model of auditory salience based on a model of cortical responses and present results that show that the derived measure of salience can be used to identify the position of perceptual onsets in a musical stimulus successfully. The salience measure is also shown

Model-based and model-free Pavlovian reward learning: revaluation, revision, and revelation.

Science.gov (United States)

Dayan, Peter; Berridge, Kent C

2014-06-01

Evidence supports at least two methods for learning about reward and punishment and making predictions for guiding actions. One method, called model-free, progressively acquires cached estimates of the long-run values of circumstances and actions from retrospective experience. The other method, called model-based, uses representations of the environment, expectations, and prospective calculations to make cognitive predictions of future value. Extensive attention has been paid to both methods in computational analyses of instrumental learning. By contrast, although a full computational analysis has been lacking, Pavlovian learning and prediction has typically been presumed to be solely model-free. Here, we revise that presumption and review compelling evidence from Pavlovian revaluation experiments showing that Pavlovian predictions can involve their own form of model-based evaluation. In model-based Pavlovian evaluation, prevailing states of the body and brain influence value computations, and thereby produce powerful incentive motivations that can sometimes be quite new. We consider the consequences of this revised Pavlovian view for the computational landscape of prediction, response, and choice. We also revisit differences between Pavlovian and instrumental learning in the control of incentive motivation.

Development of regional atmospheric dynamic and air pollution models for nuclear emergency response system WSPEEDI

International Nuclear Information System (INIS)

Furuno, Akiko; Yamazawa, Hiromi; Lee, Soon-Hwan; Tsujita, Yuichi; Takemiya, Hiroshi; Chino, Masamichi

2000-01-01

WSPEEDI (Worldwide version of System for Prediction of Environmental Emergency Dose Information) is a computer-based emergency response system to predict long-range atmospheric dispersion of radionuclides discharged into the atmosphere due to a nuclear accident. WSPEEDI has been applied to several international exercises and real events. Through such experiences, the new version of WSPEEDI aims to employ a combination of an atmospheric dynamic model and a particle random walk model for more accurate predictions. This paper describes these models, improvement of prediction and computational techniques for quick responses. (author)

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

Science.gov (United States)

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.

Pavement mechanic response of sulfate saline soil subgrade section based on fluid–structure interaction model

Directory of Open Access Journals (Sweden)

Xueying Zhao

2017-11-01

Full Text Available It is a consensus that salt heaving and frost heaving are urgent and typical distress in the sulfate saline soil area. To further investigate the microscopic performance of pavement structure in this special area, Jinan-Dongying Freeway in Shandong Province is selected as a case study engineering and the mechanic responses under salt heaving, frost heaving and traffic loads were analyzed through the finite element (FE Program (ANSYS. In this paper, the process of salt heaving and frost heaving was divided into 3 stages and FE models were established based on fluid–structure interaction (FSI model. It is shown that under both effects of salt heaving and frost heaving, the tensile stress of asphalt surface course could be up to 96.75% of its tensile strength, which means its tensile strength was seriously inadequate; however, traffic loads could help to dramatically counteract effects of salt heaving and frost heaving, which could decrease 40–80% of the tensile stress in asphalt surface course. It is also shown that in Jinan-Dongying Freeway effects of salt heaving had slightly larger effects on pavement compared with that of frost heaving, probably because salt heaving occurred from the top to the bottom of subgrade. However, as a whole, in sulfate saline soil area, compared with general area, crack resistance of asphalt courses and foundation treatment should always be strengthened. Keywords: Sulfate saline soil subgrade, Asphalt pavement, Pavement mechanic, FEM, FSI, Cracks and bulging

Monte Carlo tests of the Rasch model based on scalability coefficients

DEFF Research Database (Denmark)

Christensen, Karl Bang; Kreiner, Svend

2010-01-01

that summarizes the number of Guttman errors in the data matrix. These coefficients are shown to yield efficient tests of the Rasch model using p-values computed using Markov chain Monte Carlo methods. The power of the tests of unequal item discrimination, and their ability to distinguish between local dependence......For item responses fitting the Rasch model, the assumptions underlying the Mokken model of double monotonicity are met. This makes non-parametric item response theory a natural starting-point for Rasch item analysis. This paper studies scalability coefficients based on Loevinger's H coefficient...

Agent-based modeling and simulation Part 3 : desktop ABMS.

Energy Technology Data Exchange (ETDEWEB)

Macal, C. M.; North, M. J.; Decision and Information Sciences

2007-01-01

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS 'is a third way of doing science,' in addition to traditional deductive and inductive reasoning (Axelrod 1997b). Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, the threat of bio-warfare, and the factors responsible for the fall of ancient civilizations. This tutorial describes the theoretical and practical foundations of ABMS, identifies toolkits and methods for developing agent models, and illustrates the development of a simple agent-based model of shopper behavior using spreadsheets.

Motor execution detection based on autonomic nervous system responses

International Nuclear Information System (INIS)

Marchal-Crespo, Laura; Riener, Robert; Zimmermann, Raphael; Lambercy, Olivier; Edelmann, Janis; Fluet, Marie-Christine; Gassert, Roger; Wolf, Martin

2013-01-01

Triggered assistance has been shown to be a successful robotic strategy for provoking motor plasticity, probably because it requires neurologic patients’ active participation to initiate a movement involving their impaired limb. Triggered assistance, however, requires sufficient residual motor control to activate the trigger and, thus, is not applicable to individuals with severe neurologic injuries. In these situations, brain and body–computer interfaces have emerged as promising solutions to control robotic devices. In this paper, we investigate the feasibility of a body–machine interface to detect motion execution only monitoring the autonomic nervous system (ANS) response. Four physiological signals were measured (blood pressure, breathing rate, skin conductance response and heart rate) during an isometric pinching task and used to train a classifier based on hidden Markov models. We performed an experiment with six healthy subjects to test the effectiveness of the classifier to detect rest and active pinching periods. The results showed that the movement execution can be accurately classified based only on peripheral autonomic signals, with an accuracy level of 84.5%, sensitivity of 83.8% and specificity of 85.2%. These results are encouraging to perform further research on the use of the ANS response in body–machine interfaces. (paper)

A physiologically based nonhomogeneous Poisson counter model of visual identification.

Science.gov (United States)

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

2018-04-30

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

Investigate the plant biomass response to climate warming in permafrost ecosystem using matrix-based data assimilation

Science.gov (United States)

Lu, X.; Du, Z.; Schuur, E.; Luo, Y.

2017-12-01

Permafrost is one of the most vulnerable regions on the earth with over 40% world soil C represented in this region. Future climate warming potentially has a great impact on this region. On one hand, rising temperature accelerates permafrost soil thaw and release more C from land. On the other hand, warming may also increase the plant growing season length and therefore negatively feedback to climate change by increasing annual land C uptake. However, whether permafrost vegetation biomass change in response to warming can sequester more C has not been well understood. Manipulated air warming experiments reported that air warming has very limited impacts on grass land productivity and biomass growth in permafrost region [Mauritz et al., 2017]. It is hard to reveal the mechanisms behind the limited air warming response directly from experiment data. We employ a vegetation C cycle matrix model based on Community land model 4.5 (CLM4.5) and data assimilation technique to investigate how much do phenology and physiology processes contribute to the response respectively. Our results indicate phenology contributes the most in response to warming. The shift of vegetation parameter distributions after 2012 indicate vegetation acclimation may explain the modest response in plant biomass to air warming. The results suggest future model development need to take vegetation acclimation more seriously. The novel matrix-based model allows data assimilation to be conducted more efficiently. It provides more functional understanding of the models as well as the mechanism behind experiment data.

Evaluation of geometrically personalized THUMS pedestrian model response against sedan-pedestrian PMHS impact test data.

Science.gov (United States)

Chen, Huipeng; Poulard, David; Forman, Jason; Crandall, Jeff; Panzer, Matthew B

2018-07-04

Evaluating the biofidelity of pedestrian finite element models (PFEM) using postmortem human subjects (PMHS) is a challenge because differences in anthropometry between PMHS and PFEM could limit a model's capability to accurately capture cadaveric responses. Geometrical personalization via morphing can modify the PFEM geometry to match the specific PMHS anthropometry, which could alleviate this issue. In this study, the Total Human Model for Safety (THUMS) PFEM (Ver 4.01) was compared to the cadaveric response in vehicle-pedestrian impacts using geometrically personalized models. The AM50 THUMS PFEM was used as the baseline model, and 2 morphed PFEM were created to the anthropometric specifications of 2 obese PMHS used in a previous pedestrian impact study with a mid-size sedan. The same measurements as those obtained during the PMHS tests were calculated from the simulations (kinematics, accelerations, strains), and biofidelity metrics based on signals correlation (correlation and analysis, CORA) were established to compare the response of the models to the experiments. Injury outcomes were predicted deterministically (through strain-based threshold) and probabilistically (with injury risk functions) and compared with the injuries reported in the necropsy. The baseline model could not accurately capture all aspects of the PMHS kinematics, strain, and injury risks, whereas the morphed models reproduced biofidelic response in terms of trajectory (CORA score = 0.927 ± 0.092), velocities (0.975 ± 0.027), accelerations (0.862 ± 0.072), and strains (0.707 ± 0.143). The personalized THUMS models also generally predicted injuries consistent with those identified during posttest autopsy. The study highlights the need to control for pedestrian anthropometry when validating pedestrian human body models against PMHS data. The information provided in the current study could be useful for improving model biofidelity for vehicle-pedestrian impact scenarios.

Multi-scale Modeling of the Impact Response of a Strain Rate Sensitive High-Manganese Austenitic Steel

Directory of Open Access Journals (Sweden)

Orkun eÖnal

2014-09-01

Full Text Available A multi-scale modeling approach was applied to predict the impact response of a strain rate sensitive high-manganese austenitic steel. The roles of texture, geometry and strain rate sensitivity were successfully taken into account all at once by coupling crystal plasticity and finite element (FE analysis. Specifically, crystal plasticity was utilized to obtain the multi-axial flow rule at different strain rates based on the experimental deformation response under uniaxial tensile loading. The equivalent stress – equivalent strain response was then incorporated into the FE model for the sake of a more representative hardening rule under impact loading. The current results demonstrate that reliable predictions can be obtained by proper coupling of crystal plasticity and FE analysis even if the experimental flow rule of the material is acquired under uniaxial loading and at moderate strain rates that are significantly slower than those attained during impact loading. Furthermore, the current findings also demonstrate the need for an experiment-based multi-scale modeling approach for the sake of reliable predictions of the impact response.

Response mechanism for surface acoustic wave gas sensors based on surface-adsorption.

Science.gov (United States)

Liu, Jiansheng; Lu, Yanyan

2014-04-16

A theoretical model is established to describe the response mechanism of surface acoustic wave (SAW) gas sensors based on physical adsorption on the detector surface. Wohljent's method is utilized to describe the relationship of sensor output (frequency shift of SAW oscillator) and the mass loaded on the detector surface. The Brunauer-Emmett-Teller (BET) formula and its improved form are introduced to depict the adsorption behavior of gas on the detector surface. By combining the two methods, we obtain a theoretical model for the response mechanism of SAW gas sensors. By using a commercial SAW gas chromatography (GC) analyzer, an experiment is performed to measure the frequency shifts caused by different concentration of dimethyl methylphosphonate (DMMP). The parameters in the model are given by fitting the experimental results and the theoretical curve agrees well with the experimental data.

A model for successful use of student response systems.

Science.gov (United States)

Klein, Kathleen; Kientz, Mary

2013-01-01

This article presents a model developed to assist teachers in selecting, implementing, and assessing student response system (SRS) use in the classroom. Research indicates that SRS technology is effective in achieving desired outcomes in higher education settings. Studies indicate that effective SRS use promotes greater achievement of learning outcomes, increased student attention, improved class participation, and active engagement. The model offered in this article is based on best practices described in the literature and several years of SRS use in a traditional higher education classroom setting. Student feedback indicates increased class participation and engagement with SRS technology. Teacher feedback indicates opportunities for contingent teaching. The model described in this article provides a process to assist teachers in the successful selection, implementation, and assessment of SRS technology in the classroom.

A Model of Social Responsibility of Actors in the State Sector of Economy

Directory of Open Access Journals (Sweden)

Krutova Anzhelika S.

2017-05-01

Full Text Available The article is aimed at developing a conceptual model of social responsibility of actors in the State sector of economy and elaborating directions for its improvement. It has been determined that social responsibility of the State and actors in the State sector of economy, as managers of the budget, is to determine and reconcile positions on the achievement of joint agreements and adoption of agreed decisions by the parties to the social dialog. A conceptual model of the socially responsible State has been developed, where the functions of moderator of principles of social responsibility at all levels of socio-economic relations are vested in the State sector of economy. It has been substantiated that the main tool for the creation of a social State is the auditing of social responsibility, the basic information base for controlling the level of social responsibility is the integrated reporting of companies. To disseminate the ideas of integrated reporting, creation of a «Single portal of integrated reporting for enterprises and organizations of Ukraine» has been proposed.

Digital Tomosynthesis System Geometry Analysis Using Convolution-Based Blur-and-Add (BAA) Model.

Science.gov (United States)

Wu, Meng; Yoon, Sungwon; Solomon, Edward G; Star-Lack, Josh; Pelc, Norbert; Fahrig, Rebecca

2016-01-01

Digital tomosynthesis is a three-dimensional imaging technique with a lower radiation dose than computed tomography (CT). Due to the missing data in tomosynthesis systems, out-of-plane structures in the depth direction cannot be completely removed by the reconstruction algorithms. In this work, we analyzed the impulse responses of common tomosynthesis systems on a plane-to-plane basis and proposed a fast and accurate convolution-based blur-and-add (BAA) model to simulate the backprojected images. In addition, the analysis formalism describing the impulse response of out-of-plane structures can be generalized to both rotating and parallel gantries. We implemented a ray tracing forward projection and backprojection (ray-based model) algorithm and the convolution-based BAA model to simulate the shift-and-add (backproject) tomosynthesis reconstructions. The convolution-based BAA model with proper geometry distortion correction provides reasonably accurate estimates of the tomosynthesis reconstruction. A numerical comparison indicates that the simulated images using the two models differ by less than 6% in terms of the root-mean-squared error. This convolution-based BAA model can be used in efficient system geometry analysis, reconstruction algorithm design, out-of-plane artifacts suppression, and CT-tomosynthesis registration.

AAA gunnermodel based on observer theory. [predicting a gunner's tracking response

Science.gov (United States)

Kou, R. S.; Glass, B. C.; Day, C. N.; Vikmanis, M. M.

1978-01-01

The Luenberger observer theory is used to develop a predictive model of a gunner's tracking response in antiaircraft artillery systems. This model is composed of an observer, a feedback controller and a remnant element. An important feature of the model is that the structure is simple, hence a computer simulation requires only a short execution time. A parameter identification program based on the least squares curve fitting method and the Gauss Newton gradient algorithm is developed to determine the parameter values of the gunner model. Thus, a systematic procedure exists for identifying model parameters for a given antiaircraft tracking task. Model predictions of tracking errors are compared with human tracking data obtained from manned simulation experiments. Model predictions are in excellent agreement with the empirical data for several flyby and maneuvering target trajectories.

A Box-Cox normal model for response times

NARCIS (Netherlands)

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

2009-01-01

The log-transform has been a convenient choice in response time modelling on test items. However, motivated by a dataset of the Medical College Admission Test where the lognormal model violated the normality assumption, the possibilities of the broader class of Box–Cox transformations for response

Artificial emotional model based on finite state machine

Institute of Scientific and Technical Information of China (English)

MENG Qing-mei; WU Wei-guo

2008-01-01

According to the basic emotional theory, the artificial emotional model based on the finite state machine(FSM) was presented. In finite state machine model of emotion, the emotional space included the basic emotional space and the multiple emotional spaces. The emotion-switching diagram was defined and transition function was developed using Markov chain and linear interpolation algorithm. The simulation model was built using Stateflow toolbox and Simulink toolbox based on the Matlab platform.And the model included three subsystems: the input one, the emotion one and the behavior one. In the emotional subsystem, the responses of different personalities to the external stimuli were described by defining personal space. This model takes states from an emotional space and updates its state depending on its current state and a state of its input (also a state-emotion). The simulation model realizes the process of switching the emotion from the neutral state to other basic emotions. The simulation result is proved to correspond to emotion-switching law of human beings.

Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

Science.gov (United States)

Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

2016-02-19

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

Modeling of demand response in electricity markets : effects of price elasticity

International Nuclear Information System (INIS)

Banda, E.C.; Tuan, L.A.

2007-01-01

A design mechanism for the optimal participation of customer load in electricity markets was presented. In particular, this paper presented a modified market model for the optimal procurement of interruptible loads participating in day-ahead electricity markets. The proposed model considers the effect of price elasticity and demand-response functions. The objective was to determine the role that price elasticity plays in electricity markets. The simulation model can help the Independent System Operator (ISO) identify customers offering the lowest price of interruptible loads and load flow patterns that avoid problems associated with transmission congestion and transmission losses. Various issues associated with procurement of demand-response offerings such as advance notification, locational aspect of load, and power factor of the loads, were considered. It was shown that demand response can mitigate price volatility by allowing the ISO to maintain operating reserves during peak load periods. It was noted that the potential benefits of the demand response program would be reduced when price elasticity of demand is taken into account. This would most likely occur in actual developed open electricity markets, such as Nordpool. This study was based on the CIGRE 32-bus system, which represents the Swedish high voltage power system. It was modified for this study to include a broad range of customer characteristics. 18 refs., 2 tabs., 14 figs

Identification of estrogen responsive genes using esophageal squamous cell carcinoma (ESCC) as a model

KAUST Repository

Essack, Magbubah

2012-10-26

Background: Estrogen therapy has positively impact the treatment of several cancers, such as prostate, lung and breast cancers. Moreover, several groups have reported the importance of estrogen induced gene regulation in esophageal cancer (EC). This suggests that there could be a potential for estrogen therapy for EC. The efficient design of estrogen therapies requires as complete as possible list of genes responsive to estrogen. Our study develops a systems biology methodology using esophageal squamous cell carcinoma (ESCC) as a model to identify estrogen responsive genes. These genes, on the other hand, could be affected by estrogen therapy in ESCC.Results: Based on different sources of information we identified 418 genes implicated in ESCC. Putative estrogen responsive elements (EREs) mapped to the promoter region of the ESCC genes were used to initially identify candidate estrogen responsive genes. EREs mapped to the promoter sequence of 30.62% (128/418) of ESCC genes of which 43.75% (56/128) are known to be estrogen responsive, while 56.25% (72/128) are new candidate estrogen responsive genes. EREs did not map to 290 ESCC genes. Of these 290 genes, 50.34% (146/290) are known to be estrogen responsive. By analyzing transcription factor binding sites (TFBSs) in the promoters of the 202 (56+146) known estrogen responsive ESCC genes under study, we found that their regulatory potential may be characterized by 44 significantly over-represented co-localized TFBSs (cTFBSs). We were able to map these cTFBSs to promoters of 32 of the 72 new candidate estrogen responsive ESCC genes, thereby increasing confidence that these 32 ESCC genes are responsive to estrogen since their promoters contain both: a/mapped EREs, and b/at least four cTFBSs characteristic of ESCC genes that are responsive to estrogen. Recent publications confirm that 47% (15/32) of these 32 predicted genes are indeed responsive to estrogen.Conclusion: To the best of our knowledge our study is the first

Identification of estrogen responsive genes using esophageal squamous cell carcinoma (ESCC) as a model

KAUST Repository

Essack, Magbubah; MacPherson, Cameron Ross; Schmeier, Sebastian; Bajic, Vladimir B.

2012-01-01

Background: Estrogen therapy has positively impact the treatment of several cancers, such as prostate, lung and breast cancers. Moreover, several groups have reported the importance of estrogen induced gene regulation in esophageal cancer (EC). This suggests that there could be a potential for estrogen therapy for EC. The efficient design of estrogen therapies requires as complete as possible list of genes responsive to estrogen. Our study develops a systems biology methodology using esophageal squamous cell carcinoma (ESCC) as a model to identify estrogen responsive genes. These genes, on the other hand, could be affected by estrogen therapy in ESCC.Results: Based on different sources of information we identified 418 genes implicated in ESCC. Putative estrogen responsive elements (EREs) mapped to the promoter region of the ESCC genes were used to initially identify candidate estrogen responsive genes. EREs mapped to the promoter sequence of 30.62% (128/418) of ESCC genes of which 43.75% (56/128) are known to be estrogen responsive, while 56.25% (72/128) are new candidate estrogen responsive genes. EREs did not map to 290 ESCC genes. Of these 290 genes, 50.34% (146/290) are known to be estrogen responsive. By analyzing transcription factor binding sites (TFBSs) in the promoters of the 202 (56+146) known estrogen responsive ESCC genes under study, we found that their regulatory potential may be characterized by 44 significantly over-represented co-localized TFBSs (cTFBSs). We were able to map these cTFBSs to promoters of 32 of the 72 new candidate estrogen responsive ESCC genes, thereby increasing confidence that these 32 ESCC genes are responsive to estrogen since their promoters contain both: a/mapped EREs, and b/at least four cTFBSs characteristic of ESCC genes that are responsive to estrogen. Recent publications confirm that 47% (15/32) of these 32 predicted genes are indeed responsive to estrogen.Conclusion: To the best of our knowledge our study is the first

The influence of model parameters on catchment-response

International Nuclear Information System (INIS)

Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.

2002-01-01

This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)

Surrogate based approaches to parameter inference in ocean models

KAUST Repository

Knio, Omar

2016-01-06

This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.

Surrogate based approaches to parameter inference in ocean models

KAUST Repository

Knio, Omar

2016-01-01

This talk discusses the inference of physical parameters using model surrogates. Attention is focused on the use of sampling schemes to build suitable representations of the dependence of the model response on uncertain input data. Non-intrusive spectral projections and regularized regressions are used for this purpose. A Bayesian inference formalism is then applied to update the uncertain inputs based on available measurements or observations. To perform the update, we consider two alternative approaches, based on the application of Markov Chain Monte Carlo methods or of adjoint-based optimization techniques. We outline the implementation of these techniques to infer dependence of wind drag, bottom drag, and internal mixing coefficients.

Study of the dosimetric response of Gallium Nitride (GaN): modeling, simulation and characterization on radiotherapy

International Nuclear Information System (INIS)

Wang, Ruoxi

2015-01-01

The work in this thesis has the objective to increase the measurement precision of the dosimetry based on the Gallium Nitride (GaN) transducer and develop its applications on radiotherapy. The study includes the aspects of modeling, simulation and characterization of this response in external radiotherapy and brachytherapy. In modeling, we have proposed two approaches to model the GaN transducer's response in external radiotherapy. For the first approach, a model has been built based on experimental data, while separating the primary and scattering component of the beam. For the second approach, we have adopted a response model initially developed for the silicon diodes for the GaN radioluminescent transducer. We have also proposed an original concept of bi-media dosimetry which evaluates the dose in tissue according to different responses from two media without prior information on the conditions of irradiation. This concept has been shown by Monte Carlo simulation. Moreover, for High Dose Rate brachytherapy, the response of GaN transducer irradiated by iridium 192 and cobalt 60 sources has been evaluated by Monte Carlo simulation and confirmed by the measurements. Studies on the property characterization of GaN radioluminescent transducer has been carried out with these sources as well. An instrumented phantom prototype with GaN probe has been developed for the HDR brachytherapy quality control. It allows a real-time verification of the physics parameters of a treatment (source dwell position, source dwell time, source activity). (author) [fr

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

Science.gov (United States)

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

2017-01-01

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

Empirical Model Development for Predicting Shock Response on Composite Materials Subjected to Pyroshock Loading

Science.gov (United States)

Gentz, Steven J.; Ordway, David O; Parsons, David S.; Garrison, Craig M.; Rodgers, C. Steven; Collins, Brian W.

2015-01-01

The NASA Engineering and Safety Center (NESC) received a request to develop an analysis model based on both frequency response and wave propagation analyses for predicting shock response spectrum (SRS) on composite materials subjected to pyroshock loading. The model would account for near-field environment (approx. 9 inches from the source) dominated by direct wave propagation, mid-field environment (approx. 2 feet from the source) characterized by wave propagation and structural resonances, and far-field environment dominated by lower frequency bending waves in the structure. This report documents the outcome of the assessment.

A physiologically based nonhomogeneous Poisson counter model of visual identification

DEFF Research Database (Denmark)

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

2018-01-01

A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects that are ......A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects...... that mimicked the dynamics of receptive field selectivity as found in neurophysiological studies. Furthermore, the initial sensory response yielded theoretical hazard rate functions that closely resembled empirically estimated ones. Finally, supplied with a Naka-Rushton type contrast gain control, the model...

Simulating Durum Wheat (Triticum turgidum L. Response to Root Zone Salinity based on Statistics and Macroscopic Models

Directory of Open Access Journals (Sweden)

Vahid Reza Jalali

2017-10-01

Full Text Available Introduction Salinity as an abiotic stress can cause excessive disturbance for seed germination and plant sustainable production. Salinity with three different mechanisms of osmotic potential reduction, ionic toxicity and disturbance of plant nutritional balance, can reduce performance of the final product. Planning for optimal use of available water and saline water with poor quality in agricultural activities is of great importance. Wheat is one of the eight main food sources including rice, corn, sugar beet, cattle, sorghum, millet and cassava which provide 70-90% of all calories and 66-90% of the protein consumed in developing countries. Durum wheat (Triticum turgidum L. is an important crop grows in some arid and semi-arid areas of the world such as Middle East and North Africa. In these regions, in addition to soil salinity, sharp decline in rainfall and a sharp drop in groundwater levels in recent years has emphasized on the efficient use of limited soil and water resources. Consequently, in order to use brackish water for agricultural productions, it is required to analyze its quantitative response to salinity stress by simulation models in those regions. The objective of this study is to assess the capability of statistics and macro-simulation models of yield in saline conditions. Materials and methods In this study, two general approach of simulation includes process-physical models and statistical-experimental models were investigated. For this purpose, in order to quantify the salinity effect on seed relative yield of durum wheat (Behrang Variety at different levels of soil salinity, process-physical models of Maas & Hoffman, van Genuchten & Hoffman, Dirksen et al. and Homaee et al. models were used. Also, statistical-experimental models of Modified Gompertz Function, Bi-Exponential Function and Modified Weibull Function were used too. In order to get closer to real conditions of growth circumstances in saline soils, a natural saline

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

Directory of Open Access Journals (Sweden)

Johan D Carlin

2017-07-01

Full Text Available 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.

Influence of tyre-road contact model on vehicle vibration response

Science.gov (United States)

Múčka, Peter; Gagnon, Louis

2015-09-01

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

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

International Nuclear Information System (INIS)

Sutheerawatthana, Pitch; Minato, Takayuki

2010-01-01

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

ANN Model-Based Simulation of the Runoff Variation in Response to Climate Change on the Qinghai-Tibet Plateau, China

Directory of Open Access Journals (Sweden)

Chang Juan

2017-01-01

Full Text Available Precisely quantitative assessments of stream flow response to climatic change and permafrost thawing are highly challenging and urgent in cold regions. However, due to the notably harsh environmental conditions, there is little field monitoring data of runoff in permafrost regions, which has limited the development of physically based models in these regions. To identify the impacts of climate change in the runoff process in the Three-River Headwater Region (TRHR on the Qinghai-Tibet Plateau, two artificial neural network (ANN models, one with three input variables (previous runoff, air temperature, and precipitation and another with two input variables (air temperature and precipitation only, were developed to simulate and predict the runoff variation in the TRHR. The results show that the three-input variable ANN model has a superior real-time prediction capability and performs well in the simulation and forecasting of the runoff variation in the TRHR. Under the different scenarios conditions, the forecasting results of ANN model indicated that climate change has a great effect on the runoff processes in the TRHR. The results of this study are of practical significance for water resources management and the evaluation of the impacts of climatic change on the hydrological regime in long-term considerations.

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

Science.gov (United States)

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

2013-01-01

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

Projective Item Response Model for Test-Independent Measurement

Science.gov (United States)

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

2012-01-01

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

Uncertain hybrid model for the response calculation of an alternator

International Nuclear Information System (INIS)

Kuczkowiak, Antoine

2014-01-01

The complex structural dynamic behavior of alternator must be well understood in order to insure their reliable and safe operation. The numerical model is however difficult to construct mainly due to the presence of a high level of uncertainty. The objective of this work is to provide decision support tools in order to assess the vibratory levels in operation before to restart the alternator. Based on info-gap theory, a first decision support tool is proposed: the objective here is to assess the robustness of the dynamical response to the uncertain modal model. Based on real data, the calibration of an info-gap model of uncertainty is also proposed in order to enhance its fidelity to reality. Then, the extended constitutive relation error is used to expand identified mode shapes which are used to assess the vibratory levels. The robust expansion process is proposed in order to obtain robust expanded mode shapes to parametric uncertainties. In presence of lack-of knowledge, the trade-off between fidelity-to-data and robustness-to-uncertainties which expresses that robustness improves as fidelity deteriorates is emphasized on an industrial structure by using both reduced order model and surrogate model techniques. (author)

The Effects of Recreation Experience, Environmental Attitude, and Biospheric Value on the Environmentally Responsible Behavior of Nature-Based Tourists

Science.gov (United States)

Lee, Tsung Hung; Jan, Fen-Hauh

2015-07-01

The scientific understanding of the recreation experience and the environmentally responsible behavior of nature-based tourists is limited. This study examines the relationship among the recreation experience, environmental attitude, biospheric value, and the general and site-specific environmentally responsible behavior of nature-based tourists in Taomi, Liuqiu Island, and Aowanda and Najenshan in Taiwan. A total of 1342 usable questionnaires were collected for this study. The empirical results indicate that the recreation experience influences biospheric value and environmental attitude; subsequently, it then indirectly influences the general and site-specific environmentally responsible behavior of nature-based tourists. Our theoretical behavioral model elucidates previously proposed but unexamined behavioral models among nature-based tourists, and it offers a theoretical framework for researchers, decision makers, managers, and tourists in the field of nature-based tourism. We conclude that when an individual participates in nature-based tourism as described here, these recreation experiences strengthen their environmental attitude and biospheric value, and consequently increase their engagement in both general and site-specific environmentally responsible behaviors.

The effects of recreation experience, environmental attitude, and biospheric value on the environmentally responsible behavior of nature-based tourists.

Science.gov (United States)

Lee, Tsung Hung; Jan, Fen-Hauh

2015-07-01

The scientific understanding of the recreation experience and the environmentally responsible behavior of nature-based tourists is limited. This study examines the relationship among the recreation experience, environmental attitude, biospheric value, and the general and site-specific environmentally responsible behavior of nature-based tourists in Taomi, Liuqiu Island, and Aowanda and Najenshan in Taiwan. A total of 1342 usable questionnaires were collected for this study. The empirical results indicate that the recreation experience influences biospheric value and environmental attitude; subsequently, it then indirectly influences the general and site-specific environmentally responsible behavior of nature-based tourists. Our theoretical behavioral model elucidates previously proposed but unexamined behavioral models among nature-based tourists, and it offers a theoretical framework for researchers, decision makers, managers, and tourists in the field of nature-based tourism. We conclude that when an individual participates in nature-based tourism as described here, these recreation experiences strengthen their environmental attitude and biospheric value, and consequently increase their engagement in both general and site-specific environmentally responsible behaviors.

Bayesian Dimensionality Assessment for the Multidimensional Nominal Response Model

Directory of Open Access Journals (Sweden)

Javier Revuelta

2017-06-01

Full Text Available This article introduces Bayesian estimation and evaluation procedures for the multidimensional nominal response model. The utility of this model is to perform a nominal factor analysis of items that consist of a finite number of unordered response categories. The key aspect of the model, in comparison with traditional factorial model, is that there is a slope for each response category on the latent dimensions, instead of having slopes associated to the items. The extended parameterization of the multidimensional nominal response model requires large samples for estimation. When sample size is of a moderate or small size, some of these parameters may be weakly empirically identifiable and the estimation algorithm may run into difficulties. We propose a Bayesian MCMC inferential algorithm to estimate the parameters and the number of dimensions underlying the multidimensional nominal response model. Two Bayesian approaches to model evaluation were compared: discrepancy statistics (DIC, WAICC, and LOO that provide an indication of the relative merit of different models, and the standardized generalized discrepancy measure that requires resampling data and is computationally more involved. A simulation study was conducted to compare these two approaches, and the results show that the standardized generalized discrepancy measure can be used to reliably estimate the dimensionality of the model whereas the discrepancy statistics are questionable. The paper also includes an example with real data in the context of learning styles, in which the model is used to conduct an exploratory factor analysis of nominal data.

A Standardized Generalized Dimensionality Discrepancy Measure and a Standardized Model-Based Covariance for Dimensionality Assessment for Multidimensional Models

Science.gov (United States)

Levy, Roy; Xu, Yuning; Yel, Nedim; Svetina, Dubravka

2015-01-01

The standardized generalized dimensionality discrepancy measure and the standardized model-based covariance are introduced as tools to critique dimensionality assumptions in multidimensional item response models. These tools are grounded in a covariance theory perspective and associated connections between dimensionality and local independence.…

Conceptual Framework for Agent-Based Modeling of Customer-Oriented Supply Networks

OpenAIRE

Solano-Vanegas , Clara ,; Carrillo-Ramos , Angela; Montoya-Torres , Jairo ,

2015-01-01

Part 3: Collaboration Frameworks; International audience; Supply Networks (SN) are complex systems involving the interaction of different actors, very often, with different objectives and goals. Among the different existing modeling approaches, agent-based systems can properly represent the autonomous behavior of SN links and, simultaneously, observe the general response of the system as a result of individual actions. Most of research using agent-based modeling in SN focuses on production is...

TESS-based dose-response using pediatric clonidine exposures.

Science.gov (United States)

Benson, Blaine E; Spyker, Daniel A; Troutman, William G; Watson, William A

2006-06-01

The toxic and lethal doses of clonidine in children are unclear. This study was designed to determine whether data from the American Association of Poison Control Centers Toxic Exposure Surveillance System (TESS) could be utilized to determine a dose-response relationship for pediatric clonidine exposure. 3,458 single-substance clonidine exposures in children TESS from January 2000 through December 2003 were examined. Dose ingested, age, and medical outcome were available for 1550 cases. Respiratory arrest cases (n = 8) were classified as the most severe of the medical outcome categories (Arrest, Major, Moderate, Mild, and No effect). Exposures reported as a "taste or lick" (n = 51) were included as a dose of 1/10 of the dosage form involved. Dose ranged from 0.4 to 1980 (median 13) microg/kg. Weight was imputed based on a quadratic estimate of weight for age. Dose certainty was coded as exact (26% of cases) or not exact (74%). Medical outcome (response) was examined via logistic regression using SAS JMP (release 5.1). The logistic model describing medical outcome (P TESS data can provide the basis for a statistically sound description of dose-response for pediatric clonidine poisoning exposures.

A Physiologically Based, Multi-Scale Model of Skeletal Muscle Structure and Function

Science.gov (United States)

Röhrle, O.; Davidson, J. B.; Pullan, A. J.

2012-01-01

Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle’s response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modeling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle’s response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modeling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibers and their grouping. Together with a well-established model of motor-unit recruitment, the electro-physiological behavior of single muscle fibers within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenization. The effect of homogenization has been investigated by varying the number of embedded skeletal muscle fibers and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the tibialis anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modeling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behavior ranging from motor-unit recruitment to force generation and fatigue. PMID:22993509

A physiologically based, multi-scale model of skeletal muscle structure and function

Directory of Open Access Journals (Sweden)

Oliver eRöhrle

2012-09-01

Full Text Available Models of skeletal muscle can be classified as phenomenological or biophysical. Phenomenological models predict the muscle's response to a specified input based on experimental measurements. Prominent phenomenological models are the Hill-type muscle models, which have been incorporated into rigid-body modelling frameworks, and three-dimensional continuum-mechanical models. Biophysically based models attempt to predict the muscle's response as emerging from the underlying physiology of the system. In this contribution, the conventional biophysically based modelling methodology is extended to include several structural and functional characteristics of skeletal muscle. The result is a physiologically based, multi-scale skeletal muscle finite element model that is capable of representing detailed, geometrical descriptions of skeletal muscle fibres and their grouping. Together with a well-established model of motor unit recruitment, the electro-physiological behaviour of single muscle fibres within motor units is computed and linked to a continuum-mechanical constitutive law. The bridging between the cellular level and the organ level has been achieved via a multi-scale constitutive law and homogenisation. The effect of homogenisation has been investigated by varying the number of embedded skeletal muscle fibres and/or motor units and computing the resulting exerted muscle forces while applying the same excitatory input. All simulations were conducted using an anatomically realistic finite element model of the Tibialis Anterior muscle. Given the fact that the underlying electro-physiological cellular muscle model is capable of modelling metabolic fatigue effects such as potassium accumulation in the T-tubular space and inorganic phosphate build-up, the proposed framework provides a novel simulation-based way to investigate muscle behaviour ranging from motor unit recruitment to force generation and fatigue.

Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

NARCIS (Netherlands)

Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco; Asseng, Senthold; Baranowski, Piotr; Basso, Bruno; Bodin, Per; Buis, Samuel; Cammarano, Davide; Deligios, Paola; Destain, Marie France; Dumont, Benjamin; Ewert, Frank; Ferrise, Roberto; François, Louis; Gaiser, Thomas; Hlavinka, Petr; Jacquemin, Ingrid; Kersebaum, Kurt Christian; Kollas, Chris; Krzyszczak, Jaromir; Lorite, Ignacio J.; Minet, Julien; Minguez, M.I.; Montesino, Manuel; Moriondo, Marco; Müller, Christoph; Nendel, Claas; Öztürk, Isik; Perego, Alessia; Rodríguez, Alfredo; Ruane, Alex C.; Ruget, Françoise; Sanna, Mattia; Semenov, Mikhail A.; Slawinski, Cezary; Stratonovitch, Pierre; Supit, Iwan; Waha, Katharina; Wang, Enli; Wu, Lianhai; Zhao, Zhigan; Rötter, Reimund P.

2018-01-01

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in

A Model of Consumer Response to Over-the-Counter Drug Advertising: Antecedents and Influencing Factors.

Science.gov (United States)

Huh, Jisu; Delorme, Denise E; Reid, Leonard N

2016-01-01

Given the importance of over-the-counter (OTC) drugs in the health care marketplace and lack of systematic research on OTC drug advertising (OTCA) effects, this study tested a theory-based, product category-specific OTCA effects model. Structural equation modeling analysis of data for 1 OTC drug category, analgesics, supported the proposed model, explaining the OTCA effect process from key consumer antecedents to ad involvement, from ad involvement to ad attention, from ad attention to cognitive responses, then to affective/evaluative responses, leading to the final behavioral outcome. Several noteworthy patterns also emerged: (a) Product involvement was directly linked to ad attention, rather than exerting an indirect influence through ad involvement; (b) ad attention was significantly related to both cognitive and affective/evaluative responses to different degrees, with stronger links to cognitive responses; and (c) ad-prompted actions were influenced by both ad trust and ad attitude.

Functionally unidimensional item response models for multivariate binary data

DEFF Research Database (Denmark)

Ip, Edward; Molenberghs, Geert; Chen, Shyh-Huei

2013-01-01

The problem of fitting unidimensional item response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that have a strong dimension but also contain minor nuisance dimensions. Fitting a unidimensional model to such multidimensio......The problem of fitting unidimensional item response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that have a strong dimension but also contain minor nuisance dimensions. Fitting a unidimensional model...... to such multidimensional data is believed to result in ability estimates that represent a combination of the major and minor dimensions. We conjecture that the underlying dimension for the fitted unidimensional model, which we call the functional dimension, represents a nonlinear projection. In this article we investigate...... tool. An example regarding a construct of desire for physical competency is used to illustrate the functional unidimensional approach....

Mesoscale Modelling of the Response of Aluminas

International Nuclear Information System (INIS)

Bourne, N. K.

2006-01-01

The response of polycrystalline alumina to shock is not well addressed. There are several operating mechanisms that only hypothesized which results in models which are empirical. A similar state of affairs in reactive flow modelling led to the development of mesoscale representations of the flow to illuminate operating mechanisms. In this spirit, a similar effort is undergone for a polycrystalline alumina. Simulations are conducted to observe operating mechanisms at the micron scale. A method is then developed to extend the simulations to meet response at the continuum level where measurements are made. The approach is validated by comparison with continuum experiments. The method and results are presented, and some of the operating mechanisms are illuminated by the observed response

Plasma equilibrium response modelling and validation on JT-60U

International Nuclear Information System (INIS)

Lister, J.B.; Sharma, A.; Limebeer, D.J.N.; Wainwright, J.P.; Nakamura, Y.; Yoshino, R.

2002-01-01

A systematic procedure to identify the plasma equilibrium response to the poloidal field coil voltages has been applied to the JT-60U tokamak. The required response was predicted with a high accuracy by a state-space model derived from first principles. The ab initio derivation of linearized plasma equilibrium response models is re-examined using an approach standard in analytical mechanics. A symmetric formulation is naturally obtained, removing a previous weakness in such models. RZIP, a rigid current distribution model, is re-derived using this approach and is compared with the new experimental plasma equilibrium response data obtained from Ohmic and neutral beam injection discharges in the JT-60U tokamak. In order to remove any bias from the comparison between modelled and measured plasma responses, the electromagnetic response model without plasma was first carefully tuned against experimental data, using a parametric approach, for which different cost functions for quantifying model agreement were explored. This approach additionally provides new indications of the accuracy to which various plasma parameters are known, and to the ordering of physical effects. Having taken these precautions when tuning the plasmaless model, an empirical estimate of the plasma self-inductance, the plasma resistance and its radial derivative could be established and compared with initial assumptions. Off-line tuning of the JT-60U controller is presented as an example of the improvements which might be obtained by using such a model of the plasma equilibrium response. (author)

A quantitative model to assess Social Responsibility in Environmental Science and Technology.

Science.gov (United States)

Valcárcel, M; Lucena, R

2014-01-01

The awareness of the impact of human activities in society and environment is known as "Social Responsibility" (SR). It has been a topic of growing interest in many enterprises since the fifties of the past Century, and its implementation/assessment is nowadays supported by international standards. There is a tendency to amplify its scope of application to other areas of the human activities, such as Research, Development and Innovation (R + D + I). In this paper, a model of quantitative assessment of Social Responsibility in Environmental Science and Technology (SR EST) is described in detail. This model is based on well established written standards as the EFQM Excellence model and the ISO 26000:2010 Guidance on SR. The definition of five hierarchies of indicators, the transformation of qualitative information into quantitative data and the dual procedure of self-evaluation and external evaluation are the milestones of the proposed model, which can be applied to Environmental Research Centres and institutions. In addition, a simplified model that facilitates its implementation is presented in the article. © 2013 Elsevier B.V. All rights reserved.

Process-based models are required to manage ecological systems in a changing world

Science.gov (United States)

K. Cuddington; M.-J. Fortin; L.R. Gerber; A. Hastings; A. Liebhold; M. OConnor; C. Ray

2013-01-01

Several modeling approaches can be used to guide management decisions. However, some approaches are better fitted than others to address the problem of prediction under global change. Process-based models, which are based on a theoretical understanding of relevant ecological processes, provide a useful framework to incorporate specific responses to altered...

Psychological first-aid training for paraprofessionals: a systems-based model for enhancing capacity of rural emergency responses.

Science.gov (United States)

McCabe, O Lee; Perry, Charlene; Azur, Melissa; Taylor, Henry G; Bailey, Mark; Links, Jonathan M

2011-08-01

consider LHDs, FBOs, and AHCs as partners to work effectively within the span of a six-month period to design, promote, conduct, and evaluate a model of capacity/capability building for public mental health emergency response based on a professional "extender" rationale. Moreover, consistently high levels of perceived self-efficacy as PFA responders can be achieved with lay members of the community who receive a specially-designed, one-day training program in crisis intervention and referral strategies for disaster survivors.

Multi-wheat-model ensemble responses to interannual climatic variability

DEFF Research Database (Denmark)

Ruane, A C; Hudson, N I; Asseng, S

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...

Variance-based sensitivity indices for models with dependent inputs

International Nuclear Information System (INIS)

Mara, Thierry A.; Tarantola, Stefano

2012-01-01

Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

Can agent based models effectively reduce fisheries management implementation uncertainty?

Science.gov (United States)

Drexler, M.

2016-02-01

Uncertainty is an inherent feature of fisheries management. Implementation uncertainty remains a challenge to quantify often due to unintended responses of users to management interventions. This problem will continue to plague both single species and ecosystem based fisheries management advice unless the mechanisms driving these behaviors are properly understood. Equilibrium models, where each actor in the system is treated as uniform and predictable, are not well suited to forecast the unintended behaviors of individual fishers. Alternatively, agent based models (AMBs) can simulate the behaviors of each individual actor driven by differing incentives and constraints. This study evaluated the feasibility of using AMBs to capture macro scale behaviors of the US West Coast Groundfish fleet. Agent behavior was specified at the vessel level. Agents made daily fishing decisions using knowledge of their own cost structure, catch history, and the histories of catch and quota markets. By adding only a relatively small number of incentives, the model was able to reproduce highly realistic macro patterns of expected outcomes in response to management policies (catch restrictions, MPAs, ITQs) while preserving vessel heterogeneity. These simulations indicate that agent based modeling approaches hold much promise for simulating fisher behaviors and reducing implementation uncertainty. Additional processes affecting behavior, informed by surveys, are continually being added to the fisher behavior model. Further coupling of the fisher behavior model to a spatial ecosystem model will provide a fully integrated social, ecological, and economic model capable of performing management strategy evaluations to properly consider implementation uncertainty in fisheries management.

System behaviour modelling for demand response provision in a smart grid

International Nuclear Information System (INIS)

Dave, Saraansh; Sooriyabandara, Mahesh; Yearworth, Mike

2013-01-01

While pilot projects in the smart grid domain have abounded through public and private efforts, there is still uncertainty in identifying effective business models for the smart grid. In this paper we take the view of a new entrant in this market acting as a third party provider of demand response. New entrants are a key player in emerging technological domains but simulation and policy analysis from this perspective have not been forthcoming. We present a novel approach for evaluating business models within a regulatory context and avoid committing to specific technical solutions but instead embark on a parameter exploration through simple yet insightful agent-based models. Our simulations analyse the impact of system performance by three key variables; participant population size, household flexibility in terms of the maximum number of DR events allowed and size of load shifting/shedding available. The simulations indicate that benefits of avoided capital investment leads to valuing a participating household at approximately £1800 over a 20 year period. These results show how mandated infrastructure influenced by policy can affect the value proposition of a demand response service and provide a useful reference for system level parameter requirements. With weak business models, policy decisions can be crucial in providing the impetus needed to spur growth in this market. - Author-Highlights: • We model a demand response (DR) system to analyse interdependence of parameters. • Parameters analysed are number and flexibility of households and size of load shedding. • Challenges in providing a reliable DR service are explored. • A novel approach to evaluate business models for a DR service provider is presented. • The approach simultaneously evaluates business models in a regulatory context

A model for photothermal responses of flowering in rice. II. Model evaluation.

NARCIS (Netherlands)

Yin, X.; Kropff, M.J.; Nakagawa, H.; Horie, T.; Goudriaan, J.

1997-01-01

A detailed nonlinear model, the 3s-Beta model, for photothermal responses of flowering in rice (Oryza sativa L.) was evaluated for predicting rice flowering date in field conditions. This model was compared with other three models: a three-plane linear model and two nonlinear models, viz, the

On a problematic procedure to manipulate response biases in recognition experiments: the case of "implied" base rates.

Science.gov (United States)

Bröder, Arndt; Malejka, Simone

2017-07-01

The experimental manipulation of response biases in recognition-memory tests is an important means for testing recognition models and for estimating their parameters. The textbook manipulations for binary-response formats either vary the payoff scheme or the base rate of targets in the recognition test, with the latter being the more frequently applied procedure. However, some published studies reverted to implying different base rates by instruction rather than actually changing them. Aside from unnecessarily deceiving participants, this procedure may lead to cognitive conflicts that prompt response strategies unknown to the experimenter. To test our objection, implied base rates were compared to actual base rates in a recognition experiment followed by a post-experimental interview to assess participants' response strategies. The behavioural data show that recognition-memory performance was estimated to be lower in the implied base-rate condition. The interview data demonstrate that participants used various second-order response strategies that jeopardise the interpretability of the recognition data. We thus advice researchers against substituting actual base rates with implied base rates.

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

Science.gov (United States)

Wagatsuma, Nobuhiko; Sakai, Ko

2016-01-01

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

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

Science.gov (United States)

Wagatsuma, Nobuhiko; Sakai, Ko

2017-01-01

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

Multifunctional Analysis of CD4+ T-Cell Response as Immune-Based Model for Tuberculosis Detection

Directory of Open Access Journals (Sweden)

Miriam Lichtner

2015-01-01

Full Text Available Mono- and multifunctional specific CD4+ and CD8+ T-cell responses were evaluated to improve the immune-based detection of active tuberculosis (TB and latent infection (LTBI. We applied flow cytometry to investigate cytokines profile (IFN-γ, TNF-α, and IL-2 of T cells after stimulation with TB antigens in 28 TB-infected subjects (18 active TB and 10 LTBI and 10 uninfected controls. Cytokines production by CD4+ T cells at single-cell levels was higher in TB-infected subjects than uninfected controls P0.45%, it was possible to differentiate TB-infected (>0.45% by uninfected subjects (0.182%. The magnitude of CD8+ T-cell responses showed no differences between active TB and LTBI. Multifunctional CD4+ T-cell responses could have the potential to identify at single time point subjects without TB infection and patients having active or latent TB.

KBERG: KnowledgeBase for Estrogen Responsive Genes

DEFF Research Database (Denmark)

Tang, Suisheng; Zhang, Zhuo; Tan, Sin Lam

2007-01-01

Estrogen has a profound impact on human physiology affecting transcription of numerous genes. To decipher functional characteristics of estrogen responsive genes, we developed KnowledgeBase for Estrogen Responsive Genes (KBERG). Genes in KBERG were derived from Estrogen Responsive Gene Database...... (ERGDB) and were analyzed from multiple aspects. We explored the possible transcription regulation mechanism by capturing highly conserved promoter motifs across orthologous genes, using promoter regions that cover the range of [-1200, +500] relative to the transcription start sites. The motif detection...... is based on ab initio discovery of common cis-elements from the orthologous gene cluster from human, mouse and rat, thus reflecting a degree of promoter sequence preservation during evolution. The identified motifs are linked to transcription factor binding sites based on the TRANSFAC database. In addition...

Grid Integration of Aggregated Demand Response, Part 2: Modeling Demand Response in a Production Cost Model

Energy Technology Data Exchange (ETDEWEB)

Hummon, Marissa [National Renewable Energy Lab. (NREL), Golden, CO (United States); Palchak, David [National Renewable Energy Lab. (NREL), Golden, CO (United States); Denholm, Paul [National Renewable Energy Lab. (NREL), Golden, CO (United States); Jorgenson, Jennie [National Renewable Energy Lab. (NREL), Golden, CO (United States); Olsen, Daniel J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kiliccote, Sila [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Matson, Nance [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rose, Cody [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dudley, Junqiao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Goli, Sasank [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ma, Ookie [U.S. Dept. of Energy, Washington, DC (United States)

2013-12-01

This report is one of a series stemming from the U.S. Department of Energy (DOE) Demand Response and Energy Storage Integration Study. This study is a multi-national-laboratory effort to assess the potential value of demand response (DR) and energy storage to electricity systems with different penetration levels of variable renewable resources and to improve our understanding of associatedmarkets and institutions. This report implements DR resources in the commercial production cost model PLEXOS.

Fluid-structure interaction-based biomechanical perception model for tactile sensing.

Directory of Open Access Journals (Sweden)

Zheng Wang

Full Text Available The reproduced tactile sensation of haptic interfaces usually selectively reproduces a certain object attribute, such as the object's material reflected by vibration and its surface shape by a pneumatic nozzle array. Tactile biomechanics investigates the relation between responses to an external load stimulus and tactile perception and guides the design of haptic interface devices via a tactile mechanism. Focusing on the pneumatic haptic interface, we established a fluid-structure interaction-based biomechanical model of responses to static and dynamic loads and conducted numerical simulation and experiments. This model provides a theoretical basis for designing haptic interfaces and reproducing tactile textures.

Seismic Response Analysis and Test of 1/8 Scale Model for a Spent Fuel Storage Cask

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Han; Park, C. G.; Koo, G. H.; Seo, G. S. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Yeom, S. H. [Chungnam Univ., Daejeon (Korea, Republic of); Choi, B. I.; Cho, Y. D. [Korea Hydro and Nuclear Power Co. Ltd., Daejeon (Korea, Republic of)

2005-07-15

The seismic response tests of a spent fuel dry storage cask model of 1/8 scale are performed for an typical 1940 El-centro and Kobe earthquakes. This report firstly focuses on the data generation by seismic response tests of a free standing storage cask model to check the overturing possibility of a storage cask and the slipping displacement on concrete slab bed. The variations in seismic load magnitude and cask/bed interface friction are considered in tests. The test results show that the model gives an overturning response for an extreme condition only. A FEM model is built for the test model of 1/8 scale spent fuel dry storage cask using available 3D contact conditions in ABAQUS/Explicit. Input load for this analysis is El-centro earthquake, and the friction coefficients are obtained from the test result. Penalty and kinematic contact methods of ABAQUS are used for a mechanical contact formulation. The analysis methods was verified with the rocking angle obtained by seismic response tests. The kinematic contact method with an adequate normal contact stiffness showed a good agreement with tests. Based on the established analysis method for 1/8 scale model, the seismic response analyses of a full scale model are performed for design and beyond design seismic loads.

Gender Responsive Community Based Planning and Budgeting ...

International Development Research Centre (IDRC) Digital Library (Canada)

... Responsive Community Based Planning and Budgeting Tool for Local Governance ... in data collection, and another module that facilitates gender responsive and ... In partnership with UNESCO's Organization for Women in Science for the ...

Understanding variation in ecosystem pulse responses to wetting: Benefits of data-model coupling

Science.gov (United States)

Jenerette, D.

2011-12-01

Metabolic pulses of activity are a common ecological response to intermittently available resources and in water-limited ecosystems these pulses often occur in response to wetting. Net ecosystem CO2 exchange (NEE) in response to episodic wetting events is hypothesized to have a complex trajectory reflecting the distinct responses, or "pulses", of respiration and photosynthesis. To help direct research activities a physiological-based model of whole ecosystem metabolic activity up- and down-regulation was developed to investigate ecosystem energy balance and gas exchange pulse responses following precipitation events. This model was to investigate pulse dynamics from a local network of sites in southern Arizona, a global network of eddy-covariance ecosystem monitoring sites, laboratory incubation studies, and field manipulations. Pulse responses were found to be ubiquitous across ecosystem types. These pulses had a highly variable influence on NEE following wetting, ranging from large net sinks to sources of CO2 to the atmosphere. Much of the variability in pulse responses of NEE could be described through a coupled up- and down-regulation pulse response model. Respiration pulses were hypothesized to occur through a reduction in whole ecosystem activation energy; this model was both useful and corroborated through laboratory incubation studies of soil respiration. Using the Fluxnet eddy-covariance measurement database event specific responses were combined with the pulse model into an event specific twenty-five day net flux calculation. Across all events observed a general net accumulation of CO2 following a precipitation event, with the largest net uptake within deciduous broadleaf forests and smallest within grasslands. NEE pulses favored greater uptake when pre-event ecosystem respiration rates and total precipitation were higher. While the latter was expected, the former adds to previous theory by suggesting a larger net uptake of CO2 when pre-event metabolic

[Unfolding item response model using best-worst scaling].

Science.gov (United States)

Ikehara, Kazuya

2015-02-01

In attitude measurement and sensory tests, the unfolding model is typically used. In this model, response probability is formulated by the distance between the person and the stimulus. In this study, we proposed an unfolding item response model using best-worst scaling (BWU model), in which a person chooses the best and worst stimulus among repeatedly presented subsets of stimuli. We also formulated an unfolding model using best scaling (BU model), and compared the accuracy of estimates between the BU and BWU models. A simulation experiment showed that the BWU modell performed much better than the BU model in terms of bias and root mean square errors of estimates. With reference to Usami (2011), the proposed models were apllied to actual data to measure attitudes toward tardiness. Results indicated high similarity between stimuli estimates generated with the proposed models and those of Usami (2011).

Using item response theory to measure extreme response style in marketing research

NARCIS (Netherlands)

de Jong, Martijn G.; Steenkamp, Jan-Benedict E.M.; Fox, Gerardus J.A.; Baumgartner, Hans

2008-01-01

Extreme response style (ERS) is an important threat to the validity of survey-based marketing research. In this article, the authors present a new item response theory–based model for measuring ERS. This model contributes to the ERS literature in two ways. First, the method improves on existing

An experimentally validated bimorph cantilever model for piezoelectric energy harvesting from base excitations