More Than Just Accuracy: A Novel Method to Incorporate Multiple Test Attributes in Evaluating Diagnostic Tests Including Point of Care Tests.

Science.gov (United States)

Thompson, Matthew; Weigl, Bernhard; Fitzpatrick, Annette; Ide, Nicole

2016-01-01

Current frameworks for evaluating diagnostic tests are constrained by a focus on diagnostic accuracy, and assume that all aspects of the testing process and test attributes are discrete and equally important. Determining the balance between the benefits and harms associated with new or existing tests has been overlooked. Yet, this is critically important information for stakeholders involved in developing, testing, and implementing tests. This is particularly important for point of care tests (POCTs) where tradeoffs exist between numerous aspects of the testing process and test attributes. We developed a new model that multiple stakeholders (e.g., clinicians, patients, researchers, test developers, industry, regulators, and health care funders) can use to visualize the multiple attributes of tests, the interactions that occur between these attributes, and their impacts on health outcomes. We use multiple examples to illustrate interactions between test attributes (test availability, test experience, and test results) and outcomes, including several POCTs. The model could be used to prioritize research and development efforts, and inform regulatory submissions for new diagnostics. It could potentially provide a way to incorporate the relative weights that various subgroups or clinical settings might place on different test attributes. Our model provides a novel way that multiple stakeholders can use to visualize test attributes, their interactions, and impacts on individual and population outcomes. We anticipate that this will facilitate more informed decision making around diagnostic tests.

Three-dimensional simulations of Bingham plastic flows with the multiple-relaxation-time lattice Boltzmann model

OpenAIRE

Song-Gui Chen; Chuan-Hu Zhang; Yun-Tian Feng; Qi-Cheng Sun; Feng Jin

2016-01-01

This paper presents a three-dimensional (3D) parallel multiple-relaxation-time lattice Boltzmann model (MRT-LBM) for Bingham plastics which overcomes numerical instabilities in the simulation of non-Newtonian fluids for the Bhatnagar–Gross–Krook (BGK) model. The MRT-LBM and several related mathematical models are briefly described. Papanastasiou’s modified model is incorporated for better numerical stability. The impact of the relaxation parameters of the model is studied in detail. The MRT-L...

Incorporating direct marketing activity into latent attrition models

NARCIS (Netherlands)

Schweidel, David A.; Knox, George

2013-01-01

When defection is unobserved, latent attrition models provide useful insights about customer behavior and accurate forecasts of customer value. Yet extant models ignore direct marketing efforts. Response models incorporate the effects of direct marketing, but because they ignore latent attrition,

Improved double-multiple streamtube model for the Darrieus-type vertical axis wind turbine

Science.gov (United States)

Berg, D. E.

Double streamtube codes model the curved blade (Darrieus-type) vertical axis wind turbine (VAWT) as a double actuator fish arrangement (one half) and use conservation of momentum principles to determine the forces acting on the turbine blades and the turbine performance. Sandia National Laboratories developed a double multiple streamtube model for the VAWT which incorporates the effects of the incident wind boundary layer, nonuniform velocity between the upwind and downwind sections of the rotor, dynamic stall effects and local blade Reynolds number variations. The theory underlying this VAWT model is described, as well as the code capabilities. Code results are compared with experimental data from two VAWT's and with the results from another double multiple streamtube and a vortex filament code. The effects of neglecting dynamic stall and horizontal wind velocity distribution are also illustrated.

Modeling the Potential Effects of New Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm

Science.gov (United States)

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.

2015-01-01

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health

VNM: An R Package for Finding Multiple-Objective Optimal Designs for the 4-Parameter Logistic Model

OpenAIRE

Hyun, Seung Won; Wong, Weng Kee; Yang, Yarong

2018-01-01

A multiple-objective optimal design is useful for dose-response studies because it can incorporate several objectives at the design stage. Objectives can be of varying interests and a properly constructed multiple-objective optimal design can provide user-specified efficiencies, delivering higher efficiencies for the more important objectives. In this work, we introduce the VNM package written in R for finding 3-objective locally optimal designs for the 4-parameter logistic (4PL) model widely...

Comparison in the calculation of committed effective dose using the ICRP 30 and ICRP 60 models for a repeated incorporation by inhalation of I-125

International Nuclear Information System (INIS)

Carreno P, A.L.; Cortes C, A.; Alonso V, G.; Serrano P, F.

2005-01-01

Presently work, a comparison in the calculation of committed effective dose using the models of the ICRP 30 and those of the ICRP 60 for the analysis of internal dose due to repeated incorporation of I-125 is shown. The estimations of incorporated activity are obtained starting from the proportionate data for an exercise of inter comparison, with which it should be determined the internal dose later on. For to estimate the initial activity incorporated by repeated dose was assumed that this it was given through of multiple individual incorporations which happened in the middle points of the monitoring periods. The results using the models of the ICRP 30 and of the ICRP 60 are compared and the causes of the differences are analyzed. (Author)

A MULTI-RESOLUTION FUSION MODEL INCORPORATING COLOR AND ELEVATION FOR SEMANTIC SEGMENTATION

Directory of Open Access Journals (Sweden)

W. Zhang

2017-05-01

Full Text Available In recent years, the developments for Fully Convolutional Networks (FCN have led to great improvements for semantic segmentation in various applications including fused remote sensing data. There is, however, a lack of an in-depth study inside FCN models which would lead to an understanding of the contribution of individual layers to specific classes and their sensitivity to different types of input data. In this paper, we address this problem and propose a fusion model incorporating infrared imagery and Digital Surface Models (DSM for semantic segmentation. The goal is to utilize heterogeneous data more accurately and effectively in a single model instead of to assemble multiple models. First, the contribution and sensitivity of layers concerning the given classes are quantified by means of their recall in FCN. The contribution of different modalities on the pixel-wise prediction is then analyzed based on visualization. Finally, an optimized scheme for the fusion of layers with color and elevation information into a single FCN model is derived based on the analysis. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset. Comprehensive evaluations demonstrate the potential of the proposed approach.

A New Achiral Linker Reagent for the Incorporation of Multiple Amino Groups Into Oligonucleotides

DEFF Research Database (Denmark)

1997-01-01

The present invention relates to a new functionalized achiral linker reagent for incorporating multiple primary amino groups or reporter groups into oligonucleotides following the phosphoramidite methodology. It is possible to substitute any ribodeoxynucleotide, deoxynucleotide, or nucleotide......-oxyl-2,2,5,5-tetramethylpyrrolidine), TEMPO (N-oxyl-2,2,6,6-tetramethylpiperidine), dinitrophenyl, texas red, tetramethyl rhodamine, 7-nitrobenzo-2-oxa-1-diazole (NBD), or pyrene. The present invention also relates to a solid phase support, e.g. a Controlled Pore Glass (CPG), immobilized linker reagent...

True dose from incorporated activities. Models for internal dosimetry

International Nuclear Information System (INIS)

Breustedt, B.; Eschner, W.; Nosske, D.

2012-01-01

The assessment of doses after incorporation of radionuclides cannot use direct measurements of the doses, as for example dosimetry in external radiation fields. The only observables are activities in the body or in excretions. Models are used to calculate the doses based on the measured activities. The incorporated activities and the resulting doses can vary by more than seven orders of magnitude between occupational and medical exposures. Nevertheless the models and calculations applied in both cases are similar. Since the models for the different applications have been developed independently by ICRP and MIRD different terminologies have been used. A unified terminology is being developed. (orig.)

Incorporating interfacial phenomena in solidification models

Science.gov (United States)

Beckermann, Christoph; Wang, Chao Yang

1994-01-01

A general methodology is available for the incorporation of microscopic interfacial phenomena in macroscopic solidification models that include diffusion and convection. The method is derived from a formal averaging procedure and a multiphase approach, and relies on the presence of interfacial integrals in the macroscopic transport equations. In a wider engineering context, these techniques are not new, but their application in the analysis and modeling of solidification processes has largely been overlooked. This article describes the techniques and demonstrates their utility in two examples in which microscopic interfacial phenomena are of great importance.

High-Strain Rate Failure Modeling Incorporating Shear Banding and Fracture

Science.gov (United States)

2017-11-22

High Strain Rate Failure Modeling Incorporating Shear Banding and Fracture The views, opinions and/or findings contained in this report are those of...SECURITY CLASSIFICATION OF: 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES 12. DISTRIBUTION AVAILIBILITY STATEMENT 6. AUTHORS...Report as of 05-Dec-2017 Agreement Number: W911NF-13-1-0238 Organization: Columbia University Title: High Strain Rate Failure Modeling Incorporating

Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

Science.gov (United States)

Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

2014-08-01

Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

Multiple Model Approaches to Modelling and Control,

DEFF Research Database (Denmark)

on the ease with which prior knowledge can be incorporated. It is interesting to note that researchers in Control Theory, Neural Networks,Statistics, Artificial Intelligence and Fuzzy Logic have more or less independently developed very similar modelling methods, calling them Local ModelNetworks, Operating......, and allows direct incorporation of high-level and qualitative plant knowledge into themodel. These advantages have proven to be very appealing for industrial applications, and the practical, intuitively appealing nature of the framework isdemonstrated in chapters describing applications of local methods...... to problems in the process industries, biomedical applications and autonomoussystems. The successful application of the ideas to demanding problems is already encouraging, but creative development of the basic framework isneeded to better allow the integration of human knowledge with automated learning...

75 FR 20265 - Airworthiness Directives; Liberty Aerospace Incorporated Model XL-2 Airplanes

Science.gov (United States)

2010-04-19

... Office, 1701 Columbia Avenue, College Park, Georgia 30337; telephone: (404) 474-5524; facsimile: (404... Airworthiness Directives; Liberty Aerospace Incorporated Model XL-2 Airplanes AGENCY: Federal Aviation...-08- 05, which applies to certain Liberty Aerospace Incorporated Model XL-2 airplanes. AD 2009-08-05...

A minimal model for multiple epidemics and immunity spreading.

Science.gov (United States)

Sneppen, Kim; Trusina, Ala; Jensen, Mogens H; Bornholdt, Stefan

2010-10-18

Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

The Normative Impact of Consumer Price Expectations for Multiple Brands on Consumer Purchase Behavior

OpenAIRE

Aradhna Krishna

1992-01-01

Empirical research indicates that some consumers form price expectations which may impact their purchase behavior. While literature in operations research has built purchase policy models incorporating uncertain price expectations, these models have been built for commodities. Consumers face an environment with multiple brands. In this paper, we develop a model that incorporates consumer preferences and price expectations for multiple brands as determinants of normative consumer purchase beha...

A comparison of approaches for simultaneous inference of fixed effects for multiple outcomes using linear mixed models

DEFF Research Database (Denmark)

Jensen, Signe Marie; Ritz, Christian

2018-01-01

Longitudinal studies with multiple outcomes often pose challenges for the statistical analysis. A joint model including all outcomes has the advantage of incorporating the simultaneous behavior but is often difficult to fit due to computational challenges. We consider 2 alternative approaches to ......, pairwise fitting shows a larger loss in efficiency than the marginal models approach. Using an alternative to the joint modelling strategy will lead to some but not necessarily a large loss of efficiency for small sample sizes....

Two approaches to incorporate clinical data uncertainty into multiple criteria decision analysis for benefit-risk assessment of medicinal products.

Science.gov (United States)

Wen, Shihua; Zhang, Lanju; Yang, Bo

2014-07-01

The Problem formulation, Objectives, Alternatives, Consequences, Trade-offs, Uncertainties, Risk attitude, and Linked decisions (PrOACT-URL) framework and multiple criteria decision analysis (MCDA) have been recommended by the European Medicines Agency for structured benefit-risk assessment of medicinal products undergoing regulatory review. The objective of this article was to provide solutions to incorporate the uncertainty from clinical data into the MCDA model when evaluating the overall benefit-risk profiles among different treatment options. Two statistical approaches, the δ-method approach and the Monte-Carlo approach, were proposed to construct the confidence interval of the overall benefit-risk score from the MCDA model as well as other probabilistic measures for comparing the benefit-risk profiles between treatment options. Both approaches can incorporate the correlation structure between clinical parameters (criteria) in the MCDA model and are straightforward to implement. The two proposed approaches were applied to a case study to evaluate the benefit-risk profile of an add-on therapy for rheumatoid arthritis (drug X) relative to placebo. It demonstrated a straightforward way to quantify the impact of the uncertainty from clinical data to the benefit-risk assessment and enabled statistical inference on evaluating the overall benefit-risk profiles among different treatment options. The δ-method approach provides a closed form to quantify the variability of the overall benefit-risk score in the MCDA model, whereas the Monte-Carlo approach is more computationally intensive but can yield its true sampling distribution for statistical inference. The obtained confidence intervals and other probabilistic measures from the two approaches enhance the benefit-risk decision making of medicinal products. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

Science.gov (United States)

Walsh, Daniel P.; Norton, Andrew S.; Storm, Daniel J.; Van Deelen, Timothy R.; Heisy, Dennis M.

2018-01-01

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection

Analysis of Product Sampling for New Product Diffusion Incorporating Multiple-Unit Ownership

Directory of Open Access Journals (Sweden)

Zhineng Hu

2014-01-01

Full Text Available Multiple-unit ownership of nondurable products is an important component of sales in many product categories. Based on the Bass model, this paper develops a new model considering the multiple-unit adoptions as a diffusion process under the influence of product sampling. Though the analysis aims to determine the optimal dynamic sampling effort for a firm and the results demonstrate that experience sampling can accelerate the diffusion process, the best time to send free samples is just before the product being launched. Multiple-unit purchasing behavior can increase sales to make more profit for a firm, and it needs more samples to make the product known much better. The local sensitivity analysis shows that the increase of both external coefficients and internal coefficients has a negative influence on the sampling level, but the internal influence on the subsequent multiple-unit adoptions has little significant influence on the sampling. Using the logistic regression along with linear regression, the global sensitivity analysis gives a whole analysis of the interaction of all factors, which manifests the external influence and multiunit purchase rate are two most important factors to influence the sampling level and net present value of the new product, and presents a two-stage method to determine the sampling level.

Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment.

Science.gov (United States)

Shi, Yuan; Lau, Kevin Ka-Lun; Ng, Edward

2017-08-01

Urban air quality serves as an important function of the quality of urban life. Land use regression (LUR) modelling of air quality is essential for conducting health impacts assessment but more challenging in mountainous high-density urban scenario due to the complexities of the urban environment. In this study, a total of 21 LUR models are developed for seven kinds of air pollutants (gaseous air pollutants CO, NO 2 , NO x , O 3 , SO 2 and particulate air pollutants PM 2.5 , PM 10 ) with reference to three different time periods (summertime, wintertime and annual average of 5-year long-term hourly monitoring data from local air quality monitoring network) in Hong Kong. Under the mountainous high-density urban scenario, we improved the traditional LUR modelling method by incorporating wind availability information into LUR modelling based on surface geomorphometrical analysis. As a result, 269 independent variables were examined to develop the LUR models by using the "ADDRESS" independent variable selection method and stepwise multiple linear regression (MLR). Cross validation has been performed for each resultant model. The results show that wind-related variables are included in most of the resultant models as statistically significant independent variables. Compared with the traditional method, a maximum increase of 20% was achieved in the prediction performance of annual averaged NO 2 concentration level by incorporating wind-related variables into LUR model development. Copyright © 2017 Elsevier Inc. All rights reserved.

Medicare capitation model, functional status, and multiple comorbidities: model accuracy

Science.gov (United States)

Noyes, Katia; Liu, Hangsheng; Temkin-Greener, Helena

2012-01-01

Objective This study examined financial implications of CMS-Hierarchical Condition Categories (HCC) risk-adjustment model on Medicare payments for individuals with comorbid chronic conditions. Study Design The study used 1992-2000 data from the Medicare Current Beneficiary Survey and corresponding Medicare claims. The pairs of comorbidities were formed based on the prior evidence about possible synergy between these conditions and activities of daily living (ADL) deficiencies and included heart disease and cancer, lung disease and cancer, stroke and hypertension, stroke and arthritis, congestive heart failure (CHF) and osteoporosis, diabetes and coronary artery disease, CHF and dementia. Methods For each beneficiary, we calculated the actual Medicare cost ratio as the ratio of the individual’s annualized costs to the mean annual Medicare cost of all people in the study. The actual Medicare cost ratios, by ADLs, were compared to the HCC ratios under the CMS-HCC payment model. Using multivariate regression models, we tested whether having the identified pairs of comorbidities affects the accuracy of CMS-HCC model predictions. Results The CMS-HCC model underpredicted Medicare capitation payments for patients with hypertension, lung disease, congestive heart failure and dementia. The difference between the actual costs and predicted payments was partially explained by beneficiary functional status and less than optimal adjustment for these chronic conditions. Conclusions Information about beneficiary functional status should be incorporated in reimbursement models since underpaying providers for caring for population with multiple comorbidities may provide severe disincentives for managed care plans to enroll such individuals and to appropriately manage their complex and costly conditions. PMID:18837646

A minimal model for multiple epidemics and immunity spreading.

Directory of Open Access Journals (Sweden)

Kim Sneppen

Full Text Available Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

False discovery rate control incorporating phylogenetic tree increases detection power in microbiome-wide multiple testing.

Science.gov (United States)

Xiao, Jian; Cao, Hongyuan; Chen, Jun

2017-09-15

Next generation sequencing technologies have enabled the study of the human microbiome through direct sequencing of microbial DNA, resulting in an enormous amount of microbiome sequencing data. One unique characteristic of microbiome data is the phylogenetic tree that relates all the bacterial species. Closely related bacterial species have a tendency to exhibit a similar relationship with the environment or disease. Thus, incorporating the phylogenetic tree information can potentially improve the detection power for microbiome-wide association studies, where hundreds or thousands of tests are conducted simultaneously to identify bacterial species associated with a phenotype of interest. Despite much progress in multiple testing procedures such as false discovery rate (FDR) control, methods that take into account the phylogenetic tree are largely limited. We propose a new FDR control procedure that incorporates the prior structure information and apply it to microbiome data. The proposed procedure is based on a hierarchical model, where a structure-based prior distribution is designed to utilize the phylogenetic tree. By borrowing information from neighboring bacterial species, we are able to improve the statistical power of detecting associated bacterial species while controlling the FDR at desired levels. When the phylogenetic tree is mis-specified or non-informative, our procedure achieves a similar power as traditional procedures that do not take into account the tree structure. We demonstrate the performance of our method through extensive simulations and real microbiome datasets. We identified far more alcohol-drinking associated bacterial species than traditional methods. R package StructFDR is available from CRAN. chen.jun2@mayo.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Multiple Indicator Stationary Time Series Models.

Science.gov (United States)

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

Generalized linear longitudinal mixed models with linear covariance structure and multiplicative random effects

DEFF Research Database (Denmark)

Holst, René; Jørgensen, Bent

2015-01-01

The paper proposes a versatile class of multiplicative generalized linear longitudinal mixed models (GLLMM) with additive dispersion components, based on explicit modelling of the covariance structure. The class incorporates a longitudinal structure into the random effects models and retains...... a marginal as well as a conditional interpretation. The estimation procedure is based on a computationally efficient quasi-score method for the regression parameters combined with a REML-like bias-corrected Pearson estimating function for the dispersion and correlation parameters. This avoids...... the multidimensional integral of the conventional GLMM likelihood and allows an extension of the robust empirical sandwich estimator for use with both association and regression parameters. The method is applied to a set of otholit data, used for age determination of fish....

Incorporation of the capillary hysteresis model HYSTR into the numerical code TOUGH

International Nuclear Information System (INIS)

Niemi, A.; Bodvarsson, G.S.; Pruess, K.

1991-11-01

As part of the work performed to model flow in the unsaturated zone at Yucca Mountain Nevada, a capillary hysteresis model has been developed. The computer program HYSTR has been developed to compute the hysteretic capillary pressure -- liquid saturation relationship through interpolation of tabulated data. The code can be easily incorporated into any numerical unsaturated flow simulator. A complete description of HYSTR, including a brief summary of the previous hysteresis literature, detailed description of the program, and instructions for its incorporation into a numerical simulator are given in the HYSTR user's manual (Niemi and Bodvarsson, 1991a). This report describes the incorporation of HYSTR into the numerical code TOUGH (Transport of Unsaturated Groundwater and Heat; Pruess, 1986). The changes made and procedures for the use of TOUGH for hysteresis modeling are documented

Insights on Genomic and Molecular Alterations in Multiple Myeloma and Their Incorporation towards Risk-Adapted Treatment Strategy: Concise Clinical Review

Directory of Open Access Journals (Sweden)

Taiga Nishihori

2017-01-01

Full Text Available Although recent advances in novel treatment approaches and therapeutics have shifted the treatment landscape of multiple myeloma, it remains an incurable plasma cell malignancy. Growing knowledge of the genome and expressed genomic information characterizing the biologic behavior of multiple myeloma continues to accumulate. However, translation and incorporation of vast molecular understanding of complex tumor biology to deliver personalized and precision treatment to cure multiple myeloma have not been successful to date. Our review focuses on current evidence and understanding of myeloma biology with characterization in the context of genomic and molecular alterations. We also discuss future clinical application of the genomic and molecular knowledge, and more translational research is needed to benefit our myeloma patients.

A computational model incorporating neural stem cell dynamics reproduces glioma incidence across the lifespan in the human population.

Directory of Open Access Journals (Sweden)

Roman Bauer

Full Text Available Glioma is the most common form of primary brain tumor. Demographically, the risk of occurrence increases until old age. Here we present a novel computational model to reproduce the probability of glioma incidence across the lifespan. Previous mathematical models explaining glioma incidence are framed in a rather abstract way, and do not directly relate to empirical findings. To decrease this gap between theory and experimental observations, we incorporate recent data on cellular and molecular factors underlying gliomagenesis. Since evidence implicates the adult neural stem cell as the likely cell-of-origin of glioma, we have incorporated empirically-determined estimates of neural stem cell number, cell division rate, mutation rate and oncogenic potential into our model. We demonstrate that our model yields results which match actual demographic data in the human population. In particular, this model accounts for the observed peak incidence of glioma at approximately 80 years of age, without the need to assert differential susceptibility throughout the population. Overall, our model supports the hypothesis that glioma is caused by randomly-occurring oncogenic mutations within the neural stem cell population. Based on this model, we assess the influence of the (experimentally indicated decrease in the number of neural stem cells and increase of cell division rate during aging. Our model provides multiple testable predictions, and suggests that different temporal sequences of oncogenic mutations can lead to tumorigenesis. Finally, we conclude that four or five oncogenic mutations are sufficient for the formation of glioma.

Effect of boron incorporation on the structural and photoluminescence properties of highly-strained InxGa1-xAs/GaAs multiple quantum wells

Directory of Open Access Journals (Sweden)

Qi Wang

2013-07-01

Full Text Available In this research, 5-period highly-strained BInGaAs/GaAs multiple quantum wells (MQWs have been successfully grown at 480-510ºC by LP-MOCVD. Room-temperature photoluminescence (RT-PL measurements of BInGaAs/GaAs MQWs showed the peak wavelength as long as 1.17 μm with full-width at half maximum (FWHM of only 29.5 meV. In addition, a slight blue-shift (∼18 meV of PL peak energy of InxGa1-xAs/GaAs MQWs was observed after boron incorporation. It has been found boron incorporation ( 40%, the positive effect of boron incorporation prevailed, i.e., boron incorporation completely suppressed the thickness undulation and lead to the improvement of PL properties.

Correlations in multiple production on nuclei and Glauber model of multiple scattering

International Nuclear Information System (INIS)

Zoller, V.R.; Nikolaev, N.N.

1982-01-01

Critical analysis of possibility for describing correlation phenomena during multiple production on nuclei within the framework of the Glauber multiple seattering model generalized for particle production processes with Capella, Krziwinski and Shabelsky has been performed. It was mainly concluded that the suggested generalization of the Glauber model gives dependences on Ng(Np) (where Ng-the number of ''grey'' tracess, and Np-the number of protons flying out of nucleus) and, eventually, on #betta# (where #betta#-the number of intranuclear interactions) contradicting experience. Independent of choice of relation between #betta# and Ng(Np) in the model the rapidity corrletor Rsub(eta) is overstated in the central region and understated in the region of nucleus fragmentation. In mean multiplicities these two contradictions of experience are disguised with random compensation and agreement with experience in Nsub(S) (function of Ng) cannot be an argument in favour of the model. It is concluded that eiconal model doesn't permit to quantitatively describe correlation phenomena during the multiple production on nuclei

A neural population model incorporating dopaminergic neurotransmission during complex voluntary behaviors.

Directory of Open Access Journals (Sweden)

Stefan Fürtinger

2014-11-01

Full Text Available Assessing brain activity during complex voluntary motor behaviors that require the recruitment of multiple neural sites is a field of active research. Our current knowledge is primarily based on human brain imaging studies that have clear limitations in terms of temporal and spatial resolution. We developed a physiologically informed non-linear multi-compartment stochastic neural model to simulate functional brain activity coupled with neurotransmitter release during complex voluntary behavior, such as speech production. Due to its state-dependent modulation of neural firing, dopaminergic neurotransmission plays a key role in the organization of functional brain circuits controlling speech and language and thus has been incorporated in our neural population model. A rigorous mathematical proof establishing existence and uniqueness of solutions to the proposed model as well as a computationally efficient strategy to numerically approximate these solutions are presented. Simulated brain activity during the resting state and sentence production was analyzed using functional network connectivity, and graph theoretical techniques were employed to highlight differences between the two conditions. We demonstrate that our model successfully reproduces characteristic changes seen in empirical data between the resting state and speech production, and dopaminergic neurotransmission evokes pronounced changes in modeled functional connectivity by acting on the underlying biological stochastic neural model. Specifically, model and data networks in both speech and rest conditions share task-specific network features: both the simulated and empirical functional connectivity networks show an increase in nodal influence and segregation in speech over the resting state. These commonalities confirm that dopamine is a key neuromodulator of the functional connectome of speech control. Based on reproducible characteristic aspects of empirical data, we suggest a number

Incorporating Social System Dynamics into the Food-Energy-Water System Resilience-Sustainability Modeling Process

Science.gov (United States)

Givens, J.; Padowski, J.; Malek, K.; Guzman, C.; Boll, J.; Adam, J. C.; Witinok-Huber, R.

2017-12-01

In the face of climate change and multi-scalar governance objectives, achieving resilience of food-energy-water (FEW) systems requires interdisciplinary approaches. Through coordinated modeling and management efforts, we study "Innovations in the Food-Energy-Water Nexus (INFEWS)" through a case-study in the Columbia River Basin. Previous research on FEW system management and resilience includes some attention to social dynamics (e.g., economic, governance); however, more research is needed to better address social science perspectives. Decisions ultimately taken in this river basin would occur among stakeholders encompassing various institutional power structures including multiple U.S. states, tribal lands, and sovereign nations. The social science lens draws attention to the incompatibility between the engineering definition of resilience (i.e., return to equilibrium or a singular stable state) and the ecological and social system realities, more explicit in the ecological interpretation of resilience (i.e., the ability of a system to move into a different, possibly more resilient state). Social science perspectives include but are not limited to differing views on resilience as normative, system persistence versus transformation, and system boundary issues. To expand understanding of resilience and objectives for complex and dynamic systems, concepts related to inequality, heterogeneity, power, agency, trust, values, culture, history, conflict, and system feedbacks must be more tightly integrated into FEW research. We identify gaps in knowledge and data, and the value and complexity of incorporating social components and processes into systems models. We posit that socio-biophysical system resilience modeling would address important complex, dynamic social relationships, including non-linear dynamics of social interactions, to offer an improved understanding of sustainable management in FEW systems. Conceptual modeling that is presented in our study, represents

Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework

Directory of Open Access Journals (Sweden)

Toh Hiroyuki

2008-04-01

Full Text Available Abstract Background Structural alignment of RNAs is becoming important, since the discovery of functional non-coding RNAs (ncRNAs. Recent studies, mainly based on various approximations of the Sankoff algorithm, have resulted in considerable improvement in the accuracy of pairwise structural alignment. In contrast, for the cases with more than two sequences, the practical merit of structural alignment remains unclear as compared to traditional sequence-based methods, although the importance of multiple structural alignment is widely recognized. Results We took a different approach from a straightforward extension of the Sankoff algorithm to the multiple alignments from the viewpoints of accuracy and time complexity. As a new option of the MAFFT alignment program, we developed a multiple RNA alignment framework, X-INS-i, which builds a multiple alignment with an iterative method incorporating structural information through two components: (1 pairwise structural alignments by an external pairwise alignment method such as SCARNA or LaRA and (2 a new objective function, Four-way Consistency, derived from the base-pairing probability of every sub-aligned group at every multiple alignment stage. Conclusion The BRAliBASE benchmark showed that X-INS-i outperforms other methods currently available in the sum-of-pairs score (SPS criterion. As a basis for predicting common secondary structure, the accuracy of the present method is comparable to or rather higher than those of the current leading methods such as RNA Sampler. The X-INS-i framework can be used for building a multiple RNA alignment from any combination of algorithms for pairwise RNA alignment and base-pairing probability. The source code is available at the webpage found in the Availability and requirements section.

Incorporating Psychological Predictors of Treatment Response into Health Economic Simulation Models: A Case Study in Type 1 Diabetes.

Science.gov (United States)

Kruger, Jen; Pollard, Daniel; Basarir, Hasan; Thokala, Praveen; Cooke, Debbie; Clark, Marie; Bond, Rod; Heller, Simon; Brennan, Alan

2015-10-01

. Health economic modeling has paid limited attention to the effects that patients' psychological characteristics have on the effectiveness of treatments. This case study tests 1) the feasibility of incorporating psychological prediction models of treatment response within an economic model of type 1 diabetes, 2) the potential value of providing treatment to a subgroup of patients, and 3) the cost-effectiveness of providing treatment to a subgroup of responders defined using 5 different algorithms. . Multiple linear regressions were used to investigate relationships between patients' psychological characteristics and treatment effectiveness. Two psychological prediction models were integrated with a patient-level simulation model of type 1 diabetes. Expected value of individualized care analysis was undertaken. Five different algorithms were used to provide treatment to a subgroup of predicted responders. A cost-effectiveness analysis compared using the algorithms to providing treatment to all patients. . The psychological prediction models had low predictive power for treatment effectiveness. Expected value of individualized care results suggested that targeting education at responders could be of value. The cost-effectiveness analysis suggested, for all 5 algorithms, that providing structured education to a subgroup of predicted responders would not be cost-effective. . The psychological prediction models tested did not have sufficient predictive power to make targeting treatment cost-effective. The psychological prediction models are simple linear models of psychological behavior. Collection of data on additional covariates could potentially increase statistical power. . By collecting data on psychological variables before an intervention, we can construct predictive models of treatment response to interventions. These predictive models can be incorporated into health economic models to investigate more complex service delivery and reimbursement strategies. �

Incorporating neurophysiological concepts in mathematical thermoregulation models

Science.gov (United States)

Kingma, Boris R. M.; Vosselman, M. J.; Frijns, A. J. H.; van Steenhoven, A. A.; van Marken Lichtenbelt, W. D.

2014-01-01

Skin blood flow (SBF) is a key player in human thermoregulation during mild thermal challenges. Various numerical models of SBF regulation exist. However, none explicitly incorporates the neurophysiology of thermal reception. This study tested a new SBF model that is in line with experimental data on thermal reception and the neurophysiological pathways involved in thermoregulatory SBF control. Additionally, a numerical thermoregulation model was used as a platform to test the function of the neurophysiological SBF model for skin temperature simulation. The prediction-error of the SBF-model was quantified by root-mean-squared-residual (RMSR) between simulations and experimental measurement data. Measurement data consisted of SBF (abdomen, forearm, hand), core and skin temperature recordings of young males during three transient thermal challenges (1 development and 2 validation). Additionally, ThermoSEM, a thermoregulation model, was used to simulate body temperatures using the new neurophysiological SBF-model. The RMSR between simulated and measured mean skin temperature was used to validate the model. The neurophysiological model predicted SBF with an accuracy of RMSR human thermoregulation models can be equipped with SBF control functions that are based on neurophysiology without loss of performance. The neurophysiological approach in modelling thermoregulation is favourable over engineering approaches because it is more in line with the underlying physiology.

Incorporation of composite defects from ultrasonic NDE into CAD and FE models

Science.gov (United States)

Bingol, Onur Rauf; Schiefelbein, Bryan; Grandin, Robert J.; Holland, Stephen D.; Krishnamurthy, Adarsh

2017-02-01

Fiber-reinforced composites are widely used in aerospace industry due to their combined properties of high strength and low weight. However, owing to their complex structure, it is difficult to assess the impact of manufacturing defects and service damage on their residual life. While, ultrasonic testing (UT) is the preferred NDE method to identify the presence of defects in composites, there are no reasonable ways to model the damage and evaluate the structural integrity of composites. We have developed an automated framework to incorporate flaws and known composite damage automatically into a finite element analysis (FEA) model of composites, ultimately aiding in accessing the residual life of composites and make informed decisions regarding repairs. The framework can be used to generate a layer-by-layer 3D structural CAD model of the composite laminates replicating their manufacturing process. Outlines of structural defects, such as delaminations, are automatically detected from UT of the laminate and are incorporated into the CAD model between the appropriate layers. In addition, the framework allows for direct structural analysis of the resulting 3D CAD models with defects by automatically applying the appropriate boundary conditions. In this paper, we show a working proof-of-concept for the composite model builder with capabilities of incorporating delaminations between laminate layers and automatically preparing the CAD model for structural analysis using a FEA software.

Developing Baltic cod recruitment models II : Incorporation of environmental variability and species interaction

DEFF Research Database (Denmark)

Köster, Fritz; Hinrichsen, H.H.; St. John, Michael

2001-01-01

We investigate whether a process-oriented approach based on the results of field, laboratory, and modelling studies can be used to develop a stock-environment-recruitment model for Central Baltic cod (Gadus morhua). Based on exploratory statistical analysis, significant variables influencing...... cod in these areas, suggesting that key biotic and abiotic processes can be successfully incorporated into recruitment models....... survival of early life stages and varying systematically among spawning sites were incorporated into stock-recruitment models, first for major cod spawning sites and then combined for the entire Central Baltic. Variables identified included potential egg production by the spawning stock, abiotic conditions...

Testing for Nonuniform Differential Item Functioning with Multiple Indicator Multiple Cause Models

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Woods, Carol M.; Grimm, Kevin J.

2011-01-01

In extant literature, multiple indicator multiple cause (MIMIC) models have been presented for identifying items that display uniform differential item functioning (DIF) only, not nonuniform DIF. This article addresses, for apparently the first time, the use of MIMIC models for testing both uniform and nonuniform DIF with categorical indicators. A…

A climatological model for risk computations incorporating site- specific dry deposition influences

International Nuclear Information System (INIS)

Droppo, J.G. Jr.

1991-07-01

A gradient-flux dry deposition module was developed for use in a climatological atmospheric transport model, the Multimedia Environmental Pollutant Assessment System (MEPAS). The atmospheric pathway model computes long-term average contaminant air concentration and surface deposition patterns surrounding a potential release site incorporating location-specific dry deposition influences. Gradient-flux formulations are used to incorporate site and regional data in the dry deposition module for this atmospheric sector-average climatological model. Application of these formulations provide an effective means of accounting for local surface roughness in deposition computations. Linkage to a risk computation module resulted in a need for separate regional and specific surface deposition computations. 13 refs., 4 figs., 2 tabs

Methods improvements incorporated into the SAPHIRE ASP models

International Nuclear Information System (INIS)

Sattison, M.B.; Blackman, H.S.; Novack, S.D.; Smith, C.L.; Rasmuson, D.M.

1994-01-01

The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methodology, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3) enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements

Methods improvements incorporated into the SAPHIRE ASP models

International Nuclear Information System (INIS)

Sattison, M.B.; Blackman, H.S.; Novack, S.D.

1995-01-01

The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methods, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3) enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements

The prediction of type 1 diabetes by multiple autoantibody levels and their incorporation into an autoantibody risk score in relatives of type 1 diabetic patients.

Science.gov (United States)

Sosenko, Jay M; Skyler, Jay S; Palmer, Jerry P; Krischer, Jeffrey P; Yu, Liping; Mahon, Jeffrey; Beam, Craig A; Boulware, David C; Rafkin, Lisa; Schatz, Desmond; Eisenbarth, George

2013-09-01

We assessed whether a risk score that incorporates levels of multiple islet autoantibodies could enhance the prediction of type 1 diabetes (T1D). TrialNet Natural History Study participants (n = 784) were tested for three autoantibodies (GADA, IA-2A, and mIAA) at their initial screening. Samples from those positive for at least one autoantibody were subsequently tested for ICA and ZnT8A. An autoantibody risk score (ABRS) was developed from a proportional hazards model that combined autoantibody levels from each autoantibody along with their designations of positivity and negativity. The ABRS was strongly predictive of T1D (hazard ratio [with 95% CI] 2.72 [2.23-3.31], P < 0.001). Receiver operating characteristic curve areas (with 95% CI) for the ABRS revealed good predictability (0.84 [0.78-0.90] at 2 years, 0.81 [0.74-0.89] at 3 years, P < 0.001 for both). The composite of levels from the five autoantibodies was predictive of T1D before and after an adjustment for the positivity or negativity of autoantibodies (P < 0.001). The findings were almost identical when ICA was excluded from the risk score model. The combination of the ABRS and the previously validated Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) predicted T1D more accurately (0.93 [0.88-0.98] at 2 years, 0.91 [0.83-0.99] at 3 years) than either the DPTRS or the ABRS alone (P ≤ 0.01 for all comparisons). These findings show the importance of considering autoantibody levels in assessing the risk of T1D. Moreover, levels of multiple autoantibodies can be incorporated into an ABRS that accurately predicts T1D.

An electricity generation planning model incorporating demand response

International Nuclear Information System (INIS)

Choi, Dong Gu; Thomas, Valerie M.

2012-01-01

Energy policies that aim to reduce carbon emissions and change the mix of electricity generation sources, such as carbon cap-and-trade systems and renewable electricity standards, can affect not only the source of electricity generation, but also the price of electricity and, consequently, demand. We develop an optimization model to determine the lowest cost investment and operation plan for the generating capacity of an electric power system. The model incorporates demand response to price change. In a case study for a U.S. state, we show the price, demand, and generation mix implications of a renewable electricity standard, and of a carbon cap-and-trade policy with and without initial free allocation of carbon allowances. This study shows that both the demand moderating effects and the generation mix changing effects of the policies can be the sources of carbon emissions reductions, and also shows that the share of the sources could differ with different policy designs. The case study provides different results when demand elasticity is excluded, underscoring the importance of incorporating demand response in the evaluation of electricity generation policies. - Highlights: ► We develop an electric power system optimization model including demand elasticity. ► Both renewable electricity and carbon cap-and-trade policies can moderate demand. ► Both policies affect the generation mix, price, and demand for electricity. ► Moderated demand can be a significant source of carbon emission reduction. ► For cap-and-trade policies, initial free allowances change outcomes significantly.

"Violent Intent Modeling: Incorporating Cultural Knowledge into the Analytical Process

Energy Technology Data Exchange (ETDEWEB)

Sanfilippo, Antonio P.; Nibbs, Faith G.

2007-08-24

While culture has a significant effect on the appropriate interpretation of textual data, the incorporation of cultural considerations into data transformations has not been systematic. Recognizing that the successful prevention of terrorist activities could hinge on the knowledge of the subcultures, Anthropologist and DHS intern Faith Nibbs has been addressing the need to incorporate cultural knowledge into the analytical process. In this Brown Bag she will present how cultural ideology is being used to understand how the rhetoric of group leaders influences the likelihood of their constituents to engage in violent or radicalized behavior, and how violent intent modeling can benefit from understanding that process.

Parallel Beam-Beam Simulation Incorporating Multiple Bunches and Multiple Interaction Regions

CERN Document Server

Jones, F W; Pieloni, T

2007-01-01

The simulation code COMBI has been developed to enable the study of coherent beam-beam effects in the full collision scenario of the LHC, with multiple bunches interacting at multiple crossing points over many turns. The program structure and input are conceived in a general way which allows arbitrary numbers and placements of bunches and interaction points (IP's), together with procedural options for head-on and parasitic collisions (in the strong-strong sense), beam transport, statistics gathering, harmonic analysis, and periodic output of simulation data. The scale of this problem, once we go beyond the simplest case of a pair of bunches interacting once per turn, quickly escalates into the parallel computing arena, and herein we will describe the construction of an MPI-based version of COMBI able to utilize arbitrary numbers of processors to support efficient calculation of multi-bunch multi-IP interactions and transport. Implementing the parallel version did not require extensive disruption of the basic ...

Incorporating nitrogen fixing cyanobacteria in the global biogeochemical model HAMOCC

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Paulsen, Hanna; Ilyina, Tatiana; Six, Katharina

2015-04-01

Nitrogen fixation by marine diazotrophs plays a fundamental role in the oceanic nitrogen and carbon cycle as it provides a major source of 'new' nitrogen to the euphotic zone that supports biological carbon export and sequestration. Since most global biogeochemical models include nitrogen fixation only diagnostically, they are not able to capture its spatial pattern sufficiently. Here we present the incorporation of an explicit, dynamic representation of diazotrophic cyanobacteria and the corresponding nitrogen fixation in the global ocean biogeochemical model HAMOCC (Hamburg Ocean Carbon Cycle model), which is part of the Max Planck Institute for Meteorology Earth system model (MPI-ESM). The parameterization of the diazotrophic growth is thereby based on available knowledge about the cyanobacterium Trichodesmium spp., which is considered as the most significant pelagic nitrogen fixer. Evaluation against observations shows that the model successfully reproduces the main spatial distribution of cyanobacteria and nitrogen fixation, covering large parts of the tropical and subtropical oceans. Besides the role of cyanobacteria in marine biogeochemical cycles, their capacity to form extensive surface blooms induces a number of bio-physical feedback mechanisms in the Earth system. The processes driving these interactions, which are related to the alteration of heat absorption, surface albedo and momentum input by wind, are incorporated in the biogeochemical and physical model of the MPI-ESM in order to investigate their impacts on a global scale. First preliminary results will be shown.

Incorporating Environmental Justice into Second Generation Indices of Multiple Deprivation: Lessons from the UK and Progress Internationally

Directory of Open Access Journals (Sweden)

Jon Fairburn

2016-07-01

Full Text Available Second generation area-based indices of multiple deprivation have been extensively used in the UK over the last 15 years. They resulted from significant developments in political, technical, and conceptual spheres for deprivation data. We review the parallel development of environmental justice research and how and when environmental data was incorporated into these indices. We explain the transfer of these methods from the UK to Germany and assess the progress internationally in developing such indices. Finally, we illustrate how billions of pounds in the UK was allocated by using these tools to tackle neighbourhood deprivation and environmental justice to address the determinants of health.

Modeling Rabbit Responses to Single and Multiple Aerosol ...

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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

Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation

OpenAIRE

Min Yan; Xin Tian; Zengyuan Li; Erxue Chen; Xufeng Wang; Zongtao Han; Hong Sun

2016-01-01

This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC) using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17) model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST) sensitivity analysis. Then the optimized MOD_17 mo...

Transient stability risk assessment of power systems incorporating wind farms

DEFF Research Database (Denmark)

Miao, Lu; Fang, Jiakun; Wen, Jinyu

2013-01-01

fed induction generator has been established. Wind penetration variation and multiple stochastic factors of power systems have been considered. The process of transient stability risk assessment based on the Monte Carlo method has been described and a comprehensive risk indicator has been proposed......Large-scale wind farm integration has brought several aspects of challenges to the transient stability of power systems. This paper focuses on the research of the transient stability of power systems incorporating with wind farms by utilizing risk assessment methods. The detailed model of double....... An investigation has been conducted into an improved 10-generator 39-bus system with a wind farm incorporated to verify the validity and feasibility of the risk assessment method proposed....

INCORPORATION OF MECHANISTIC INFORMATION IN THE ARSENIC PBPK MODEL DEVELOPMENT PROCESS

Science.gov (United States)

INCORPORATING MECHANISTIC INSIGHTS IN A PBPK MODEL FOR ARSENICElaina M. Kenyon, Michael F. Hughes, Marina V. Evans, David J. Thomas, U.S. EPA; Miroslav Styblo, University of North Carolina; Michael Easterling, Analytical Sciences, Inc.A physiologically based phar...

Modeling of Particle Acceleration at Multiple Shocks Via Diffusive Shock Acceleration: Preliminary Results

Science.gov (United States)

Parker, L. N.; Zank, G. P.

2013-12-01

Successful forecasting of energetic particle events in space weather models require algorithms for correctly predicting the spectrum of ions accelerated from a background population of charged particles. We present preliminary results from a model that diffusively accelerates particles at multiple shocks. Our basic approach is related to box models (Protheroe and Stanev, 1998; Moraal and Axford, 1983; Ball and Kirk, 1992; Drury et al., 1999) in which a distribution of particles is diffusively accelerated inside the box while simultaneously experiencing decompression through adiabatic expansion and losses from the convection and diffusion of particles outside the box (Melrose and Pope, 1993; Zank et al., 2000). We adiabatically decompress the accelerated particle distribution between each shock by either the method explored in Melrose and Pope (1993) and Pope and Melrose (1994) or by the approach set forth in Zank et al. (2000) where we solve the transport equation by a method analogous to operator splitting. The second method incorporates the additional loss terms of convection and diffusion and allows for the use of a variable time between shocks. We use a maximum injection energy (Emax) appropriate for quasi-parallel and quasi-perpendicular shocks (Zank et al., 2000, 2006; Dosch and Shalchi, 2010) and provide a preliminary application of the diffusive acceleration of particles by multiple shocks with frequencies appropriate for solar maximum (i.e., a non-Markovian process).

A code reviewer assignment model incorporating the competence differences and participant preferences

Directory of Open Access Journals (Sweden)

Wang Yanqing

2016-03-01

Full Text Available A good assignment of code reviewers can effectively utilize the intellectual resources, assure code quality and improve programmers’ skills in software development. However, little research on reviewer assignment of code review has been found. In this study, a code reviewer assignment model is created based on participants’ preference to reviewing assignment. With a constraint of the smallest size of a review group, the model is optimized to maximize review outcomes and avoid the negative impact of “mutual admiration society”. This study shows that the reviewer assignment strategies incorporating either the reviewers’ preferences or the authors’ preferences get much improvement than a random assignment. The strategy incorporating authors’ preference makes higher improvement than that incorporating reviewers’ preference. However, when the reviewers’ and authors’ preference matrixes are merged, the improvement becomes moderate. The study indicates that the majority of the participants have a strong wish to work with reviewers and authors having highest competence. If we want to satisfy the preference of both reviewers and authors at the same time, the overall improvement of learning outcomes may be not the best.

Incorporation of Damage and Failure into an Orthotropic Elasto-Plastic Three-Dimensional Model with Tabulated Input Suitable for Use in Composite Impact Problems

Science.gov (United States)

Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Hoffarth, Canio; Khaled, Bilal; Rajan, Subramaniam; Blankenhorn, Gunther

2016-01-01

A material model which incorporates several key capabilities which have been identified by the aerospace community as lacking in the composite impact models currently available in LS-DYNA(Registered Trademark) is under development. In particular, the material model, which is being implemented as MAT 213 into a tailored version of LS-DYNA being jointly developed by the FAA and NASA, incorporates both plasticity and damage within the material model, utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength), and is able to analyze the response of composites composed with a variety of fiber architectures. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. The capability to account for the rate and temperature dependent deformation response of composites has also been incorporated into the material model. For the damage model, a strain equivalent formulation is utilized to allow for the uncoupling of the deformation and damage analyses. In the damage model, a diagonal damage tensor is defined to account for the directionally dependent variation of damage. However, in composites it has been found that loading in one direction can lead to damage in multiple coordinate directions. To account for this phenomena, the terms in the damage matrix are semi-coupled such that the damage in a particular coordinate direction is a function of the stresses and plastic strains in all of the coordinate directions. The onset of material failure, and thus element deletion, is being developed to be a function of the stresses and plastic strains in the various coordinate directions. Systematic procedures are being developed to generate the required input parameters based on the results of

Incorporating model parameter uncertainty into inverse treatment planning

International Nuclear Information System (INIS)

Lian Jun; Xing Lei

2004-01-01

Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

Multi-criteria media mix decision model for advertising multiple product with segment specific and mass media

Directory of Open Access Journals (Sweden)

Sugandha Aggarwal

2014-12-01

Full Text Available Judicious media planning decisions are crucial for successful advertising of products. Media planners extensively use mathematical models supplemented with market research and expert opinion to devise the media plans. Media planning models discussed in the literature largely focus on single products with limited studies related to the multi-product media planning. In this paper we propose a media planning model to allocate limited advertising budget among multiple products advertised in a segmented market and determine the number of advertisements to be given in different media. The proposed model is formulated considering both segment specific and mass media vehicles to maximize the total advertising reach for each product. The model also incorporates the cross product effect of advertising of one product on the other. The proposed formulation is a multi-objective linear integer programming model and interactive linear integer goal programming is discussed to solve the model. A real life case study is presented to illustrate the application of the proposed model.

Generalized multiple kernel learning with data-dependent priors.

Science.gov (United States)

Mao, Qi; Tsang, Ivor W; Gao, Shenghua; Wang, Li

2015-06-01

Multiple kernel learning (MKL) and classifier ensemble are two mainstream methods for solving learning problems in which some sets of features/views are more informative than others, or the features/views within a given set are inconsistent. In this paper, we first present a novel probabilistic interpretation of MKL such that maximum entropy discrimination with a noninformative prior over multiple views is equivalent to the formulation of MKL. Instead of using the noninformative prior, we introduce a novel data-dependent prior based on an ensemble of kernel predictors, which enhances the prediction performance of MKL by leveraging the merits of the classifier ensemble. With the proposed probabilistic framework of MKL, we propose a hierarchical Bayesian model to learn the proposed data-dependent prior and classification model simultaneously. The resultant problem is convex and other information (e.g., instances with either missing views or missing labels) can be seamlessly incorporated into the data-dependent priors. Furthermore, a variety of existing MKL models can be recovered under the proposed MKL framework and can be readily extended to incorporate these priors. Extensive experiments demonstrate the benefits of our proposed framework in supervised and semisupervised settings, as well as in tasks with partial correspondence among multiple views.

Electricity supply industry modelling for multiple objectives under demand growth uncertainty

International Nuclear Information System (INIS)

Heinrich, G.; Basson, L.; Howells, M.; Petrie, J.

2007-01-01

Appropriate energy-environment-economic (E3) modelling provides key information for policy makers in the electricity supply industry (ESI) faced with navigating a sustainable development path. Key challenges include engaging with stakeholder values and preferences, and exploring trade-offs between competing objectives in the face of underlying uncertainty. As a case study we represent the South African ESI using a partial equilibrium E3 modelling approach, and extend the approach to include multiple objectives under selected future uncertainties. This extension is achieved by assigning cost penalties to non-cost attributes to force the model's least-cost objective function to better satisfy non-cost criteria. This paper incorporates aspects of flexibility to demand growth uncertainty into each future expansion alternative by introducing stochastic programming with recourse into the model. Technology lead times are taken into account by the inclusion of a decision node along the time horizon where aspects of real options theory are considered within the planning process. Hedging in the recourse programming is automatically translated from being purely financial, to include the other attributes that the cost penalties represent. From a retrospective analysis of the cost penalties, the correct market signals, can be derived to meet policy goal, with due regard to demand uncertainty. (author)

Incorporation of various uncertainties in dependent failure-probability estimation

International Nuclear Information System (INIS)

Samanta, P.K.; Mitra, S.P.

1982-01-01

This paper describes an approach that allows the incorporation of various types of uncertainties in the estimation of dependent failure (common mode failure) probability. The types of uncertainties considered are attributable to data, modeling and coupling. The method developed is applied to a class of dependent failures, i.e., multiple human failures during testing, maintenance and calibration. Estimation of these failures is critical as they have been shown to be significant contributors to core melt probability in pressurized water reactors

Hyperspectral material identification on radiance data using single-atmosphere or multiple-atmosphere modeling

Science.gov (United States)

Mariano, Adrian V.; Grossmann, John M.

2010-11-01

Reflectance-domain methods convert hyperspectral data from radiance to reflectance using an atmospheric compensation model. Material detection and identification are performed by comparing the compensated data to target reflectance spectra. We introduce two radiance-domain approaches, Single atmosphere Adaptive Cosine Estimator (SACE) and Multiple atmosphere ACE (MACE) in which the target reflectance spectra are instead converted into sensor-reaching radiance using physics-based models. For SACE, known illumination and atmospheric conditions are incorporated in a single atmospheric model. For MACE the conditions are unknown so the algorithm uses many atmospheric models to cover the range of environmental variability, and it approximates the result using a subspace model. This approach is sometimes called the invariant method, and requires the choice of a subspace dimension for the model. We compare these two radiance-domain approaches to a Reflectance-domain ACE (RACE) approach on a HYDICE image featuring concealed materials. All three algorithms use the ACE detector, and all three techniques are able to detect most of the hidden materials in the imagery. For MACE we observe a strong dependence on the choice of the material subspace dimension. Increasing this value can lead to a decline in performance.

Geometrical model of multiple production

International Nuclear Information System (INIS)

Chikovani, Z.E.; Jenkovszky, L.L.; Kvaratshelia, T.M.; Struminskij, B.V.

1988-01-01

The relation between geometrical and KNO-scaling and their violation is studied in a geometrical model of multiple production of hadrons. Predictions concerning the behaviour of correlation coefficients at future accelerators are given

Optimal design of compact and connected nature reserves for multiple species.

Science.gov (United States)

Wang, Yicheng; Önal, Hayri

2016-04-01

When designing a conservation reserve system for multiple species, spatial attributes of the reserves must be taken into account at species level. The existing optimal reserve design literature considers either one spatial attribute or when multiple attributes are considered the analysis is restricted only to one species. We built a linear integer programing model that incorporates compactness and connectivity of the landscape reserved for multiple species. The model identifies multiple reserves that each serve a subset of target species with a specified coverage probability threshold to ensure the species' long-term survival in the reserve, and each target species is covered (protected) with another probability threshold at the reserve system level. We modeled compactness by minimizing the total distance between selected sites and central sites, and we modeled connectivity of a selected site to its designated central site by selecting at least one of its adjacent sites that has a nearer distance to the central site. We considered structural distance and functional distances that incorporated site quality between sites. We tested the model using randomly generated data on 2 species, one ground species that required structural connectivity and the other an avian species that required functional connectivity. We applied the model to 10 bird species listed as endangered by the state of Illinois (U.S.A.). Spatial coherence and selection cost of the reserves differed substantially depending on the weights assigned to these 2 criteria. The model can be used to design a reserve system for multiple species, especially species whose habitats are far apart in which case multiple disjunct but compact and connected reserves are advantageous. The model can be modified to increase or decrease the distance between reserves to reduce or promote population connectivity. © 2015 Society for Conservation Biology.

Multiplicity Control in Structural Equation Modeling

Science.gov (United States)

Cribbie, Robert A.

2007-01-01

Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

Incorporation of ice sheet models into an Earth system model: Focus on methodology of coupling

Science.gov (United States)

Rybak, Oleg; Volodin, Evgeny; Morozova, Polina; Nevecherja, Artiom

2018-03-01

Elaboration of a modern Earth system model (ESM) requires incorporation of ice sheet dynamics. Coupling of an ice sheet model (ICM) to an AOGCM is complicated by essential differences in spatial and temporal scales of cryospheric, atmospheric and oceanic components. To overcome this difficulty, we apply two different approaches for the incorporation of ice sheets into an ESM. Coupling of the Antarctic ice sheet model (AISM) to the AOGCM is accomplished via using procedures of resampling, interpolation and assigning to the AISM grid points annually averaged meanings of air surface temperature and precipitation fields generated by the AOGCM. Surface melting, which takes place mainly on the margins of the Antarctic peninsula and on ice shelves fringing the continent, is currently ignored. AISM returns anomalies of surface topography back to the AOGCM. To couple the Greenland ice sheet model (GrISM) to the AOGCM, we use a simple buffer energy- and water-balance model (EWBM-G) to account for orographically-driven precipitation and other sub-grid AOGCM-generated quantities. The output of the EWBM-G consists of surface mass balance and air surface temperature to force the GrISM, and freshwater run-off to force thermohaline circulation in the oceanic block of the AOGCM. Because of a rather complex coupling procedure of GrIS compared to AIS, the paper mostly focuses on Greenland.

Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

Science.gov (United States)

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

Incorporation particle creation and annihilation into Bohm's Pilot Wave model

Energy Technology Data Exchange (ETDEWEB)

Sverdlov, Roman [Raman Research Institute, C.V. Raman Avenue, Sadashiva Nagar, Bangalore, Karnataka, 560080 (India)

2011-07-08

The purpose of this paper is to come up with a Pilot Wave model of quantum field theory that incorporates particle creation and annihilation without sacrificing determinism; this theory is subsequently coupled with gravity.

Improving Watershed-Scale Hydrodynamic Models by Incorporating Synthetic 3D River Bathymetry Network

Science.gov (United States)

Dey, S.; Saksena, S.; Merwade, V.

2017-12-01

Digital Elevation Models (DEMs) have an incomplete representation of river bathymetry, which is critical for simulating river hydrodynamics in flood modeling. Generally, DEMs are augmented with field collected bathymetry data, but such data are available only at individual reaches. Creating a hydrodynamic model covering an entire stream network in the basin requires bathymetry for all streams. This study extends a conceptual bathymetry model, River Channel Morphology Model (RCMM), to estimate the bathymetry for an entire stream network for application in hydrodynamic modeling using a DEM. It is implemented at two large watersheds with different relief and land use characterizations: coastal Guadalupe River basin in Texas with flat terrain and a relatively urban White River basin in Indiana with more relief. After bathymetry incorporation, both watersheds are modeled using HEC-RAS (1D hydraulic model) and Interconnected Pond and Channel Routing (ICPR), a 2-D integrated hydrologic and hydraulic model. A comparison of the streamflow estimated by ICPR at the outlet of the basins indicates that incorporating bathymetry influences streamflow estimates. The inundation maps show that bathymetry has a higher impact on flat terrains of Guadalupe River basin when compared to the White River basin.

75 FR 17737 - Industrial Economics, Incorporated; Transfer of Data

Science.gov (United States)

2010-04-07

... ENVIRONMENTAL PROTECTION AGENCY [EPA-HQ-OPP-2010-0194; FRL-8820-2] Industrial Economics... (CBI) by the submitter, will be transferred to Industrial Economics, Incorporated in accordance with 40 CFR 2.307(h)(3) and 2.308(i)(2). Industrial Economics, Incorporated has been awarded multiple...

An Elementary Semantics for Cardelli's System of Multiple Inheritance

NARCIS (Netherlands)

Fokkinga, M.M.

1987-01-01

In [Cardelli 84] Luca Cardelli gave a formal definition of a typed object-oriented language incorporating a sub-type relation used to describe multiple inheritance. Cardelli's fundamental result was a semantics for his system that enabled sub-typing to be modelled as straightforward set-inclusion.

Prediction of preterm birth in multiple pregnancies: development of a multivariable model including cervical length measurement at 16 to 21 weeks' gestation.

Science.gov (United States)

van de Mheen, Lidewij; Schuit, Ewoud; Lim, Arianne C; Porath, Martina M; Papatsonis, Dimitri; Erwich, Jan J; van Eyck, Jim; van Oirschot, Charlotte M; Hummel, Piet; Duvekot, Johannes J; Hasaart, Tom H M; Groenwold, Rolf H H; Moons, Karl G M; de Groot, Christianne J M; Bruinse, Hein W; van Pampus, Maria G; Mol, Ben W J

2014-04-01

To develop a multivariable prognostic model for the risk of preterm delivery in women with multiple pregnancy that includes cervical length measurement at 16 to 21 weeks' gestation and other variables. We used data from a previous randomized trial. We assessed the association between maternal and pregnancy characteristics including cervical length measurement at 16 to 21 weeks' gestation and time to delivery using multivariable Cox regression modelling. Performance of the final model was assessed for the outcomes of preterm and very preterm delivery using calibration and discrimination measures. We studied 507 women, of whom 270 (53%) delivered models for preterm and very preterm delivery had a c-index of 0.68 (95% CI 0.63 to 0.72) and 0.68 (95% CI 0.62 to 0.75), respectively, and showed good calibration. In women with a multiple pregnancy, the risk of preterm delivery can be assessed with a multivariable model incorporating cervical length and other predictors.

Integration of multiple, excess, backup, and expected covering models

OpenAIRE

M S Daskin; K Hogan; C ReVelle

1988-01-01

The concepts of multiple, excess, backup, and expected coverage are defined. Model formulations using these constructs are reviewed and contrasted to illustrate the relationships between them. Several new formulations are presented as is a new derivation of the expected covering model which indicates more clearly the relationship of the model to other multi-state covering models. An expected covering model with multiple time standards is also presented.

Evolving Four Part Harmony Using a Multiple Worlds Model

DEFF Research Database (Denmark)

Scirea, Marco; Brown, Joseph Alexander

2015-01-01

This application of the Multiple Worlds Model examines a collaborative fitness model for generating four part harmonies. In this model we have multiple populations and the fitness of the individuals is based on the ability of a member from each population to work with the members of other...

Double-multiple streamtube model for Darrieus in turbines

Science.gov (United States)

Paraschivoiu, I.

1981-01-01

An analytical model is proposed for calculating the rotor performance and aerodynamic blade forces for Darrieus wind turbines with curved blades. The method of analysis uses a multiple-streamtube model, divided into two parts: one modeling the upstream half-cycle of the rotor and the other, the downstream half-cycle. The upwind and downwind components of the induced velocities at each level of the rotor were obtained using the principle of two actuator disks in tandem. Variation of the induced velocities in the two parts of the rotor produces larger forces in the upstream zone and smaller forces in the downstream zone. Comparisons of the overall rotor performance with previous methods and field test data show the important improvement obtained with the present model. The calculations were made using the computer code CARDAA developed at IREQ. The double-multiple streamtube model presented has two major advantages: it requires a much shorter computer time than the three-dimensional vortex model and is more accurate than multiple-streamtube model in predicting the aerodynamic blade loads.

Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

Energy Technology Data Exchange (ETDEWEB)

Sullivan, P.; Eurek, K.; Margolis, R.

2014-07-01

Because solar power is a rapidly growing component of the electricity system, robust representations of solar technologies should be included in capacity-expansion models. This is a challenge because modeling the electricity system--and, in particular, modeling solar integration within that system--is a complex endeavor. This report highlights the major challenges of incorporating solar technologies into capacity-expansion models and shows examples of how specific models address those challenges. These challenges include modeling non-dispatchable technologies, determining which solar technologies to model, choosing a spatial resolution, incorporating a solar resource assessment, and accounting for solar generation variability and uncertainty.

A hybrid health service accreditation program model incorporating mandated standards and continuous improvement: interview study of multiple stakeholders in Australian health care.

Science.gov (United States)

Greenfield, David; Hinchcliff, Reece; Hogden, Anne; Mumford, Virginia; Debono, Deborah; Pawsey, Marjorie; Westbrook, Johanna; Braithwaite, Jeffrey

2016-07-01

The study aim was to investigate the understandings and concerns of stakeholders regarding the evolution of health service accreditation programs in Australia. Stakeholder representatives from programs in the primary, acute and aged care sectors participated in semi-structured interviews. Across 2011-12 there were 47 group and individual interviews involving 258 participants. Interviews lasted, on average, 1 h, and were digitally recorded and transcribed. Transcriptions were analysed using textual referencing software. Four significant issues were considered to have directed the evolution of accreditation programs: altering underlying program philosophies; shifting of program content focus and details; different surveying expectations and experiences and the influence of external contextual factors upon accreditation programs. Three accreditation program models were noted by participants: regulatory compliance; continuous quality improvement and a hybrid model, incorporating elements of these two. Respondents noted the compatibility or incommensurability of the first two models. Participation in a program was reportedly experienced as ranging on a survey continuum from "malicious compliance" to "performance audits" to "quality improvement journeys". Wider contextual factors, in particular, political and community expectations, and associated media reporting, were considered significant influences on the operation and evolution of programs. A hybrid accreditation model was noted to have evolved. The hybrid model promotes minimum standards and continuous quality improvement, through examining the structure and processes of organisations and the outcomes of care. The hybrid model appears to be directing organisational and professional attention to enhance their safety cultures. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Multiple resonant absorber with prism-incorporated graphene and one-dimensional photonic crystals in the visible and near-infrared spectral range

Science.gov (United States)

Zou, X. J.; Zheng, G. G.; Chen, Y. Y.; Xu, L. H.; Lai, M.

2018-04-01

A multi-band absorber constructed from prism-incorporated one-dimensional photonic crystal (1D-PhC) containing graphene defects is achieved theoretically in the visible and near-infrared (vis-NIR) spectral range. By means of the transfer matrix method (TMM), the effect of structural parameters on the optical response of the structure has been investigated. It is possible to achieve multi-peak and complete optical absorption. The simulations reveal that the light intensity is enhanced at the graphene plane, and the resonant wavelength and the absorption intensity can also be tuned by tilting the incidence angle of the impinging light. In particular, multiple graphene sheets are embedded in the arrays, without any demand of manufacture process to cut them into periodic patterns. The proposed concept can be extended to other two-dimensional (2D) materials and engineered for promising applications, including selective or multiplex filters, multiple channel sensors, and photodetectors.

In silico investigation of the short QT syndrome, using human ventricle models incorporating electromechanical coupling

Directory of Open Access Journals (Sweden)

Ismail eAdeniran

2013-07-01

Full Text Available Introduction Genetic forms of the Short QT Syndrome (SQTS arise due to cardiac ion channel mutations leading to accelerated ventricular repolarisation, arrhythmias and sudden cardiac death. Results from experimental and simulation studies suggest that changes to refractoriness and tissue vulnerability produce a substrate favourable to re-entry. Potential electromechanical consequences of the SQTS are less well understood. The aim of this study was to utilize electromechanically coupled human ventricle models to explore electromechanical consequences of the SQTS. Methods and results: The Rice et al. mechanical model was coupled to the ten Tusscher et al. ventricular cell model. Previously validated K+ channel formulations for SQT variants 1 and 3 were incorporated. Functional effects of the SQTS mutations on transients, sarcomere length shortening and contractile force at the single cell level were evaluated with and without the consideration of stretch activated channel current (Isac. Without Isac, the SQTS mutations produced dramatic reductions in the amplitude of transients, sarcomere length shortening and contractile force. When Isac was incorporated, there was a considerable attenuation of the effects of SQTS-associated action potential shortening on Ca2+ transients, sarcomere shortening and contractile force. Single cell models were then incorporated into 3D human ventricular tissue models. The timing of maximum deformation was delayed in the SQTS setting compared to control. Conclusion: The incorporation of Isac appears to be an important consideration in modelling functional effects of SQT 1 and 3 mutations on cardiac electro-mechanical coupling. Whilst there is little evidence of profoundly impaired cardiac contractile function in SQTS patients, our 3D simulations correlate qualitatively with reported evidence for dissociation between ventricular repolarization and the end of mechanical systole.

Investigations of incorporating source directivity into room acoustics computer models to improve auralizations

Science.gov (United States)

Vigeant, Michelle C.

Room acoustics computer modeling and auralizations are useful tools when designing or modifying acoustically sensitive spaces. In this dissertation, the input parameter of source directivity has been studied in great detail to determine first its effect in room acoustics computer models and secondly how to better incorporate the directional source characteristics into these models to improve auralizations. To increase the accuracy of room acoustics computer models, the source directivity of real sources, such as musical instruments, must be included in the models. The traditional method for incorporating source directivity into room acoustics computer models involves inputting the measured static directivity data taken every 10° in a sphere-shaped pattern around the source. This data can be entered into the room acoustics software to create a directivity balloon, which is used in the ray tracing algorithm to simulate the room impulse response. The first study in this dissertation shows that using directional sources over an omni-directional source in room acoustics computer models produces significant differences both in terms of calculated room acoustics parameters and auralizations. The room acoustics computer model was also validated in terms of accurately incorporating the input source directivity. A recently proposed technique for creating auralizations using a multi-channel source representation has been investigated with numerous subjective studies, applied to both solo instruments and an orchestra. The method of multi-channel auralizations involves obtaining multi-channel anechoic recordings of short melodies from various instruments and creating individual channel auralizations. These auralizations are then combined to create a total multi-channel auralization. Through many subjective studies, this process was shown to be effective in terms of improving the realism and source width of the auralizations in a number of cases, and also modeling different

Making a difference: incorporating theories of autonomy into models of informed consent.

Science.gov (United States)

Delany, C

2008-09-01

Obtaining patients' informed consent is an ethical and legal obligation in healthcare practice. Whilst the law provides prescriptive rules and guidelines, ethical theories of autonomy provide moral foundations. Models of practice of consent, have been developed in the bioethical literature to assist in understanding and integrating the ethical theory of autonomy and legal obligations into the clinical process of obtaining a patient's informed consent to treatment. To review four models of consent and analyse the way each model incorporates the ethical meaning of autonomy and how, as a consequence, they might change the actual communicative process of obtaining informed consent within clinical contexts. An iceberg framework of consent is used to conceptualise how ethical theories of autonomy are positioned and underpin the above surface, and visible clinical communication, including associated legal guidelines and ethical rules. Each model of consent is critically reviewed from the perspective of how it might shape the process of informed consent. All four models would alter the process of obtaining consent. Two models provide structure and guidelines for the content and timing of obtaining patients' consent. The two other models rely on an attitudinal shift in clinicians. They provide ideas for consent by focusing on underlying values, attitudes and meaning associated with the ethical meaning of autonomy. The paper concludes that models of practice that explicitly incorporate the underlying ethical meaning of autonomy as their basis, provide less prescriptive, but more theoretically rich guidance for healthcare communicative practices.

PWR plant operator training used full scope simulator incorporated MAAP model

International Nuclear Information System (INIS)

Matsumoto, Y.; Tabuchi, T.; Yamashita, T.; Komatsu, Y.; Tsubouchi, K.; Banka, T.; Mochizuki, T.; Nishimura, K.; Iizuka, H.

2015-01-01

NTC makes an effort with the understanding of plant behavior of core damage accident as part of our advanced training. For the Fukushima Daiichi Nuclear Power Station accident, we introduced the MAAP model into PWR operator training full scope simulator and also made the Severe Accident Visual Display unit. From 2014, we will introduce new training program for a core damage accident with PWR operator training full scope simulator incorporated the MAAP model and the Severe Accident Visual Display unit. (author)

Incorporating modelled subglacial hydrology into inversions for basal drag

Directory of Open Access Journals (Sweden)

C. P. Koziol

2017-12-01

Full Text Available A key challenge in modelling coupled ice-flow–subglacial hydrology is initializing the state and parameters of the system. We address this problem by presenting a workflow for initializing these values at the start of a summer melt season. The workflow depends on running a subglacial hydrology model for the winter season, when the system is not forced by meltwater inputs, and ice velocities can be assumed constant. Key parameters of the winter run of the subglacial hydrology model are determined from an initial inversion for basal drag using a linear sliding law. The state of the subglacial hydrology model at the end of winter is incorporated into an inversion of basal drag using a non-linear sliding law which is a function of water pressure. We demonstrate this procedure in the Russell Glacier area and compare the output of the linear sliding law with two non-linear sliding laws. Additionally, we compare the modelled winter hydrological state to radar observations and find that it is in line with summer rather than winter observations.

Incorporation of stochastic engineering models as prior information in Bayesian medical device trials.

Science.gov (United States)

Haddad, Tarek; Himes, Adam; Thompson, Laura; Irony, Telba; Nair, Rajesh

2017-01-01

Evaluation of medical devices via clinical trial is often a necessary step in the process of bringing a new product to market. In recent years, device manufacturers are increasingly using stochastic engineering models during the product development process. These models have the capability to simulate virtual patient outcomes. This article presents a novel method based on the power prior for augmenting a clinical trial using virtual patient data. To properly inform clinical evaluation, the virtual patient model must simulate the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters. The number of virtual patients is controlled by a discount function which uses the similarity between modeled and observed data. This method is illustrated by a case study of cardiac lead fracture. Different discount functions are used to cover a wide range of scenarios in which the type I error rates and power vary for the same number of enrolled patients. Incorporation of engineering models as prior knowledge in a Bayesian clinical trial design can provide benefits of decreased sample size and trial length while still controlling type I error rate and power.

The water balance of the urban Salt Lake Valley: a multiple-box model validated by observations

Science.gov (United States)

Stwertka, C.; Strong, C.

2012-12-01

A main focus of the recently awarded National Science Foundation (NSF) EPSCoR Track-1 research project "innovative Urban Transitions and Arid-region Hydro-sustainability (iUTAH)" is to quantify the primary components of the water balance for the Wasatch region, and to evaluate their sensitivity to climate change and projected urban development. Building on the multiple-box model that we developed and validated for carbon dioxide (Strong et al 2011), mass balance equations for water in the atmosphere and surface are incorporated into the modeling framework. The model is used to determine how surface fluxes, ground-water transport, biological fluxes, and meteorological processes regulate water cycling within and around the urban Salt Lake Valley. The model is used to evaluate the hypotheses that increased water demand associated with urban growth in Salt Lake Valley will (1) elevate sensitivity to projected climate variability and (2) motivate more attentive management of urban water use and evaporative fluxes.

Making Invasion models useful for decision makers; incorporating uncertainty, knowledge gaps, and decision-making preferences

Science.gov (United States)

Denys Yemshanov; Frank H Koch; Mark Ducey

2015-01-01

Uncertainty is inherent in model-based forecasts of ecological invasions. In this chapter, we explore how the perceptions of that uncertainty can be incorporated into the pest risk assessment process. Uncertainty changes a decision maker’s perceptions of risk; therefore, the direct incorporation of uncertainty may provide a more appropriate depiction of risk. Our...

Multiple model cardinalized probability hypothesis density filter

Science.gov (United States)

Georgescu, Ramona; Willett, Peter

2011-09-01

The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

Bayesian inference based modelling for gene transcriptional dynamics by integrating multiple source of knowledge

Directory of Open Access Journals (Sweden)

Wang Shu-Qiang

2012-07-01

Full Text Available Abstract Background A key challenge in the post genome era is to identify genome-wide transcriptional regulatory networks, which specify the interactions between transcription factors and their target genes. Numerous methods have been developed for reconstructing gene regulatory networks from expression data. However, most of them are based on coarse grained qualitative models, and cannot provide a quantitative view of regulatory systems. Results A binding affinity based regulatory model is proposed to quantify the transcriptional regulatory network. Multiple quantities, including binding affinity and the activity level of transcription factor (TF are incorporated into a general learning model. The sequence features of the promoter and the possible occupancy of nucleosomes are exploited to estimate the binding probability of regulators. Comparing with the previous models that only employ microarray data, the proposed model can bridge the gap between the relative background frequency of the observed nucleotide and the gene's transcription rate. Conclusions We testify the proposed approach on two real-world microarray datasets. Experimental results show that the proposed model can effectively identify the parameters and the activity level of TF. Moreover, the kinetic parameters introduced in the proposed model can reveal more biological sense than previous models can do.

Mean multiplicity in the Regge models with rising cross sections

International Nuclear Information System (INIS)

Chikovani, Z.E.; Kobylisky, N.A.; Martynov, E.S.

1979-01-01

Behaviour of the mean multiplicity and the total cross section σsub(t) of hadron-hadron interactions is considered in the framework of the Regge models at high energies. Generating function was plotted for models of dipole and froissaron, and the mean multiplicity and multiplicity moments were calculated. It is shown that approximately ln 2 S (energy square) in the dipole model, which is in good agreement with the experiment. It is also found that in various Regge models approximately σsub(t)lnS

Do Knowledge-Component Models Need to Incorporate Representational Competencies?

Science.gov (United States)

Rau, Martina Angela

2017-01-01

Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…

Intelligent Decision Support in Proportional–Stop-Loss Reinsurance Using Multiple Attribute Decision-Making (MADM

Directory of Open Access Journals (Sweden)

Shirley Jie Xuan Wang

2017-11-01

Full Text Available This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. This article focuses on adopting more than one optimality criteria under a more generic combinational design of commonly used reinsurance products, i.e., proportional reinsurance and stop-loss reinsurance. In terms of methodology, the significant contribution of the study the incorporation of the well-established decision analysis tool multiple-attribute decision-making (MADM into the modelling of reinsurance selection. To illustrate the feasibility of incorporating intelligent decision supporting systems in the reinsurance market, the study includes a numerical case study using the simulation software @Risk in modeling insurance claims, as well as programming in MATLAB to realize MADM. A list of managerial implications could be drawn from the case study results. Most importantly, when choosing the most appropriate type of reinsurance, insurance companies should base their decisions on multiple measurements instead of single-criteria decision-making models so that their decisions may be more robust.

Tantalum strength model incorporating temperature, strain rate and pressure

Science.gov (United States)

Lim, Hojun; Battaile, Corbett; Brown, Justin; Lane, Matt

Tantalum is a body-centered-cubic (BCC) refractory metal that is widely used in many applications in high temperature, strain rate and pressure environments. In this work, we propose a physically-based strength model for tantalum that incorporates effects of temperature, strain rate and pressure. A constitutive model for single crystal tantalum is developed based on dislocation kink-pair theory, and calibrated to measurements on single crystal specimens. The model is then used to predict deformations of single- and polycrystalline tantalum. In addition, the proposed strength model is implemented into Sandia's ALEGRA solid dynamics code to predict plastic deformations of tantalum in engineering-scale applications at extreme conditions, e.g. Taylor impact tests and Z machine's high pressure ramp compression tests, and the results are compared with available experimental data. Sandia National Laboratories is a multi program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Multiple model adaptive control with mixing

Science.gov (United States)

Kuipers, Matthew

Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

Incorporation of essential oil in alginate microparticles by multiple emulsion/ionic gelation process.

Science.gov (United States)

Hosseini, Seyede Marzieh; Hosseini, Hedayat; Mohammadifar, Mohammad Amin; Mortazavian, Amir Mohammad; Mohammadi, Abdorreza; Khosravi-Darani, Kianoosh; Shojaee-Aliabadi, Saeedeh; Dehghan, Solmaz; Khaksar, Ramin

2013-11-01

In this study, an o/w/o multiple emulsion/ionic gelation method was developed for production of alginate microparticles loaded with Satureja hortensis essential oil (SEO). It was found that the essential oil concentration has significant influence on encapsulation efficiency (EE), loading capacity (LC) and size of microparticles. The values of EE, LC and particle mean diameter were about 52-66%, 20-26%, and 47-117 μm, respectively, when the initial SEO content was 1-3% (v/v) .The essential oil-loaded microparticles were porous, as displayed by scanning electron micrograph. The presence of SEO in alginate microparticles was confirmed by Fourier transform-infrared (FT-IR) spectroscopy and differential scanning calorimetry (DSC) analyses. SEO-loaded microparticles showed good antioxidant (with DPPH radical scavenging activity of 40.7-73.5%) and antibacterial properties; this effect was greatly improved when the concentration of SEO was 3% (v/v). S. aureus was found to be the most sensitive bacterium to SEO and showed a highest inhibition zone of 304.37 mm(2) in the microparticles incorporated with 3% (v/v) SEO. In vitro release studies showed an initial burst release and followed by a slow release. In addition, the release of SEO from the microparticles followed Fickian diffusion with acceptable release. Copyright © 2013 Elsevier B.V. All rights reserved.

Design of Xen Hybrid Multiple Police Model

Science.gov (United States)

Sun, Lei; Lin, Renhao; Zhu, Xianwei

2017-10-01

Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.

An improved analytical model of 4H-SiC MESFET incorporating bulk and interface trapping effects

Science.gov (United States)

Hema Lata Rao, M.; Narasimha Murty, N. V. L.

2015-01-01

An improved analytical model for the current—voltage (I-V) characteristics of the 4H-SiC metal semiconductor field effect transistor (MESFET) on a high purity semi-insulating (HPSI) substrate with trapping and thermal effects is presented. The 4H-SiC MESFET structure includes a stack of HPSI substrates and a uniformly doped channel layer. The trapping effects include both the effect of multiple deep-level traps in the substrate and surface traps between the gate to source/drain. The self-heating effects are also incorporated to obtain the accurate and realistic nature of the analytical model. The importance of the proposed model is emphasised through the inclusion of the recent and exact nature of the traps in the 4H-SiC HPSI substrate responsible for substrate compensation. The analytical model is used to exhibit DC I-V characteristics of the device with and without trapping and thermal effects. From the results, the current degradation is observed due to the surface and substrate trapping effects and the negative conductance introduced by the self-heating effect at a high drain voltage. The calculated results are compared with reported experimental and two-dimensional simulations (Silvaco®-TCAD). The proposed model also illustrates the effectiveness of the gate—source distance scaling effect compared to the gate—drain scaling effect in optimizing 4H-SiC MESFET performance. Results demonstrate that the proposed I-V model of 4H-SiC MESFET is suitable for realizing SiC based monolithic circuits (MMICs) on HPSI substrates.

An improved analytical model of 4H-SiC MESFET incorporating bulk and interface trapping effects

International Nuclear Information System (INIS)

Rao, M. Hema Lata; Murty, N. V. L. Narasimha

2015-01-01

An improved analytical model for the current—voltage (I–V) characteristics of the 4H-SiC metal semiconductor field effect transistor (MESFET) on a high purity semi-insulating (HPSI) substrate with trapping and thermal effects is presented. The 4H-SiC MESFET structure includes a stack of HPSI substrates and a uniformly doped channel layer. The trapping effects include both the effect of multiple deep-level traps in the substrate and surface traps between the gate to source/drain. The self-heating effects are also incorporated to obtain the accurate and realistic nature of the analytical model. The importance of the proposed model is emphasised through the inclusion of the recent and exact nature of the traps in the 4H-SiC HPSI substrate responsible for substrate compensation. The analytical model is used to exhibit DC I–V characteristics of the device with and without trapping and thermal effects. From the results, the current degradation is observed due to the surface and substrate trapping effects and the negative conductance introduced by the self-heating effect at a high drain voltage. The calculated results are compared with reported experimental and two-dimensional simulations (Silvaco®-TCAD). The proposed model also illustrates the effectiveness of the gate—source distance scaling effect compared to the gate—drain scaling effect in optimizing 4H-SiC MESFET performance. Results demonstrate that the proposed I–V model of 4H-SiC MESFET is suitable for realizing SiC based monolithic circuits (MMICs) on HPSI substrates. (semiconductor devices)

Modeling fraud detection and the incorporation of forensic specialists in the audit process

DEFF Research Database (Denmark)

Sakalauskaite, Dominyka

Financial statement audits are still comparatively poor in fraud detection. Forensic specialists can play a significant role in increasing audit quality. In this paper, based on prior academic research, I develop a model of fraud detection and the incorporation of forensic specialists in the audit...... process. The intention of the model is to identify the reasons why the audit is weak in fraud detection and to provide the analytical framework to assess whether the incorporation of forensic specialists can help to improve it. The results show that such specialists can potentially improve the fraud...... detection in the audit, but might also cause some negative implications. Overall, even though fraud detection is one of the main topics in research there are very few studies done on the subject of how auditors co-operate with forensic specialists. Thus, the paper concludes with suggestions for further...

A new adaptive control scheme based on the interacting multiple model (IMM) estimation

International Nuclear Information System (INIS)

Afshari, Hamed H.; Al-Ani, Dhafar; Habibi, Saeid

2016-01-01

In this paper, an Interacting multiple model (IMM) adaptive estimation approach is incorporated to design an optimal adaptive control law for stabilizing an Unmanned vehicle. Due to variations of the forward velocity of the Unmanned vehicle, its aerodynamic derivatives are constantly changing. In order to stabilize the unmanned vehicle and achieve the control objectives for in-flight conditions, one seeks for an adaptive control strategy that can adjust itself to varying flight conditions. In this context, a bank of linear models is used to describe the vehicle dynamics in different operating modes. Each operating mode represents a particular dynamic with a different forward velocity. These models are then used within an IMM filter containing a bank of Kalman filters (KF) in a parallel operating mechanism. To regulate and stabilize the vehicle, a Linear quadratic regulator (LQR) law is designed and implemented for each mode. The IMM structure determines the particular mode based on the stored models and in-flight input-output measurements. The LQR controller also provides a set of controllers; each corresponds to a particular flight mode and minimizes the tracking error. Finally, the ultimate control law is obtained as a weighted summation of all individual controllers whereas weights are obtained using mode probabilities of each operating mode.

Incorporating H2 Dynamics and Inhibition into a Microbially Based Methanogenesis Model for Restored Wetland Sediments

Science.gov (United States)

Pal, David; Jaffe, Peter

2015-04-01

Estimates of global CH4 emissions from wetlands indicate that wetlands are the largest natural source of CH4 to the atmosphere. In this paper, we propose that there is a missing component to these models that should be addressed. CH4 is produced in wetland sediments from the microbial degradation of organic carbon through multiple fermentation steps and methanogenesis pathways. There are multiple sources of carbon for methananogenesis; in vegetated wetland sediments, microbial communities consume root exudates as a major source of organic carbon. In many methane models propionate is used as a model carbon molecule. This simple sugar is fermented into acetate and H2, acetate is transformed to methane and CO2, while the H2 and CO2 are used to form an additional CH4 molecule. The hydrogenotrophic pathway involves the equilibrium of two dissolved gases, CH4 and H2. In an effort to limit CH4 emissions from wetlands, there has been growing interest in finding ways to limit plant transport of soil gases through root systems. Changing planted species, or genetically modifying new species of plants may control this transport of soil gases. While this may decrease the direct emissions of methane, there is little understanding about how H2 dynamics may feedback into overall methane production. The results of an incubation study were combined with a new model of propionate degradation for methanogenesis that also examines other natural parameters (i.e. gas transport through plants). This presentation examines how we would expect this model to behave in a natural field setting with changing sulfate and carbon loading schemes. These changes can be controlled through new plant species and other management practices. Next, we compare the behavior of two variations of this model, with or without the incorporation of H2 interactions, with changing sulfate, carbon loading and root volatilization. Results show that while the models behave similarly there may be a discrepancy of nearly

Incorporating damage mechanics into explosion simulation models

International Nuclear Information System (INIS)

Sammis, C.G.

1993-01-01

The source region of an underground explosion is commonly modeled as a nested series of shells. In the innermost open-quotes hydrodynamic regimeclose quotes pressures and temperatures are sufficiently high that the rock deforms as a fluid and may be described using a PVT equation of state. Just beyond the hydrodynamic regime, is the open-quotes non-linear regimeclose quotes in which the rock has shear strength but the deformation is nonlinear. This regime extends out to the open-quotes elastic radiusclose quotes beyond which the deformation is linear. In this paper, we develop a model for the non-linear regime in crystalline source rock where the nonlinearity is mostly due to fractures. We divide the non-linear regime into a open-quotes damage regimeclose quotes in which the stresses are sufficiently high to nucleate new fractures from preexisting ones and a open-quotes crack-slidingclose quotes regime where motion on preexisting cracks produces amplitude dependent attenuation and other non-linear effects, but no new cracks are nucleated. The boundary between these two regimes is called the open-quotes damage radius.close quotes The micromechanical damage mechanics recently developed by Ashby and Sammis (1990) is used to write an analytic expression for the damage radius in terms of the initial fracture spectrum of the source rock, and to develop an algorithm which may be used to incorporate damage mechanics into computer source models for the damage regime. Effects of water saturation and loading rate are also discussed

Supersymmetric U(1)' model with multiple dark matters

International Nuclear Information System (INIS)

Hur, Taeil; Lee, Hye-Sung; Nasri, Salah

2008-01-01

We consider a scenario where a supersymmetric model has multiple dark matter particles. Adding a U(1) ' gauge symmetry is a well-motivated extension of the minimal supersymmetric standard model (MSSM). It can cure the problems of the MSSM such as the μ problem or the proton decay problem with high-dimensional lepton number and baryon number violating operators which R parity allows. An extra parity (U parity) may arise as a residual discrete symmetry after U(1) ' gauge symmetry is spontaneously broken. The lightest U-parity particle (LUP) is stable under the new parity becoming a new dark matter candidate. Up to three massive particles can be stable in the presence of the R parity and the U parity. We numerically illustrate that multiple stable particles in our model can satisfy both constraints from the relic density and the direct detection, thus providing a specific scenario where a supersymmetric model has well-motivated multiple dark matters consistent with experimental constraints. The scenario provides new possibilities in the present and upcoming dark matter searches in the direct detection and collider experiments

Multiple Social Networks, Data Models and Measures for

DEFF Research Database (Denmark)

Magnani, Matteo; Rossi, Luca

2017-01-01

Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

A statistical model for aggregating judgments by incorporating peer predictions

OpenAIRE

McCoy, John; Prelec, Drazen

2017-01-01

We propose a probabilistic model to aggregate the answers of respondents answering multiple-choice questions. The model does not assume that everyone has access to the same information, and so does not assume that the consensus answer is correct. Instead, it infers the most probable world state, even if only a minority vote for it. Each respondent is modeled as receiving a signal contingent on the actual world state, and as using this signal to both determine their own answer and predict the ...

Multiple Response Regression for Gaussian Mixture Models with Known Labels.

Science.gov (United States)

Lee, Wonyul; Du, Ying; Sun, Wei; Hayes, D Neil; Liu, Yufeng

2012-12-01

Multiple response regression is a useful regression technique to model multiple response variables using the same set of predictor variables. Most existing methods for multiple response regression are designed for modeling homogeneous data. In many applications, however, one may have heterogeneous data where the samples are divided into multiple groups. Our motivating example is a cancer dataset where the samples belong to multiple cancer subtypes. In this paper, we consider modeling the data coming from a mixture of several Gaussian distributions with known group labels. A naive approach is to split the data into several groups according to the labels and model each group separately. Although it is simple, this approach ignores potential common structures across different groups. We propose new penalized methods to model all groups jointly in which the common and unique structures can be identified. The proposed methods estimate the regression coefficient matrix, as well as the conditional inverse covariance matrix of response variables. Asymptotic properties of the proposed methods are explored. Through numerical examples, we demonstrate that both estimation and prediction can be improved by modeling all groups jointly using the proposed methods. An application to a glioblastoma cancer dataset reveals some interesting common and unique gene relationships across different cancer subtypes.

Three-dimensional simulations of Bingham plastic flows with the multiple-relaxation-time lattice Boltzmann model

Directory of Open Access Journals (Sweden)

Song-Gui Chen

2016-01-01

Full Text Available This paper presents a three-dimensional (3D parallel multiple-relaxation-time lattice Boltzmann model (MRT-LBM for Bingham plastics which overcomes numerical instabilities in the simulation of non-Newtonian fluids for the Bhatnagar–Gross–Krook (BGK model. The MRT-LBM and several related mathematical models are briefly described. Papanastasiou’s modified model is incorporated for better numerical stability. The impact of the relaxation parameters of the model is studied in detail. The MRT-LBM is then validated through a benchmark problem: a 3D steady Poiseuille flow. The results from the numerical simulations are consistent with those derived analytically which indicates that the MRT-LBM effectively simulates Bingham fluids but with better stability. A parallel MRT-LBM framework is introduced, and the parallel efficiency is tested through a simple case. The MRT-LBM is shown to be appropriate for parallel implementation and to have high efficiency. Finally, a Bingham fluid flowing past a square-based prism with a fixed sphere is simulated. It is found the drag coefficient is a function of both Reynolds number (Re and Bingham number (Bn. These results reveal the flow behavior of Bingham plastics.

SDG and qualitative trend based model multiple scale validation

Science.gov (United States)

Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike

2017-09-01

Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

A Multiple Items EPQ/EOQ Model for a Vendor and Multiple Buyers System with Considering Continuous and Discrete Demand Simultaneously

Science.gov (United States)

Jonrinaldi; Rahman, T.; Henmaidi; Wirdianto, E.; Zhang, D. Z.

2018-03-01

This paper proposed a mathematical model for multiple items Economic Production and Order Quantity (EPQ/EOQ) with considering continuous and discrete demand simultaneously in a system consisting of a vendor and multiple buyers. This model is used to investigate the optimal production lot size of the vendor and the number of shipments policy of orders to multiple buyers. The model considers the multiple buyers’ holding cost as well as transportation cost, which minimize the total production and inventory costs of the system. The continuous demand from any other customers can be fulfilled anytime by the vendor while the discrete demand from multiple buyers can be fulfilled by the vendor using the multiple delivery policy with a number of shipments of items in the production cycle time. A mathematical model is developed to illustrate the system based on EPQ and EOQ model. Solution procedures are proposed to solve the model using a Mixed Integer Non Linear Programming (MINLP) and algorithm methods. Then, the numerical example is provided to illustrate the system and results are discussed.

Incorporating vehicle mix in stimulus-response car-following models

Directory of Open Access Journals (Sweden)

Saidi Siuhi

2016-06-01

Full Text Available The objective of this paper is to incorporate vehicle mix in stimulus-response car-following models. Separate models were estimated for acceleration and deceleration responses to account for vehicle mix via both movement state and vehicle type. For each model, three sub-models were developed for different pairs of following vehicles including “automobile following automobile,” “automobile following truck,” and “truck following automobile.” The estimated model parameters were then validated against other data from a similar region and roadway. The results indicated that drivers' behaviors were significantly different among the different pairs of following vehicles. Also the magnitude of the estimated parameters depends on the type of vehicle being driven and/or followed. These results demonstrated the need to use separate models depending on movement state and vehicle type. The differences in parameter estimates confirmed in this paper highlight traffic safety and operational issues of mixed traffic operation on a single lane. The findings of this paper can assist transportation professionals to improve traffic simulation models used to evaluate the impact of different strategies on ameliorate safety and performance of highways. In addition, driver response time lag estimates can be used in roadway design to calculate important design parameters such as stopping sight distance on horizontal and vertical curves for both automobiles and trucks.

A data-driven model for influenza transmission incorporating media effects.

Science.gov (United States)

Mitchell, Lewis; Ross, Joshua V

2016-10-01

Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza; however, quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of 'big data' coming from online social media and the like, large volumes of data on a population's engagement with mass media during an epidemic are becoming available to researchers. In this study, we combine an online dataset comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data, we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies.

Incorporating microbiota data into epidemiologic models: examples from vaginal microbiota research.

Science.gov (United States)

van de Wijgert, Janneke H; Jespers, Vicky

2016-05-01

Next generation sequencing and quantitative polymerase chain reaction technologies are now widely available, and research incorporating these methods is growing exponentially. In the vaginal microbiota (VMB) field, most research to date has been descriptive. The purpose of this article is to provide an overview of different ways in which next generation sequencing and quantitative polymerase chain reaction data can be used to answer clinical epidemiologic research questions using examples from VMB research. We reviewed relevant methodological literature and VMB articles (published between 2008 and 2015) that incorporated these methodologies. VMB data have been analyzed using ecologic methods, methods that compare the presence or relative abundance of individual taxa or community compositions between different groups of women or sampling time points, and methods that first reduce the complexity of the data into a few variables followed by the incorporation of these variables into traditional biostatistical models. To make future VMB research more clinically relevant (such as studying associations between VMB compositions and clinical outcomes and the effects of interventions on the VMB), it is important that these methods are integrated with rigorous epidemiologic methods (such as appropriate study designs, sampling strategies, and adjustment for confounding). Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Multiple commodities in statistical microeconomics: Model and market

Science.gov (United States)

Baaquie, Belal E.; Yu, Miao; Du, Xin

2016-11-01

A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

AgMIP Training in Multiple Crop Models and Tools

Science.gov (United States)

Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

2015-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

Organizational culture shapes the adoption and incorporation of simulation into nursing curricula: a grounded theory study.

Science.gov (United States)

Taplay, Karyn; Jack, Susan M; Baxter, Pamela; Eva, Kevin; Martin, Lynn

2014-01-01

Purpose. To create a substantive mid-range theory explaining how the organizational cultures of undergraduate nursing programs shape the adoption and incorporation of mid-to high-level technical fidelity simulators as a teaching strategy within curricula. Method. A constructivist grounded theory was used to guide this study which was conducted in Ontario, Canada, during 2011-12. Semistructured interviews (n = 43) with participants that included nursing administrators, nursing faculty, and simulation leaders across multiple programs (n = 13) informed this study. Additionally, key documents (n = 67) were reviewed. Purposeful and theoretical sampling was used and data were collected and analyzed simultaneously. Data were compared among and between sites. Findings. The organizational elements that shape simulation in nursing (OESSN) model depicts five key organizational factors at the nursing program level that shaped the adoption and incorporation of simulation: (1) leaders working in tandem, (2) information exchange, (3) physical locale, (4) shared motivators, and (5) scaffolding to manage change. Conclusions. The OESSN model provides an explanation of the organizational factors that contributed to the adoption and incorporation of simulation into nursing curricula. Nursing programs that use the OESSN model may experience a more rapid or broad uptake of simulation when organizational factors that impact adoption and incorporation are considered and planned for.

Incorporating Social Anxiety Into a Model of College Problem Drinking: Replication and Extension

OpenAIRE

Ham, Lindsay S.; Hope, Debra A.

2006-01-01

Although research has found an association between social anxiety and alcohol use in noncollege samples, results have been mixed for college samples. College students face many novel social situations in which they may drink to reduce social anxiety. In the current study, the authors tested a model of college problem drinking, incorporating social anxiety and related psychosocial variables among 228 undergraduate volunteers. According to structural equation modeling (SEM) results, social anxi...

Efficient Adoption and Assessment of Multiple Process Improvement Reference Models

Directory of Open Access Journals (Sweden)

Simona Jeners

2013-06-01

Full Text Available A variety of reference models such as CMMI, COBIT or ITIL support IT organizations to improve their processes. These process improvement reference models (IRMs cover different domains such as IT development, IT Services or IT Governance but also share some similarities. As there are organizations that address multiple domains and need to coordinate their processes in their improvement we present MoSaIC, an approach to support organizations to efficiently adopt and conform to multiple IRMs. Our solution realizes a semantic integration of IRMs based on common meta-models. The resulting IRM integration model enables organizations to efficiently implement and asses multiple IRMs and to benefit from synergy effects.

Incorporating ligament laxity in a finite element model for the upper cervical spine.

Science.gov (United States)

Lasswell, Timothy L; Cronin, Duane S; Medley, John B; Rasoulinejad, Parham

2017-11-01

Predicting physiological range of motion (ROM) using a finite element (FE) model of the upper cervical spine requires the incorporation of ligament laxity. The effect of ligament laxity can be observed only on a macro level of joint motion and is lost once ligaments have been dissected and preconditioned for experimental testing. As a result, although ligament laxity values are recognized to exist, specific values are not directly available in the literature for use in FE models. The purpose of the current study is to propose an optimization process that can be used to determine a set of ligament laxity values for upper cervical spine FE models. Furthermore, an FE model that includes ligament laxity is applied, and the resulting ROM values are compared with experimental data for physiological ROM, as well as experimental data for the increase in ROM when a Type II odontoid fracture is introduced. The upper cervical spine FE model was adapted from a 50th percentile male full-body model developed with the Global Human Body Models Consortium (GHBMC). FE modeling was performed in LS-DYNA and LS-OPT (Livermore Software Technology Group) was used for ligament laxity optimization. Ordinate-based curve matching was used to minimize the mean squared error (MSE) between computed load-rotation curves and experimental load-rotation curves under flexion, extension, and axial rotation with pure moment loads from 0 to 3.5 Nm. Lateral bending was excluded from the optimization because the upper cervical spine was considered to be primarily responsible for flexion, extension, and axial rotation. Based on recommendations from the literature, four varying inputs representing laxity in select ligaments were optimized to minimize the MSE. Funding was provided by the Natural Sciences and Engineering Research Council of Canada as well as GHMBC. The present study was funded by the Natural Sciences and Engineering Research Council of Canada to support the work of one graduate student

Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

Directory of Open Access Journals (Sweden)

Quanzhen Huang

2017-01-01

Full Text Available Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

[Incorporation of an organic MAGIC (Model of Acidification of Groundwater in Catchments) and testing of the revised model using independent data sources]. [MAGIC Model

Energy Technology Data Exchange (ETDEWEB)

Sullivan, T.J.

1992-09-01

A project was initiated in March, 1992 to (1) incorporate a rigorous organic acid representation, based on empirical data and geochemical considerations, into the MAGIC model of acidification response, and (2) test the revised model using three sets of independent data. After six months of performance, the project is on schedule and the majority of the tasks outlined for Year 1 have been successfully completed. Major accomplishments to data include development of the organic acid modeling approach, using data from the Adirondack Lakes Survey Corporation (ALSC), and coupling the organic acid model with MAGIC for chemical hindcast comparisons. The incorporation of an organic acid representation into MAGIC can account for much of the discrepancy earlier observed between MAGIC hindcasts and paleolimnological reconstructions of preindustrial pH and alkalinity for 33 statistically-selected Adirondack lakes. Additional work is on-going for model calibration and testing with data from two whole-catchment artificial acidification projects. Results obtained thus far are being prepared as manuscripts for submission to the peer-reviewed scientific literature.

Translation system engineering in Escherichia coli enhances non-canonical amino acid incorporation into proteins.

Science.gov (United States)

Gan, Rui; Perez, Jessica G; Carlson, Erik D; Ntai, Ioanna; Isaacs, Farren J; Kelleher, Neil L; Jewett, Michael C

2017-05-01

The ability to site-specifically incorporate non-canonical amino acids (ncAAs) into proteins has made possible the study of protein structure and function in fundamentally new ways, as well as the bio synthesis of unnatural polymers. However, the task of site-specifically incorporating multiple ncAAs into proteins with high purity and yield continues to present a challenge. At the heart of this challenge lies the lower efficiency of engineered orthogonal translation system components compared to their natural counterparts (e.g., translation elements that specifically use a ncAA and do not interact with the cell's natural translation apparatus). Here, we show that evolving and tuning expression levels of multiple components of an engineered translation system together as a whole enhances ncAA incorporation efficiency. Specifically, we increase protein yield when incorporating multiple p-azido-phenylalanine(pAzF) residues into proteins by (i) evolving the Methanocaldococcus jannaschii p-azido-phenylalanyl-tRNA synthetase anti-codon binding domain, (ii) evolving the elongation factor Tu amino acid-binding pocket, and (iii) tuning the expression of evolved translation machinery components in a single vector. Use of the evolved translation machinery in a genomically recoded organism lacking release factor one enabled enhanced multi-site ncAA incorporation into proteins. We anticipate that our approach to orthogonal translation system development will accelerate and expand our ability to site-specifically incorporate multiple ncAAs into proteins and biopolymers, advancing new horizons for synthetic and chemical biotechnology. Biotechnol. Bioeng. 2017;114: 1074-1086. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Are adverse effects incorporated in economic models? An initial review of current practice.

Science.gov (United States)

Craig, D; McDaid, C; Fonseca, T; Stock, C; Duffy, S; Woolacott, N

2009-12-01

To identify methodological research on the incorporation of adverse effects in economic models and to review current practice. Major electronic databases (Cochrane Methodology Register, Health Economic Evaluations Database, NHS Economic Evaluation Database, EconLit, EMBASE, Health Management Information Consortium, IDEAS, MEDLINE and Science Citation Index) were searched from inception to September 2007. Health technology assessment (HTA) reports commissioned by the National Institute for Health Research (NIHR) HTA programme and published between 2004 and 2007 were also reviewed. The reviews of methodological research on the inclusion of adverse effects in decision models and of current practice were carried out according to standard methods. Data were summarised in a narrative synthesis. Of the 719 potentially relevant references in the methodological research review, five met the inclusion criteria; however, they contained little information of direct relevance to the incorporation of adverse effects in models. Of the 194 HTA monographs published from 2004 to 2007, 80 were reviewed, covering a range of research and therapeutic areas. In total, 85% of the reports included adverse effects in the clinical effectiveness review and 54% of the decision models included adverse effects in the model; 49% included adverse effects in the clinical review and model. The link between adverse effects in the clinical review and model was generally weak; only 3/80 (manipulation. Of the models including adverse effects, 67% used a clinical adverse effects parameter, 79% used a cost of adverse effects parameter, 86% used one of these and 60% used both. Most models (83%) used utilities, but only two (2.5%) used solely utilities to incorporate adverse effects and were explicit that the utility captured relevant adverse effects; 53% of those models that included utilities derived them from patients on treatment and could therefore be interpreted as capturing adverse effects. In total

Integrating multiple distribution models to guide conservation efforts of an endangered toad

Science.gov (United States)

Treglia, Michael L.; Fisher, Robert N.; Fitzgerald, Lee A.

2015-01-01

Species distribution models are used for numerous purposes such as predicting changes in species’ ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad (Anaxyrus californicus), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species’ current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.

Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

Science.gov (United States)

Dawicke, D. S.; Newman, J. C., Jr.

1992-08-01

A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

Analysis and prediction of Multiple-Site Damage (MSD) fatigue crack growth

Science.gov (United States)

Dawicke, D. S.; Newman, J. C., Jr.

1992-01-01

A technique was developed to calculate the stress intensity factor for multiple interacting cracks. The analysis was verified through comparison with accepted methods of calculating stress intensity factors. The technique was incorporated into a fatigue crack growth prediction model and used to predict the fatigue crack growth life for multiple-site damage (MSD). The analysis was verified through comparison with experiments conducted on uniaxially loaded flat panels with multiple cracks. Configuration with nearly equal and unequal crack distribution were examined. The fatigue crack growth predictions agreed within 20 percent of the experimental lives for all crack configurations considered.

A test for the parameters of multiple linear regression models ...

African Journals Online (AJOL)

A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...

Incorporation of chemical kinetic models into process control

International Nuclear Information System (INIS)

Herget, C.J.; Frazer, J.W.

1981-01-01

An important consideration in chemical process control is to determine the precise rationing of reactant streams, particularly when a large time delay exists between the mixing of the reactants and the measurement of the product. In this paper, a method is described for incorporating chemical kinetic models into the control strategy in order to achieve optimum operating conditions. The system is first characterized by determining a reaction rate surface as a function of all input reactant concentrations over a feasible range. A nonlinear constrained optimization program is then used to determine the combination of reactants which produces the specified yield at minimum cost. This operating condition is then used to establish the nominal concentrations of the reactants. The actual operation is determined through a feedback control system employing a Smith predictor. The method is demonstrated on a laboratory bench scale enzyme reactor

Parametric modeling for damped sinusoids from multiple channels

DEFF Research Database (Denmark)

Zhou, Zhenhua; So, Hing Cheung; Christensen, Mads Græsbøll

2013-01-01

frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages......The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct...... of the proposed multi-channel sinusoidal modeling methodology compared with existing methods....

Incorporation of detailed eye model into polygon-mesh versions of ICRP-110 reference phantoms.

Science.gov (United States)

Nguyen, Thang Tat; Yeom, Yeon Soo; Kim, Han Sung; Wang, Zhao Jun; Han, Min Cheol; Kim, Chan Hyeong; Lee, Jai Ki; Zankl, Maria; Petoussi-Henss, Nina; Bolch, Wesley E; Lee, Choonsik; Chung, Beom Sun

2015-11-21

The dose coefficients for the eye lens reported in ICRP 2010 Publication 116 were calculated using both a stylized model and the ICRP-110 reference phantoms, according to the type of radiation, energy, and irradiation geometry. To maintain consistency of lens dose assessment, in the present study we incorporated the ICRP-116 detailed eye model into the converted polygon-mesh (PM) version of the ICRP-110 reference phantoms. After the incorporation, the dose coefficients for the eye lens were calculated and compared with those of the ICRP-116 data. The results showed generally a good agreement between the newly calculated lens dose coefficients and the values of ICRP 2010 Publication 116. Significant differences were found for some irradiation cases due mainly to the use of different types of phantoms. Considering that the PM version of the ICRP-110 reference phantoms preserve the original topology of the ICRP-110 reference phantoms, it is believed that the PM version phantoms, along with the detailed eye model, provide more reliable and consistent dose coefficients for the eye lens.

Modeling Carbon Turnover in Five Terrestrial Ecosystems in the Boreal Zone Using Multiple Criteria of Acceptance

International Nuclear Information System (INIS)

Karlberg, Louise; Gustafsson, David; Jansson, Per-Erik

2006-01-01

Estimates of carbon fluxes and turnover in ecosystems are key elements in the understanding of climate change and in predicting the accumulation of trace elements in the biosphere. In this paper we present estimates of carbon fluxes and turnover times for five terrestrial ecosystems using a modeling approach. Multiple criteria of acceptance were used to parameterize the model, thus incorporating large amounts of multi-faceted empirical data in the simulations in a standardized manner. Mean turnover times of carbon were found to be rather similar between systems with a few exceptions, even though the size of both the pools and the fluxes varied substantially. Depending on the route of the carbon through the ecosystem, turnover times varied from less than one year to more than one hundred, which may be of importance when considering trace element transport and retention. The parameterization method was useful both in the estimation of unknown parameters, and to identify variability in carbon turnover in the selected ecosystems

Application of Multiple Evaluation Models in Brazil

Directory of Open Access Journals (Sweden)

Rafael Victal Saliba

2008-07-01

Full Text Available Based on two different samples, this article tests the performance of a number of Value Drivers commonly used for evaluating companies by finance practitioners, through simple regression models of cross-section type which estimate the parameters associated to each Value Driver, denominated Market Multiples. We are able to diagnose the behavior of several multiples in the period 1994-2004, with an outlook also on the particularities of the economic activities performed by the sample companies (and their impacts on the performance through a subsequent analysis with segregation of companies in the sample by sectors. Extrapolating simple multiples evaluation standards from analysts of the main financial institutions in Brazil, we find that adjusting the ratio formulation to allow for an intercept does not provide satisfactory results in terms of pricing errors reduction. Results found, in spite of evidencing certain relative and absolute superiority among the multiples, may not be generically representative, given samples limitation.

Formulation of an explicit-multiple-time-step time integration method for use in a global primitive equation grid model

Science.gov (United States)

Chao, W. C.

1982-01-01

With appropriate modifications, a recently proposed explicit-multiple-time-step scheme (EMTSS) is incorporated into the UCLA model. In this scheme, the linearized terms in the governing equations that generate the gravity waves are split into different vertical modes. Each mode is integrated with an optimal time step, and at periodic intervals these modes are recombined. The other terms are integrated with a time step dictated by the CFL condition for low-frequency waves. This large time step requires a special modification of the advective terms in the polar region to maintain stability. Test runs for 72 h show that EMTSS is a stable, efficient and accurate scheme.

Deterministic integer multiple firing depending on initial state in Wang model

Energy Technology Data Exchange (ETDEWEB)

Xie Yong [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)]. E-mail: yxie@mail.xjtu.edu.cn; Xu Jianxue [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China); Jiang Jun [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)

2006-12-15

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables.

Deterministic integer multiple firing depending on initial state in Wang model

International Nuclear Information System (INIS)

Xie Yong; Xu Jianxue; Jiang Jun

2006-01-01

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables

Multiple regression and beyond an introduction to multiple regression and structural equation modeling

CERN Document Server

Keith, Timothy Z

2014-01-01

Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

Predicting the oral pharmacokinetic profiles of multiple-unit (pellet) dosage forms using a modeling and simulation approach coupled with biorelevant dissolution testing: case example diclofenac sodium.

Science.gov (United States)

Kambayashi, Atsushi; Blume, Henning; Dressman, Jennifer B

2014-07-01

The objective of this research was to characterize the dissolution profile of a poorly soluble drug, diclofenac, from a commercially available multiple-unit enteric coated dosage form, Diclo-Puren® capsules, and to develop a predictive model for its oral pharmacokinetic profile. The paddle method was used to obtain the dissolution profiles of this dosage form in biorelevant media, with the exposure to simulated gastric conditions being varied in order to simulate the gastric emptying behavior of pellets. A modified Noyes-Whitney theory was subsequently fitted to the dissolution data. A physiologically-based pharmacokinetic (PBPK) model for multiple-unit dosage forms was designed using STELLA® software and coupled with the biorelevant dissolution profiles in order to simulate the plasma concentration profiles of diclofenac from Diclo-Puren® capsule in both the fasted and fed state in humans. Gastric emptying kinetics relevant to multiple-units pellets were incorporated into the PBPK model by setting up a virtual patient population to account for physiological variations in emptying kinetics. Using in vitro biorelevant dissolution coupled with in silico PBPK modeling and simulation it was possible to predict the plasma profile of this multiple-unit formulation of diclofenac after oral administration in both the fasted and fed state. This approach might be useful to predict variability in the plasma profiles for other drugs housed in multiple-unit dosage forms. Copyright © 2014 Elsevier B.V. All rights reserved.

New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

DEFF Research Database (Denmark)

Dong, Yiqiu; Zeng, Tieyong

2013-01-01

A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

Fuzzy Logic-Based Model That Incorporates Personality Traits for Heterogeneous Pedestrians

Directory of Open Access Journals (Sweden)

Zhuxin Xue

2017-10-01

Full Text Available Most models designed to simulate pedestrian dynamical behavior are based on the assumption that human decision-making can be described using precise values. This study proposes a new pedestrian model that incorporates fuzzy logic theory into a multi-agent system to address cognitive behavior that introduces uncertainty and imprecision during decision-making. We present a concept of decision preferences to represent the intrinsic control factors of decision-making. To realize the different decision preferences of heterogeneous pedestrians, the Five-Factor (OCEAN personality model is introduced to model the psychological characteristics of individuals. Then, a fuzzy logic-based approach is adopted for mapping the relationships between the personality traits and the decision preferences. Finally, we have developed an application using our model to simulate pedestrian dynamical behavior in several normal or non-panic scenarios, including a single-exit room, a hallway with obstacles, and a narrowing passage. The effectiveness of the proposed model is validated with a user study. The results show that the proposed model can generate more reasonable and heterogeneous behavior in the simulation and indicate that individual personality has a noticeable effect on pedestrian dynamical behavior.

Comparison in the calculation of committed effective dose using the ICRP 30 and ICRP 60 models for a repeated incorporation by inhalation of I-125; Comparacion en el calculo de la dosis efectiva comprometida usando los modelos del ICRP 30 y del ICRP 60 para una incorporacion repetida por inhalacion de I-125

Energy Technology Data Exchange (ETDEWEB)

Carreno P, A.L.; Cortes C, A. [CNSNS, Dr. Barragan 779, Col. Narvarte, Mexico D.F. (Mexico); Alonso V, G.; Serrano P, F. [IPN, Edificio de Fisica Avanzada Zacatenco, 07300 Mexico D.F. (Mexico)

2005-07-01

Presently work, a comparison in the calculation of committed effective dose using the models of the ICRP 30 and those of the ICRP 60 for the analysis of internal dose due to repeated incorporation of I-125 is shown. The estimations of incorporated activity are obtained starting from the proportionate data for an exercise of inter comparison, with which it should be determined the internal dose later on. For to estimate the initial activity incorporated by repeated dose was assumed that this it was given through of multiple individual incorporations which happened in the middle points of the monitoring periods. The results using the models of the ICRP 30 and of the ICRP 60 are compared and the causes of the differences are analyzed. (Author)

Mathematical Modeling of Loop Heat Pipes with Multiple Capillary Pumps and Multiple Condensers. Part 1; Stead State Stimulations

Science.gov (United States)

Hoang, Triem T.; OConnell, Tamara; Ku, Jentung

2004-01-01

Loop Heat Pipes (LHPs) have proven themselves as reliable and robust heat transport devices for spacecraft thermal control systems. So far, the LHPs in earth-orbit satellites perform very well as expected. Conventional LHPs usually consist of a single capillary pump for heat acquisition and a single condenser for heat rejection. Multiple pump/multiple condenser LHPs have shown to function very well in ground testing. Nevertheless, the test results of a dual pump/condenser LHP also revealed that the dual LHP behaved in a complicated manner due to the interaction between the pumps and condensers. Thus it is redundant to say that more research is needed before they are ready for 0-g deployment. One research area that perhaps compels immediate attention is the analytical modeling of LHPs, particularly the transient phenomena. Modeling a single pump/single condenser LHP is difficult enough. Only a handful of computer codes are available for both steady state and transient simulations of conventional LHPs. No previous effort was made to develop an analytical model (or even a complete theory) to predict the operational behavior of the multiple pump/multiple condenser LHP systems. The current research project offered a basic theory of the multiple pump/multiple condenser LHP operation. From it, a computer code was developed to predict the LHP saturation temperature in accordance with the system operating and environmental conditions.

Developing a stochastic parameterization to incorporate plant trait variability into ecohydrologic modeling

Science.gov (United States)

Liu, S.; Ng, G. H. C.

2017-12-01

The global plant database has revealed that plant traits can vary more within a plant functional type (PFT) than among different PFTs, indicating that the current paradigm in ecohydrogical models of specifying fixed parameters based solely on plant functional type (PFT) could potentially bias simulations. Although some recent modeling studies have attempted to incorporate this observed plant trait variability, many failed to consider uncertainties due to sparse global observation, or they omitted spatial and/or temporal variability in the traits. Here we present a stochastic parameterization for prognostic vegetation simulations that are stochastic in time and space in order to represent plant trait plasticity - the process by which trait differences arise. We have developed the new PFT parameterization within the Community Land Model 4.5 (CLM 4.5) and tested the method for a desert shrubland watershed in the Mojave Desert, where fixed parameterizations cannot represent acclimation to desert conditions. Spatiotemporally correlated plant trait parameters were first generated based on TRY statistics and were then used to implement ensemble runs for the study area. The new PFT parameterization was then further conditioned on field measurements of soil moisture and remotely sensed observations of leaf-area-index to constrain uncertainties in the sparse global database. Our preliminary results show that incorporating data-conditioned, variable PFT parameterizations strongly affects simulated soil moisture and water fluxes, compared with default simulations. The results also provide new insights about correlations among plant trait parameters and between traits and environmental conditions in the desert shrubland watershed. Our proposed stochastic PFT parameterization method for ecohydrological models has great potential in advancing our understanding of how terrestrial ecosystems are predicted to adapt to variable environmental conditions.

Adolescent Decision-Making Processes regarding University Entry: A Model Incorporating Cultural Orientation, Motivation and Occupational Variables

Science.gov (United States)

Jung, Jae Yup

2013-01-01

This study tested a newly developed model of the cognitive decision-making processes of senior high school students related to university entry. The model incorporated variables derived from motivation theory (i.e. expectancy-value theory and the theory of reasoned action), literature on cultural orientation and occupational considerations. A…

A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

Directory of Open Access Journals (Sweden)

Lewei Duan

2013-01-01

Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

Predictive performance models and multiple task performance

Science.gov (United States)

Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

1989-01-01

Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

A multiple choice decision analysis: an integrated QFD – AHP model ...

African Journals Online (AJOL)

The aim of this work is to propose a new methodological approach to define customer specifications through the employment of an integrated Quality Function Deployment (QFD) – Analytic Hierarchy Process (AHP) model. The model, which is loosely based on QFD, incorporates the AHP approach to delineate and rank the ...

A Mass Balance Model for Designing Green Roof Systems that Incorporate a Cistern for Re-Use

Directory of Open Access Journals (Sweden)

Manoj Chopra

2012-11-01

Full Text Available Green roofs, which have been used for several decades in many parts of the world, offer a unique and sustainable approach to stormwater management. Within this paper, evidence is presented on water retention for an irrigated green roof system. The presented green roof design results in a water retention volume on site. A first principle mass balance computer model is introduced to assist with the design of these green roof systems which incorporate a cistern to capture and reuse runoff waters for irrigation of the green roof. The model is used to estimate yearly stormwater retention volume for different cistern storage volumes. Additionally, the Blaney and Criddle equation is evaluated for estimation of monthly evapotranspiration rates for irrigated systems and incorporated into the model. This is done so evapotranspiration rates can be calculated for regions where historical data does not exist, allowing the model to be used anywhere historical weather data are available. This model is developed and discussed within this paper as well as compared to experimental results.

MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.

Science.gov (United States)

Tuta, Jure; Juric, Matjaz B

2018-03-24

This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method

Directory of Open Access Journals (Sweden)

Jure Tuta

2018-03-01

Full Text Available This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method, a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.. Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

Petroacoustic Modelling of Heterolithic Sandstone Reservoirs: A Novel Approach to Gassmann Modelling Incorporating Sedimentological Constraints and NMR Porosity data

Science.gov (United States)

Matthews, S.; Lovell, M.; Davies, S. J.; Pritchard, T.; Sirju, C.; Abdelkarim, A.

2012-12-01

Heterolithic or 'shaly' sandstone reservoirs constitute a significant proportion of hydrocarbon resources. Petroacoustic models (a combination of petrophysics and rock physics) enhance the ability to extract reservoir properties from seismic data, providing a connection between seismic and fine-scale rock properties. By incorporating sedimentological observations these models can be better constrained and improved. Petroacoustic modelling is complicated by the unpredictable effects of clay minerals and clay-sized particles on geophysical properties. Such effects are responsible for erroneous results when models developed for "clean" reservoirs - such as Gassmann's equation (Gassmann, 1951) - are applied to heterolithic sandstone reservoirs. Gassmann's equation is arguably the most popular petroacoustic modelling technique in the hydrocarbon industry and is used to model elastic effects of changing reservoir fluid saturations. Successful implementation of Gassmann's equation requires well-constrained drained rock frame properties, which in heterolithic sandstones are heavily influenced by reservoir sedimentology, particularly clay distribution. The prevalent approach to categorising clay distribution is based on the Thomas - Stieber model (Thomas & Stieber, 1975), this approach is inconsistent with current understanding of 'shaly sand' sedimentology and omits properties such as sorting and grain size. The novel approach presented here demonstrates that characterising reservoir sedimentology constitutes an important modelling phase. As well as incorporating sedimentological constraints, this novel approach also aims to improve drained frame moduli estimates through more careful consideration of Gassmann's model assumptions and limitations. A key assumption of Gassmann's equation is a pore space in total communication with movable fluids. This assumption is often violated by conventional applications in heterolithic sandstone reservoirs where effective porosity, which

A realistic closed-form radiobiological model of clinical tumor-control data incorporating intertumor heterogeneity

International Nuclear Information System (INIS)

Roberts, Stephen A.; Hendry, Jolyon H.

1998-01-01

Purpose: To investigate the role of intertumor heterogeneity in clinical tumor control datasets and the relationship to in vitro measurements of tumor biopsy samples. Specifically, to develop a modified linear-quadratic (LQ) model incorporating such heterogeneity that it is practical to fit to clinical tumor-control datasets. Methods and Materials: We developed a modified version of the linear-quadratic (LQ) model for tumor control, incorporating a (lagged) time factor to allow for tumor cell repopulation. We explicitly took into account the interpatient heterogeneity in clonogen number, radiosensitivity, and repopulation rate. Using this model, we could generate realistic TCP curves using parameter estimates consistent with those reported from in vitro studies, subject to the inclusion of a radiosensitivity (or dose)-modifying factor. We then demonstrated that the model was dominated by the heterogeneity in α (tumor radiosensitivity) and derived an approximate simplified model incorporating this heterogeneity. This simplified model is expressible in a compact closed form, which it is practical to fit to clinical datasets. Using two previously analysed datasets, we fit the model using direct maximum-likelihood techniques and obtained parameter estimates that were, again, consistent with the experimental data on the radiosensitivity of primary human tumor cells. This heterogeneity model includes the same number of adjustable parameters as the standard LQ model. Results: The modified model provides parameter estimates that can easily be reconciled with the in vitro measurements. The simplified (approximate) form of the heterogeneity model is a compact, closed-form probit function that can readily be fitted to clinical series by conventional maximum-likelihood methodology. This heterogeneity model provides a slightly better fit to the datasets than the conventional LQ model, with the same numbers of fitted parameters. The parameter estimates of the clinically

Multiple causes of nonstationarity in the Weihe annual low-flow series

Science.gov (United States)

Xiong, Bin; Xiong, Lihua; Chen, Jie; Xu, Chong-Yu; Li, Lingqi

2018-02-01

Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial

Quantum Chemical Examination of the Sequential Halogen Incorporation Scheme for the Modeling of Speciation of I/Br/Cl-Containing Trihalomethanes.

Science.gov (United States)

Zhang, Chenyang; Li, Maodong; Han, Xuze; Yan, Mingquan

2018-02-20

The recently developed three-step ternary halogenation model interprets the incorporation of chlorine, bromine, and iodine ions into natural organic matter (NOM) and formation of iodine-, bromine-, and chlorine-containing trihalomethanes (THMs) based on the competition of iodine, bromine, and chlorine species at each node of the halogenation sequence. This competition is accounted for using the dimensionless ratios (denoted as γ) of kinetic rates of reactions of the initial attack sites or halogenated intermediates with chlorine, bromine, and iodine ions. However, correlations between the model predictions made and mechanistic aspects of the incorporation of halogen species need to be ascertained in more detail. In this study, quantum chemistry calculations were first used to probe the formation mechanism of 10 species of Cl-/Br-/I- THMs. The HOMO energy (E HOMO ) of each mono-, bi-, or trihalomethanes were calculated by B3LYP method in Gaussian 09 software. Linear correlations were found to exist between the logarithms of experimentally determined kinetic preference coefficients γ reported in prior research and, on the other hand, differences of E HOMO values between brominated/iodinated and chlorinated halomethanes. One notable exception from this trend was that observed for the incorporation of iodine into mono- and di-iodinated intermediates. These observations confirm the three-step halogen incorporation sequence and the factor γ in the statistical model. The combined use of quantum chemistry calculations and the ternary sequential halogenation model provides a new insight into the microscopic nature of NOM-halogen interactions and the trends seen in the behavior of γ factors incorporated in the THM speciation models.

Multiplicity Analysis during Photon Interrogation of Fissionable Material

International Nuclear Information System (INIS)

Clarke, Shaun D.; Pozzi, Sara A.; Padovani, Enrico; Downar, Thomas J.

2007-01-01

Simulation of multiplicity distributions with the Monte Carlo method is difficult because each history is treated individually. In order to accurately model the multiplicity distribution, the intensity and time width of the interrogation pulse must be incorporated into the calculation. This behavior dictates how many photons arrive at the target essentially simultaneously. In order to model the pulse width correctly, a Monte Carlo code system consisting of modified versions of the codes MCNPX and MCNP-PoliMi has been developed in conjunction with a post-processing algorithm to operate on the MCNP-PoliMi output file. The purpose of this subroutine is to assemble the interactions into groups corresponding to the number of interactions which would occur during a given pulse. The resulting multiplicity distributions appear more realistic and capture the higher-order multiplets which are a product of multiple reactions occurring during a single accelerator pulse. Plans are underway to gather relevant experimental data to verify and validate the methodology developed and presented here. This capability will enable the simulation of a large number of materials and detector geometries. Analysis of this information will determine the feasibility of using multiplicity distributions as an identification tool for special nuclear material.

Nonlinear Knowledge in Kernel-Based Multiple Criteria Programming Classifier

Science.gov (United States)

Zhang, Dongling; Tian, Yingjie; Shi, Yong

Kernel-based Multiple Criteria Linear Programming (KMCLP) model is used as classification methods, which can learn from training examples. Whereas, in traditional machine learning area, data sets are classified only by prior knowledge. Some works combine the above two classification principle to overcome the defaults of each approach. In this paper, we propose a model to incorporate the nonlinear knowledge into KMCLP in order to solve the problem when input consists of not only training example, but also nonlinear prior knowledge. In dealing with real world case breast cancer diagnosis, the model shows its better performance than the model solely based on training data.

Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

KAUST Repository

Li, Muxingzi

2017-01-01

of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous

Incorporation of human factors into ship collision risk models focusing on human centred design aspects

International Nuclear Information System (INIS)

Sotiralis, P.; Ventikos, N.P.; Hamann, R.; Golyshev, P.; Teixeira, A.P.

2016-01-01

This paper presents an approach that more adequately incorporates human factor considerations into quantitative risk analysis of ship operation. The focus is on the collision accident category, which is one of the main risk contributors in ship operation. The approach is based on the development of a Bayesian Network (BN) model that integrates elements from the Technique for Retrospective and Predictive Analysis of Cognitive Errors (TRACEr) and focuses on the calculation of the collision accident probability due to human error. The model takes into account the human performance in normal, abnormal and critical operational conditions and implements specific tasks derived from the analysis of the task errors leading to the collision accident category. A sensitivity analysis is performed to identify the most important contributors to human performance and ship collision. Finally, the model developed is applied to assess the collision risk of a feeder operating in Dover strait using the collision probability estimated by the developed BN model and an Event tree model for calculation of human, economic and environmental risks. - Highlights: • A collision risk model for the incorporation of human factors into quantitative risk analysis is proposed. • The model takes into account the human performance in different operational conditions leading to the collision. • The most important contributors to human performance and ship collision are identified. • The model developed is applied to assess the collision risk of a feeder operating in Dover strait.

MODEL PENSKORAN PARTIAL CREDIT PADA BUTIR MULTIPLE TRUE-FALSE BIDANG FISIKA

Directory of Open Access Journals (Sweden)

Wasis Wasis

2013-01-01

Full Text Available Tujuan penelitian ini menghasilkan model penskoran politomus untuk respons butir multiple true-false, sehingga dapat mengestimasi secara lebih akurat kemampuan di bidang fisika. Pengembangan penskoran menggunakan Four-D model dan diuji akurasinya melalui penelitian empiris dan simulasi. Penelitian empiris menggunakan 15 butir multiple true-false yang diambil dari soal UMPTN tahun 1996-2006 dan dikenakan pada 410 mahasiswa baru FMIPA Universitas Negeri Surabaya angkatan tahun 2007. Respons peserta tes diskor dengan tiga model partial credit (PCM I; II; dan III dan secara dikotomus. Hasil penskoran dianalisis dengan program Quest untuk mendapat-kan estimasi tingkat kesukaran butir (δ dan estimasi ke-mampuan peserta (θ untuk menentukan nilai fungsi informasi tes dan kesalahan baku estimasi. Penelitian simulasi mengguna-kan data bangkitan berdasarkan parameter empiris (δ dan θ memakai program statistik SAS dan akurasi estimasinya di-analisis dengan metode root mean squared error (RMSE. Hasil penelitian ini menunjukkan: (i Penskoran PCM dengan pem-bobotan mampu mengestimasi kemampuan lebih akurat di-bandingkan tanpa pembobotan maupun secara dikotomus; (ii Semakin banyak jumlah kategori dalam penskoran partial credit, semakin akurat. Kata kunci: model penskoran partial credit, butir multiple true-false ____________________________________________________________ THE PARTIAL CREDIT SCORING MODEL FOR THE MULTIPLE TRUE-FALSE BUTIRS IN PHYSICS Abstract This study is an attempt to overcome the weaknesses. This study aims to produce a polytomous scoring model for responses to multiple true-false butirs in order to get a more accurate estimation of abilities in physics. It adopts the Four-D model and its accuracy is assessed through empirical and simulation studies. The empirical study employed 15 multiple true-false butirs taken from the New Students Entrance Test of State University the year of 1996–2006. It administered to 410 new students enrolled

Incorporating genetic variation into a model of budburst phenology of coast Douglas-fir (Pseudotsuga menziesii var

Science.gov (United States)

Peter J. Gould; Constance A. Harrington; Bradley J. St Clair

2011-01-01

Models to predict budburst and other phenological events in plants are needed to forecast how climate change may impact ecosystems and for the development of mitigation strategies. Differences among genotypes are important to predicting phenological events in species that show strong clinal variation in adaptive traits. We present a model that incorporates the effects...

FORMULATION AND CHARACTERIZATION OF A MULTIPLE ...

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Vitamin C, was incorporated into the inner aqueous phase of water-in-oil-in-water ... Multiple emulsion was prepared by two step method. ... that there was no significant change (p > 0.05) in globule sizes in most of the samples ... advantages of prolonged release of active agent, incorporation of incompatible materials and.

A collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers.

Science.gov (United States)

Li, Guo; Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

Science.gov (United States)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Analysis of the residential location choice and household energy consumption behavior by incorporating multiple self-selection effects

International Nuclear Information System (INIS)

Yu Biying; Junyi Zhang; Fujiwara, Akimasa

2012-01-01

It is expected that the residential location choice and household energy consumption behavior might correlate with each other. Besides, due to the existence of self-selection effects, the observed inter-relationship between them might be the spurious result of the fact that some unobserved variables are causing both. These concerns motivate us to (1) consider residential location choice and household energy consumption behavior (for both in-home appliances and out-of-home cars) simultaneously and, (2) explicitly control self-selection effects so as to capture a relatively true effect of land-use policy on household energy consumption behavior. An integrated model termed as joint mixed Multinomial Logit-Multiple Discrete-Continuous Extreme Value model is presented here to identify the sensitivity of household energy consumption to land use policy by considering multiple self-selection effects. The model results indicate that land-use policy do play a great role in changing Beijing residents’ energy consumption pattern, while the self-selection effects cannot be ignored when evaluating the effect of land-use policy. Based on the policy scenario design, it is found that increasing recreational facilities and bus lines in the neighborhood can greatly promote household's energy-saving behavior. Additionally, the importance of “soft policy” and package policy is also emphasized in the context of Beijing. - Highlights: ► Representing residential choice and household energy consumption behavior jointly. ► Land use policy is found effective to control the household energy use in Beijing. ► Multiple self-selection effects are posed to get the true effect of land use policy. ► Significant self-selection effects call an attention to the soft policy in Beijing. ► The necessity of package policy on saving Beijing residents’ energy use is confirmed.

Reduction of bias in neutron multiplicity assay using a weighted point model

Energy Technology Data Exchange (ETDEWEB)

Geist, W. H. (William H.); Krick, M. S. (Merlyn S.); Mayo, D. R. (Douglas R.)

2004-01-01

Accurate assay of most common plutonium samples was the development goal for the nondestructive assay technique of neutron multiplicity counting. Over the past 20 years the technique has been proven for relatively pure oxides and small metal items. Unfortunately, the technique results in large biases when assaying large metal items. Limiting assumptions, such as unifoh multiplication, in the point model used to derive the multiplicity equations causes these biases for large dense items. A weighted point model has been developed to overcome some of the limitations in the standard point model. Weighting factors are detemiined from Monte Carlo calculations using the MCNPX code. Monte Carlo calculations give the dependence of the weighting factors on sample mass and geometry, and simulated assays using Monte Carlo give the theoretical accuracy of the weighted-point-model assay. Measured multiplicity data evaluated with both the standard and weighted point models are compared to reference values to give the experimental accuracy of the assay. Initial results show significant promise for the weighted point model in reducing or eliminating biases in the neutron multiplicity assay of metal items. The negative biases observed in the assay of plutonium metal samples are caused by variations in the neutron multiplication for neutrons originating in various locations in the sample. The bias depends on the mass and shape of the sample and depends on the amount and energy distribution of the ({alpha},n) neutrons in the sample. When the standard point model is used, this variable-multiplication bias overestimates the multiplication and alpha values of the sample, and underestimates the plutonium mass. The weighted point model potentially can provide assay accuracy of {approx}2% (1 {sigma}) for cylindrical plutonium metal samples < 4 kg with {alpha} < 1 without knowing the exact shape of the samples, provided that the ({alpha},n) source is uniformly distributed throughout the

Global dynamics of a PDE model for aedes aegypti mosquitoe incorporating female sexual preference

KAUST Repository

Parshad, Rana

2011-01-01

In this paper we study the long time dynamics of a reaction diffusion system, describing the spread of Aedes aegypti mosquitoes, which are the primary cause of dengue infection. The system incorporates a control attempt via the sterile insect technique. The model incorporates female mosquitoes sexual preference for wild males over sterile males. We show global existence of strong solution for the system. We then derive uniform estimates to prove the existence of a global attractor in L-2(Omega), for the system. The attractor is shown to be L-infinity(Omega) regular and posess state of extinction, if the injection of sterile males is large enough. We also provide upper bounds on the Hausdorff and fractal dimensions of the attractor.

Modelling and Simulation of a Manipulator with Stable Viscoelastic Grasping Incorporating Friction

Directory of Open Access Journals (Sweden)

A. Khurshid

2016-12-01

Full Text Available Design, dynamics and control of a humanoid robotic hand based on anthropological dimensions, with joint friction, is modelled, simulated and analysed in this paper by using computer aided design and multibody dynamic simulation. Combined joint friction model is incorporated in the joints. Experimental values of coefficient of friction of grease lubricated sliding contacts representative of manipulator joints are presented. Human fingers deform to the shape of the grasped object (enveloping grasp at the area of interaction. A mass-spring-damper model of the grasp is developed. The interaction of the viscoelastic gripper of the arm with objects is analysed by using Bond Graph modelling method. Simulations were conducted for several material parameters. These results of the simulation are then used to develop a prototype of the proposed gripper. Bond graph model is experimentally validated by using the prototype. The gripper is used to successfully transport soft and fragile objects. This paper provides information on optimisation of friction and its inclusion in both dynamic modelling and simulation to enhance mechanical efficiency.

Incorporating NDVI in a gravity model setting to describe spatio-temporal patterns of Lyme borreliosis incidence

Science.gov (United States)

Barrios, J. M.; Verstraeten, W. W.; Farifteh, J.; Maes, P.; Aerts, J. M.; Coppin, P.

2012-04-01

Lyme borreliosis (LB) is the most common tick-borne disease in Europe and incidence growth has been reported in several European countries during the last decade. LB is caused by the bacterium Borrelia burgdorferi and the main vector of this pathogen in Europe is the tick Ixodes ricinus. LB incidence and spatial spread is greatly dependent on environmental conditions impacting habitat, demography and trophic interactions of ticks and the wide range of organisms ticks parasite. The landscape configuration is also a major determinant of tick habitat conditions and -very important- of the fashion and intensity of human interaction with vegetated areas, i.e. human exposure to the pathogen. Hence, spatial notions as distance and adjacency between urban and vegetated environments are related to human exposure to tick bites and, thus, to risk. This work tested the adequacy of a gravity model setting to model the observed spatio-temporal pattern of LB as a function of location and size of urban and vegetated areas and the seasonal and annual change in the vegetation dynamics as expressed by MODIS NDVI. Opting for this approach implies an analogy with Newton's law of universal gravitation in which the attraction forces between two bodies are directly proportional to the bodies mass and inversely proportional to distance. Similar implementations have proven useful in fields like trade modeling, health care service planning, disease mapping among other. In our implementation, the size of human settlements and vegetated systems and the distance separating these landscape elements are considered the 'bodies'; and the 'attraction' between them is an indicator of exposure to pathogen. A novel element of this implementation is the incorporation of NDVI to account for the seasonal and annual variation in risk. The importance of incorporating this indicator of vegetation activity resides in the fact that alterations of LB incidence pattern observed the last decade have been ascribed

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

Science.gov (United States)

Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

2016-01-01

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

Infinite Multiple Membership Relational Modeling for Complex Networks

DEFF Research Database (Denmark)

Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...

Analysis of PWR control rod ejection accident with the coupled code system SKETCH-INS/TRACE by incorporating pin power reconstruction model

International Nuclear Information System (INIS)

Nakajima, T.; Sakai, T.

2010-01-01

The pin power reconstruction model was incorporated in the 3-D nodal kinetics code SKETCH-INS in order to produce accurate calculation of three-dimensional pin power distributions throughout the reactor core. In order to verify the employed pin power reconstruction model, the PWR MOX/UO_2 core transient benchmark problem was analyzed with the coupled code system SKETCH-INS/TRACE by incorporating the model and the influence of pin power reconstruction model was studied. SKETCH-INS pin power distributions for 3 benchmark problems were compared with the PARCS solutions which were provided by the host organisation of the benchmark. SKETCH-INS results were in good agreement with the PARCS results. The capability of employed pin power reconstruction model was confirmed through the analysis of benchmark problems. A PWR control rod ejection benchmark problem was analyzed with the coupled code system SKETCH-INS/ TRACE by incorporating the pin power reconstruction model. The influence of pin power reconstruction model was studied by comparing with the result of conventional node averaged flux model. The results indicate that the pin power reconstruction model has significant effect on the pin powers during transient and hence on the fuel enthalpy

Modeling a historical mountain pine beetle outbreak using Landsat MSS and multiple lines of evidence

Science.gov (United States)

Assal, Timothy J.; Sibold, Jason; Reich, Robin M.

2014-01-01

Mountain pine beetles are significant forest disturbance agents, capable of inducing widespread mortality in coniferous forests in western North America. Various remote sensing approaches have assessed the impacts of beetle outbreaks over the last two decades. However, few studies have addressed the impacts of historical mountain pine beetle outbreaks, including the 1970s event that impacted Glacier National Park. The lack of spatially explicit data on this disturbance represents both a major data gap and a critical research challenge in that wildfire has removed some of the evidence from the landscape. We utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We incorporate historical aerial and landscape photos, aerial detection survey data, a nine-year collection of satellite imagery and abiotic data. This study presents a remote sensing based framework to (1) relate measurements of canopy mortality from fine-scale aerial photography to coarse-scale multispectral imagery and (2) classify the severity of mountain pine beetle affected areas using a temporal sequence of Landsat data and other landscape variables. We sampled canopy mortality in 261 plots from aerial photos and found that insect effects on mortality were evident in changes to the Normalized Difference Vegetation Index (NDVI) over time. We tested multiple spectral indices and found that a combination of NDVI and the green band resulted in the strongest model. We report a two-step process where we utilize a generalized least squares model to account for the large-scale variability in the data and a binary regression tree to describe the small-scale variability. The final model had a root mean square error estimate of 9.8% canopy mortality, a mean absolute error of 7.6% and an R2 of 0.82. The results demonstrate that a model of percent canopy mortality as a continuous variable can be developed to identify a gradient of mountain pine beetle severity on the

Optimization of the Darrieus wind turbines with double-multiple-streamtube model

International Nuclear Information System (INIS)

Paraschivoiu, I.

1985-01-01

This paper discusses a new improvement of the double-multiple-stream tube model by considering the stream tube expansion effects on the Darrieus wind turbine. These effects, allowing a more realistic modeling of the upwind/downwind flow field asymmetries inherent in the Darrieus rotor, were calculated by using CARDAAX computer code. When the dynamic stall is introduced in the double-multiple-stream tube model, the aerodynamic loads and performance show significant changes in the range of low tip-speed ratio

Towards a functional model of mental disorders incorporating the laws of thermodynamics.

Science.gov (United States)

Murray, George C; McKenzie, Karen

2013-05-01

The current paper presents the hypothesis that the understanding of mental disorders can be advanced by incorporating the laws of thermodynamics, specifically relating to energy conservation and energy transfer. These ideas, along with the introduction of the notion that entropic activities are symptomatic of inefficient energy transfer or disorder, were used to propose a model of understanding mental ill health as resulting from the interaction of entropy, capacity and work (environmental demands). The model was applied to Attention Deficit Hyperactivity Disorder, and was shown to be compatible with current thinking about this condition, as well as emerging models of mental disorders as complex networks. A key implication of the proposed model is that it argues that all mental disorders require a systemic functional approach, with the advantage that it offers a number of routes into the assessment, formulation and treatment for mental health problems. Copyright © 2013 Elsevier Ltd. All rights reserved.

In vitro method determing sensitivity of anticancer agents by incorporation of radioactive precursors

International Nuclear Information System (INIS)

Sakakibara, Satoshi

1983-01-01

A new sensitivity test of anticancer agents was developed to measure the lethal effects of cancer cells by the incorporation of radioactive precursors. The thousand cancer cells were cultured in a microplate in the presence of anticancer agents. These cells were exposed to radioactive precursors. Two or three days later, the cancer cells were harvested on a glass fiver filter by a multiple automatic cell-harvester and the incorporation of precursors was counted by a liquid scintillation counter. In this study, the in vivo results of drug testing in animal model systems were compared with drug sensitivities. Mice inoculated Ehrlich ascites cells were treated with various kinds of anticancer drugs. The development of the cells was compatible with the result of the sensitivity test. The growths of Lauson and ME-180 cells derived from human cancers implanted subcutaneously to nude mice were also well correlated with this sensitivity test. (author)

A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

Directory of Open Access Journals (Sweden)

Guo Li

2014-01-01

Full Text Available This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

Science.gov (United States)

Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104

Multiple Time Series Ising Model for Financial Market Simulations

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2015-01-01

In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated

Incorporation of Markov reliability models for digital instrumentation and control systems into existing PRAs

International Nuclear Information System (INIS)

Bucci, P.; Mangan, L. A.; Kirschenbaum, J.; Mandelli, D.; Aldemir, T.; Arndt, S. A.

2006-01-01

Markov models have the ability to capture the statistical dependence between failure events that can arise in the presence of complex dynamic interactions between components of digital instrumentation and control systems. One obstacle to the use of such models in an existing probabilistic risk assessment (PRA) is that most of the currently available PRA software is based on the static event-tree/fault-tree methodology which often cannot represent such interactions. We present an approach to the integration of Markov reliability models into existing PRAs by describing the Markov model of a digital steam generator feedwater level control system, how dynamic event trees (DETs) can be generated from the model, and how the DETs can be incorporated into an existing PRA with the SAPHIRE software. (authors)

A generalized linear-quadratic model incorporating reciprocal time pattern of radiation damage repair

International Nuclear Information System (INIS)

Huang, Zhibin; Mayr, Nina A.; Lo, Simon S.; Wang, Jian Z.; Jia Guang; Yuh, William T. C.; Johnke, Roberta

2012-01-01

Purpose: It has been conventionally assumed that the repair rate for sublethal damage (SLD) remains constant during the entire radiation course. However, increasing evidence from animal studies suggest that this may not the case. Rather, it appears that the repair rate for radiation-induced SLD slows down with increasing time. Such a slowdown in repair would suggest that the exponential repair pattern would not necessarily accurately predict repair process. As a result, the purpose of this study was to investigate a new generalized linear-quadratic (LQ) model incorporating a repair pattern with reciprocal time. The new formulas were tested with published experimental data. Methods: The LQ model has been widely used in radiation therapy, and the parameter G in the surviving fraction represents the repair process of sublethal damage with T r as the repair half-time. When a reciprocal pattern of repair process was adopted, a closed form of G was derived analytically for arbitrary radiation schemes. The published animal data adopted to test the reciprocal formulas. Results: A generalized LQ model to describe the repair process in a reciprocal pattern was obtained. Subsequently, formulas for special cases were derived from this general form. The reciprocal model showed a better fit to the animal data than the exponential model, particularly for the ED50 data (reduced χ 2 min of 2.0 vs 4.3, p = 0.11 vs 0.006), with the following gLQ parameters: α/β = 2.6-4.8 Gy, T r = 3.2-3.9 h for rat feet skin, and α/β = 0.9 Gy, T r = 1.1 h for rat spinal cord. Conclusions: These results of repair process following a reciprocal time suggest that the generalized LQ model incorporating the reciprocal time of sublethal damage repair shows a better fit than the exponential repair model. These formulas can be used to analyze the experimental and clinical data, where a slowing-down repair process appears during the course of radiation therapy.

Model of charge-state distributions for electron cyclotron resonance ion source plasmas

Directory of Open Access Journals (Sweden)

D. H. Edgell

1999-12-01

Full Text Available A computer model for the ion charge-state distribution (CSD in an electron cyclotron resonance ion source (ECRIS plasma is presented that incorporates non-Maxwellian distribution functions, multiple atomic species, and ion confinement due to the ambipolar potential well that arises from confinement of the electron cyclotron resonance (ECR heated electrons. Atomic processes incorporated into the model include multiple ionization and multiple charge exchange with rate coefficients calculated for non-Maxwellian electron distributions. The electron distribution function is calculated using a Fokker-Planck code with an ECR heating term. This eliminates the electron temperature as an arbitrary user input. The model produces results that are a good match to CSD data from the ANL-ECRII ECRIS. Extending the model to 1D axial will also allow the model to determine the plasma and electrostatic potential profiles, further eliminating arbitrary user input to the model.

Alternative approaches to reliability modeling of a multiple engineered barrier system

International Nuclear Information System (INIS)

Ananda, M.M.A.; Singh, A.K.

1994-01-01

The lifetime of the engineered barrier system used for containment of high-level radioactive waste will significantly impact the total performance of a geological repository facility. Currently two types of designs are under consideration for an engineered barrier system, single engineered barrier system and multiple engineered barrier system. Multiple engineered barrier system consists of several metal barriers and the waste form (cladding). Some recent work show that a significant improvement of performance can be achieved by utilizing multiple engineered barrier systems. Considering sequential failures for each barrier, we model the reliability of the multiple engineered barrier system. Weibull and exponential lifetime distributions are used through out the analysis. Furthermore, the number of failed engineered barrier systems in a repository at a given time is modeled using a poisson approximation

Feedback structure based entropy approach for multiple-model estimation

Institute of Scientific and Technical Information of China (English)

Shen-tu Han; Xue Anke; Guo Yunfei

2013-01-01

The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.

A PDP model of the simultaneous perception of multiple objects

Science.gov (United States)

Henderson, Cynthia M.; McClelland, James L.

2011-06-01

Illusory conjunctions in normal and simultanagnosic subjects are two instances where the visual features of multiple objects are incorrectly 'bound' together. A connectionist model explores how multiple objects could be perceived correctly in normal subjects given sufficient time, but could give rise to illusory conjunctions with damage or time pressure. In this model, perception of two objects benefits from lateral connections between hidden layers modelling aspects of the ventral and dorsal visual pathways. As with simultanagnosia, simulations of dorsal lesions impair multi-object recognition. In contrast, a large ventral lesion has minimal effect on dorsal functioning, akin to dissociations between simple object manipulation (retained in visual form agnosia and semantic dementia) and object discrimination (impaired in these disorders) [Hodges, J.R., Bozeat, S., Lambon Ralph, M.A., Patterson, K., and Spatt, J. (2000), 'The Role of Conceptual Knowledge: Evidence from Semantic Dementia', Brain, 123, 1913-1925; Milner, A.D., and Goodale, M.A. (2006), The Visual Brain in Action (2nd ed.), New York: Oxford]. It is hoped that the functioning of this model might suggest potential processes underlying dorsal and ventral contributions to the correct perception of multiple objects.

Incorporating dominant environment into individual fitness promotes cooperation in the spatial prisoners' dilemma game

International Nuclear Information System (INIS)

Jin, Jiahua; Shen, Chen; Chu, Chen; Shi, Lei

2017-01-01

Highlights: • In spatial games, each player incorporates its environment into fitness only when its environment is greater than or equal to its payoff. • The mechanism of incorporating dominant environment promotes evolution of cooperation. • The robustness of such a mechanism to promote cooperation is verified for the snowdrift game and the various interaction networks. - Abstract: In spatial evolutionary games, the fitness of each player is usually measured by its inheritance (i.e. the accumulated payoffs by playing the game with its all nearest neighbors), or by the linear combination of its inheritance and its environment (i.e. the average of its all nearest neighbors’ inheritance). However, a rational individual incorporates environment into its fitness to develop itself only when environment is dominant in real life. Here, we redefine the individual fitness as a linear combination of inheritance and environment when environment performs better than inheritance. Multiple Monte Carlo simulation results show that incorporating dominant environment can improve cooperation comparing with the traditional case, and furthermore increasing the proportion of prevailing environment can enhance cooperative level better. These findings indicate that our mechanism enhances the individual ability to adapt environment, and makes the spatial reciprocity more efficient. Besides, we also verify its robustness against different game models and various topology structures.

SWAMP+: multiple subsequence alignment using associative massive parallelism

Energy Technology Data Exchange (ETDEWEB)

Steinfadt, Shannon Irene [Los Alamos National Laboratory; Baker, Johnnie W [KENT STATE UNIV.

2010-10-18

A new parallel algorithm SWAMP+ incorporates the Smith-Waterman sequence alignment on an associative parallel model known as ASC. It is a highly sensitive parallel approach that expands traditional pairwise sequence alignment. This is the first parallel algorithm to provide multiple non-overlapping, non-intersecting subsequence alignments with the accuracy of Smith-Waterman. The efficient algorithm provides multiple alignments similar to BLAST while creating a better workflow for the end users. The parallel portions of the code run in O(m+n) time using m processors. When m = n, the algorithmic analysis becomes O(n) with a coefficient of two, yielding a linear speedup. Implementation of the algorithm on the SIMD ClearSpeed CSX620 confirms this theoretical linear speedup with real timings.

MODEL PENSKORAN PARTIAL CREDIT PADA BUTIR MULTIPLE TRUE-FALSE BIDANG FISIKA

OpenAIRE

Wasis Wasis

2013-01-01

Tujuan penelitian ini menghasilkan model penskoran politomus untuk respons butir multiple true-false, sehingga dapat mengestimasi secara lebih akurat kemampuan di bidang fisika. Pengembangan penskoran menggunakan Four-D model dan diuji akurasinya melalui penelitian empiris dan simulasi. Penelitian empiris menggunakan 15 butir multiple true-false yang diambil dari soal UMPTN tahun 1996-2006 dan dikenakan pada 410 mahasiswa baru FMIPA Universitas Negeri Surabaya angkatan tahun 2007. Respons pes...

NoSQL data model for semi-automatic integration of ethnomedicinal plant data from multiple sources.

Science.gov (United States)

Ningthoujam, Sanjoy Singh; Choudhury, Manabendra Dutta; Potsangbam, Kumar Singh; Chetia, Pankaj; Nahar, Lutfun; Sarker, Satyajit D; Basar, Norazah; Das Talukdar, Anupam

2014-01-01

Sharing traditional knowledge with the scientific community could refine scientific approaches to phytochemical investigation and conservation of ethnomedicinal plants. As such, integration of traditional knowledge with scientific data using a single platform for sharing is greatly needed. However, ethnomedicinal data are available in heterogeneous formats, which depend on cultural aspects, survey methodology and focus of the study. Phytochemical and bioassay data are also available from many open sources in various standards and customised formats. To design a flexible data model that could integrate both primary and curated ethnomedicinal plant data from multiple sources. The current model is based on MongoDB, one of the Not only Structured Query Language (NoSQL) databases. Although it does not contain schema, modifications were made so that the model could incorporate both standard and customised ethnomedicinal plant data format from different sources. The model presented can integrate both primary and secondary data related to ethnomedicinal plants. Accommodation of disparate data was accomplished by a feature of this database that supported a different set of fields for each document. It also allowed storage of similar data having different properties. The model presented is scalable to a highly complex level with continuing maturation of the database, and is applicable for storing, retrieving and sharing ethnomedicinal plant data. It can also serve as a flexible alternative to a relational and normalised database. Copyright © 2014 John Wiley & Sons, Ltd.

Hybrid approaches for multiple-species stochastic reaction–diffusion models

International Nuclear Information System (INIS)

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

2015-01-01

Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries

Hybrid approaches for multiple-species stochastic reaction–diffusion models

Energy Technology Data Exchange (ETDEWEB)

Spill, Fabian, E-mail: fspill@bu.edu [Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215 (United States); Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States); Guerrero, Pilar [Department of Mathematics, University College London, Gower Street, London WC1E 6BT (United Kingdom); Alarcon, Tomas [Centre de Recerca Matematica, Campus de Bellaterra, Edifici C, 08193 Bellaterra (Barcelona) (Spain); Departament de Matemàtiques, Universitat Atonòma de Barcelona, 08193 Bellaterra (Barcelona) (Spain); Maini, Philip K. [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Byrne, Helen [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Computational Biology Group, Department of Computer Science, University of Oxford, Oxford OX1 3QD (United Kingdom)

2015-10-15

Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.

Modeling a Single SEP Event from Multiple Vantage Points Using the iPATH Model

Science.gov (United States)

Hu, Junxiang; Li, Gang; Fu, Shuai; Zank, Gary; Ao, Xianzhi

2018-02-01

Using the recently extended 2D improved Particle Acceleration and Transport in the Heliosphere (iPATH) model, we model an example gradual solar energetic particle event as observed at multiple locations. Protons and ions that are energized via the diffusive shock acceleration mechanism are followed at a 2D coronal mass ejection-driven shock where the shock geometry varies across the shock front. The subsequent transport of energetic particles, including cross-field diffusion, is modeled by a Monte Carlo code that is based on a stochastic differential equation method. Time intensity profiles and particle spectra at multiple locations and different radial distances, separated in longitudes, are presented. The results shown here are relevant to the upcoming Parker Solar Probe mission.

A modified Wright-Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity.

Science.gov (United States)

Zhao, Lei; Gossmann, Toni I; Waxman, David

2016-03-21

The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have

Incorporating Multiple Energy Relay Dyes in Liquid Dye-Sensitized Solar Cells

KAUST Repository

Yum, Jun-Ho; Hardin, Brian E.; Hoke, Eric T.; Baranoff, Etienne; Zakeeruddin, Shaik M.; Nazeeruddin, Mohammad K.; Torres, Tomas; McGehee, Michael D.; Grä tzel, Michael

2011-01-01

Panchromatic response is essential to increase the light-harvesting efficiency in solar conversion systems. Herein we show increased light harvesting from using multiple energy relay dyes inside dye-sensitized solar cells. Additional photoresponse

Dealing with Multiple Solutions in Structural Vector Autoregressive Models.

Science.gov (United States)

Beltz, Adriene M; Molenaar, Peter C M

2016-01-01

Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.

A model to incorporate organ deformation in the evaluation of dose/volume relationship

International Nuclear Information System (INIS)

Yan, D.; Jaffray, D.; Wong, J.; Brabbins, D.; Martinez, A. A.

1997-01-01

Purpose: Measurements of internal organ motion have demonstrated that daily organ deformation exists during the course of radiation treatment. However, a model to evaluate the resultant dose delivered to a daily deformed organ remains a difficult challenge. Current methods which model such organ deformation as rigid body motion in the dose calculation for treatment planning evaluation are incorrect and misleading. In this study, a new model for treatment planning evaluation is introduced which incorporates patient specific information of daily organ deformation and setup variation. The model was also used to retrospectively analyze the actual treatment data measured using daily CT scans for 5 patients with prostate treatment. Methods and Materials: The model assumes that for each patient, the organ of interest can be measured during the first few treatment days. First, the volume of each organ is delineated from each of the daily measurements and cumulated in a 3D bit-map. A tissue occupancy distribution is then constructed with the 50% isodensity representing the mean, or effective, organ volume. During the course of treatment, each voxel in the effective organ volume is assumed to move inside a local 3D neighborhood with a specific distribution function. The neighborhood and the distribution function are deduced from the positions and shapes of the organ in the first few measurements using the biomechanics model of viscoelastic body. For each voxel, the local distribution function is then convolved with the spatial dose distribution. The latter includes also the variation in dose due to daily setup error. As a result, the cumulative dose to the voxel incorporates the effects of daily setup variation and organ deformation. A ''variation adjusted'' dose volume histogram, aDVH, for the effective organ volume can then be constructed for the purpose of treatment evaluation and optimization. Up to 20 daily CT scans and daily portal images for 5 patients with prostate

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

Science.gov (United States)

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

Science.gov (United States)

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

Green communication: The enabler to multiple business models

DEFF Research Database (Denmark)

Lindgren, Peter; Clemmensen, Suberia; Taran, Yariv

2010-01-01

Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...... possibility to enable lower energy consumption. This paper shows how green communication enables innovation of green business models and multiple business models running simultaneously in different markets to different customers.......Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...

A toolkit for incorporating genetics into mainstream medical services: Learning from service development pilots in England.

Science.gov (United States)

Bennett, Catherine L; Burke, Sarah E; Burton, Hilary; Farndon, Peter A

2010-05-14

As advances in genetics are becoming increasingly relevant to mainstream healthcare, a major challenge is to ensure that these are integrated appropriately into mainstream medical services. In 2003, the Department of Health for England announced the availability of start-up funding for ten 'Mainstreaming Genetics' pilot services to develop models to achieve this. Multiple methods were used to explore the pilots' experiences of incorporating genetics which might inform the development of new services in the future. A workshop with project staff, an email questionnaire, interviews and a thematic analysis of pilot final reports were carried out. Seven themes relating to the integration of genetics into mainstream medical services were identified: planning services to incorporate genetics; the involvement of genetics departments; the establishment of roles incorporating genetic activities; identifying and involving stakeholders; the challenges of working across specialty boundaries; working with multiple healthcare organisations; and the importance of cultural awareness of genetic conditions. Pilots found that the planning phase often included the need to raise awareness of genetic conditions and services and that early consideration of organisational issues such as clinic location was essential. The formal involvement of genetics departments was crucial to success; benefits included provision of clinical and educational support for staff in new roles. Recruitment and retention for new roles outside usual career pathways sometimes proved difficult. Differences in specialties' working practices and working with multiple healthcare organisations also brought challenges such as the 'genetic approach' of working with families, incompatible record systems and different approaches to health professionals' autonomous practice. 'Practice points' have been collated into a Toolkit which includes resources from the pilots, including job descriptions and clinical tools. These can

Using a cognitive architecture in educational and recreational games : How to incorporate a model in your App

NARCIS (Netherlands)

Taatgen, Niels A.; de Weerd, Harmen; Reitter, David; Ritter, Frank

2016-01-01

We present a Swift re-implementation of the ACT-R cognitive architecture, which can be used to quickly build iOS Apps that incorporate an ACT-R model as a core feature. We discuss how this implementation can be used in an example model, and explore the breadth of possibilities by presenting six Apps

Incorporation of uridine-H3 into healthy and tobacco necrosis virus-infected mesophyll cells of Chenopodium amaranticolor

International Nuclear Information System (INIS)

Faccioli, G.; Rubies-Autonel, C.

1975-01-01

Tritiated uridine was selectively incorporated into the nucleus, nucleolus and cytoplasm of actinomycin D-treated Chenopodium amaranticolor cells locally infected with a strain of tobacco necrosis virus (TNV), 3 days after inoculation. Healthy cells did not show such an incorporation. Chloroplasts, in both types of cells, were free of label. Treatment with pancreatic ribonuclease removed the label completely in the majority of nuclei and nucleoli of infected cells. Since infectivity tests showed that AMD treatment increased virus multiplication by 10-12%, it is conceivable to think that the incorporation observed was due to virus synthesis. Preliminary infectivity experiments also showed that treatment of the cells with cycloheximide inhibited virus multiplication up to 80%, while chloramphenicol increased such multiplication. Our results lead to the conclusion that nucleus, nucleolus and cytoplasm but not chloroplasts are the sites involved in the synthesis of TNV. (orig.) [de

Modeling Freedom From Progression for Standard-Risk Medulloblastoma: A Mathematical Tumor Control Model With Multiple Modes of Failure

International Nuclear Information System (INIS)

Brodin, N. Patrik; Vogelius, Ivan R.; Björk-Eriksson, Thomas; Munck af Rosenschöld, Per; Bentzen, Søren M.

2013-01-01

Purpose: As pediatric medulloblastoma (MB) is a relatively rare disease, it is important to extract the maximum information from trials and cohort studies. Here, a framework was developed for modeling tumor control with multiple modes of failure and time-to-progression for standard-risk MB, using published pattern of failure data. Methods and Materials: Outcome data for standard-risk MB published after 1990 with pattern of relapse information were used to fit a tumor control dose-response model addressing failures in both the high-dose boost volume and the elective craniospinal volume. Estimates of 5-year event-free survival from 2 large randomized MB trials were used to model the time-to-progression distribution. Uncertainty in freedom from progression (FFP) was estimated by Monte Carlo sampling over the statistical uncertainty in input data. Results: The estimated 5-year FFP (95% confidence intervals [CI]) for craniospinal doses of 15, 18, 24, and 36 Gy while maintaining 54 Gy to the posterior fossa was 77% (95% CI, 70%-81%), 78% (95% CI, 73%-81%), 79% (95% CI, 76%-82%), and 80% (95% CI, 77%-84%) respectively. The uncertainty in FFP was considerably larger for craniospinal doses below 18 Gy, reflecting the lack of data in the lower dose range. Conclusions: Estimates of tumor control and time-to-progression for standard-risk MB provides a data-driven setting for hypothesis generation or power calculations for prospective trials, taking the uncertainties into account. The presented methods can also be applied to incorporate further risk-stratification for example based on molecular biomarkers, when the necessary data become available

Developing Baltic cod recruitment models II : Incorporation of environmental variability and species interaction

DEFF Research Database (Denmark)

Köster, Fritz; Hinrichsen, H.H.; St. John, Michael

2001-01-01

We investigate whether a process-oriented approach based on the results of field, laboratory, and modelling studies can be used to develop a stock-environment-recruitment model for Central Baltic cod (Gadus morhua). Based on exploratory statistical analysis, significant variables influencing...... affecting survival of eggs, predation by clupeids on eggs, larval transport, and cannibalism. Results showed that recruitment in the most important spawning area, the Bornholm Basin, during 1976-1995 was related to egg production; however, other factors affecting survival of the eggs (oxygen conditions......, predation) were also significant and when incorporated explained 69% of the variation in 0-group recruitment. In other spawning areas, variable hydrographic conditions did not allow for regular successful egg development. Hence, relatively simple models proved sufficient to predict recruitment of 0-group...

Multiplicity distribution and forward-backward correlations in the hydrodynamic theory of multiple production

International Nuclear Information System (INIS)

Tarasov, Yu.A.

1992-01-01

A hydrodynamic model for the collisions of gluon clusters is used to calculate the charge-particle multiplicity distributions in collisions of nucleons at ISR and collider energies. The separation temperature of the hydrodynamic system is calculated as a function of the rapidity [T k (γ 1 )] for each value of the inelasticity coefficient K. In the central region, this temperature is higher at collider energies than at the ISR energy. The average number of resonance clusters which decay into various (fixed) numbers of charged hadrons is found for each value of K. The number of these clusters fluctuates in accordance with a Poisson distribution. A hadron multiplicity distribution which incorporates these fluctuations is found. This distribution is averaged over the inelasticity coefficient. The distributions p(n ch ) and the KNO functions Ψ(z) are calculated for the overall and central regions of the rapidity, |y| ≤ 1.5. The broadening of the distributions and the violation of KNO scaling at collider energies results from increased contributions from the decays of resonances. The front-back multiplicity correlations are also studied; the decay of resonances is taken into account. The distributions and slope coefficients of the correlation function which are found for the various energies agree with experimental data

A model for arsenic anti-site incorporation in GaAs grown by hydride vapor phase epitaxy

Energy Technology Data Exchange (ETDEWEB)

Schulte, K. L.; Kuech, T. F. [Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States)

2014-12-28

GaAs growth by hydride vapor phase epitaxy (HVPE) has regained interest as a potential route to low cost, high efficiency thin film photovoltaics. In order to attain the highest efficiencies, deep level defect incorporation in these materials must be understood and controlled. The arsenic anti-site defect, As{sub Ga} or EL2, is the predominant deep level defect in HVPE-grown GaAs. In the present study, the relationships between HVPE growth conditions and incorporation of EL2 in GaAs epilayers were determined. Epitaxial n-GaAs layers were grown under a wide range of deposition temperatures (T{sub D}) and gallium chloride partial pressures (P{sub GaCl}), and the EL2 concentration, [EL2], was determined by deep level transient spectroscopy. [EL2] agreed with equilibrium thermodynamic predictions in layers grown under conditions in which the growth rate, R{sub G}, was controlled by conditions near thermodynamic equilibrium. [EL2] fell below equilibrium levels when R{sub G} was controlled by surface kinetic processes, with the disparity increasing as R{sub G} decreased. The surface chemical composition during growth was determined to have a strong influence on EL2 incorporation. Under thermodynamically limited growth conditions, e.g., high T{sub D} and/or low P{sub GaCl}, the surface vacancy concentration was high and the bulk crystal was close to equilibrium with the vapor phase. Under kinetically limited growth conditions, e.g., low T{sub D} and/or high P{sub GaCl}, the surface attained a high GaCl coverage, blocking As adsorption. This competitive adsorption process reduced the growth rate and also limited the amount of arsenic that incorporated as As{sub Ga}. A defect incorporation model which accounted for the surface concentration of arsenic as a function of the growth conditions, was developed. This model was used to identify optimal growth parameters for the growth of thin films for photovoltaics, conditions in which a high growth rate and low [EL2] could be

An extension of the multiple-trapping model

International Nuclear Information System (INIS)

Shkilev, V. P.

2012-01-01

The hopping charge transport in disordered semiconductors is considered. Using the concept of the transport energy level, macroscopic equations are derived that extend a multiple-trapping model to the case of semiconductors with both energy and spatial disorders. It is shown that, although both types of disorder can cause dispersive transport, the frequency dependence of conductivity is determined exclusively by the spatial disorder.

Incorporating Yearly Derived Winter Wheat Maps Into Winter Wheat Yield Forecasting Model

Science.gov (United States)

Skakun, S.; Franch, B.; Roger, J.-C.; Vermote, E.; Becker-Reshef, I.; Justice, C.; Santamaría-Artigas, A.

2016-01-01

Wheat is one of the most important cereal crops in the world. Timely and accurate forecast of wheat yield and production at global scale is vital in implementing food security policy. Becker-Reshef et al. (2010) developed a generalized empirical model for forecasting winter wheat production using remote sensing data and official statistics. This model was implemented using static wheat maps. In this paper, we analyze the impact of incorporating yearly wheat masks into the forecasting model. We propose a new approach of producing in season winter wheat maps exploiting satellite data and official statistics on crop area only. Validation on independent data showed that the proposed approach reached 6% to 23% of omission error and 10% to 16% of commission error when mapping winter wheat 2-3 months before harvest. In general, we found a limited impact of using yearly winter wheat masks over a static mask for the study regions.

A Multiple Model Prediction Algorithm for CNC Machine Wear PHM

Directory of Open Access Journals (Sweden)

Huimin Chen

2011-01-01

Full Text Available The 2010 PHM data challenge focuses on the remaining useful life (RUL estimation for cutters of a high speed CNC milling machine using measurements from dynamometer, accelerometer, and acoustic emission sensors. We present a multiple model approach for wear depth estimation of milling machine cutters using the provided data. The feature selection, initial wear estimation and multiple model fusion components of the proposed algorithm are explained in details and compared with several alternative methods using the training data. The final submission ranked #2 among professional and student participants and the method is applicable to other data driven PHM problems.

Filtering Meteoroid Flights Using Multiple Unscented Kalman Filters

Science.gov (United States)

Sansom, E. K.; Bland, P. A.; Rutten, M. G.; Paxman, J.; Towner, M. C.

2016-11-01

Estimator algorithms are immensely versatile and powerful tools that can be applied to any problem where a dynamic system can be modeled by a set of equations and where observations are available. A well designed estimator enables system states to be optimally predicted and errors to be rigorously quantified. Unscented Kalman filters (UKFs) and interactive multiple models can be found in methods from satellite tracking to self-driving cars. The luminous trajectory of the Bunburra Rockhole fireball was observed by the Desert Fireball Network in mid-2007. The recorded data set is used in this paper to examine the application of these two techniques as a viable approach to characterizing fireball dynamics. The nonlinear, single-body system of equations, used to model meteoroid entry through the atmosphere, is challenged by gross fragmentation events that may occur. The incorporation of the UKF within an interactive multiple model smoother provides a likely solution for when fragmentation events may occur as well as providing a statistical analysis of the state uncertainties. In addition to these benefits, another advantage of this approach is its automatability for use within an image processing pipeline to facilitate large fireball data analyses and meteorite recoveries.

Upscaling permeability for three-dimensional fractured porous rocks with the multiple boundary method

Science.gov (United States)

Chen, Tao; Clauser, Christoph; Marquart, Gabriele; Willbrand, Karen; Hiller, Thomas

2018-02-01

Upscaling permeability of grid blocks is crucial for groundwater models. A novel upscaling method for three-dimensional fractured porous rocks is presented. The objective of the study was to compare this method with the commonly used Oda upscaling method and the volume averaging method. First, the multiple boundary method and its computational framework were defined for three-dimensional stochastic fracture networks. Then, the different upscaling methods were compared for a set of rotated fractures, for tortuous fractures, and for two discrete fracture networks. The results computed by the multiple boundary method are comparable with those of the other two methods and fit best the analytical solution for a set of rotated fractures. The errors in flow rate of the equivalent fracture model decrease when using the multiple boundary method. Furthermore, the errors of the equivalent fracture models increase from well-connected fracture networks to poorly connected ones. Finally, the diagonal components of the equivalent permeability tensors tend to follow a normal or log-normal distribution for the well-connected fracture network model with infinite fracture size. By contrast, they exhibit a power-law distribution for the poorly connected fracture network with multiple scale fractures. The study demonstrates the accuracy and the flexibility of the multiple boundary upscaling concept. This makes it attractive for being incorporated into any existing flow-based upscaling procedures, which helps in reducing the uncertainty of groundwater models.

Selecting Tools to Model Integer and Binomial Multiplication

Science.gov (United States)

Pratt, Sarah Smitherman; Eddy, Colleen M.

2017-01-01

Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

Comparative study between a QCD inspired model and a multiple diffraction model

International Nuclear Information System (INIS)

Luna, E.G.S.; Martini, A.F.; Menon, M.J.

2003-01-01

A comparative study between a QCD Inspired Model (QCDIM) and a Multiple Diffraction Model (MDM) is presented, with focus on the results for pp differential cross section at √s = 52.8 GeV. It is shown that the MDM predictions are in agreement with experimental data, except for the dip region and that the QCDIM describes only the diffraction peak region. Interpretations in terms of the corresponding eikonals are also discussed. (author)

Digital terrain model generalization incorporating scale, semantic and cognitive constraints

Science.gov (United States)

Partsinevelos, Panagiotis; Papadogiorgaki, Maria

2014-05-01

Cartographic generalization is a well-known process accommodating spatial data compression, visualization and comprehension under various scales. In the last few years, there are several international attempts to construct tangible GIS systems, forming real 3D surfaces using a vast number of mechanical parts along a matrix formation (i.e., bars, pistons, vacuums). Usually, moving bars upon a structured grid push a stretching membrane resulting in a smooth visualization for a given surface. Most of these attempts suffer either in their cost, accuracy, resolution and/or speed. Under this perspective, the present study proposes a surface generalization process that incorporates intrinsic constrains of tangible GIS systems including robotic-motor movement and surface stretching limitations. The main objective is to provide optimized visualizations of 3D digital terrain models with minimum loss of information. That is, to minimize the number of pixels in a raster dataset used to define a DTM, while reserving the surface information. This neighborhood type of pixel relations adheres to the basics of Self Organizing Map (SOM) artificial neural networks, which are often used for information abstraction since they are indicative of intrinsic statistical features contained in the input patterns and provide concise and characteristic representations. Nevertheless, SOM remains more like a black box procedure not capable to cope with possible particularities and semantics of the application at hand. E.g. for coastal monitoring applications, the near - coast areas, surrounding mountains and lakes are more important than other features and generalization should be "biased"-stratified to fulfill this requirement. Moreover, according to the application objectives, we extend the SOM algorithm to incorporate special types of information generalization by differentiating the underlying strategy based on topologic information of the objects included in the application. The final

Gold Incorporated Mesoporous Silica Thin Film Model Surface as a Robust SERS and Catalytically Active Substrate

Directory of Open Access Journals (Sweden)

Anandakumari Chandrasekharan Sunil Sekhar

2016-05-01

Full Text Available Ultra-small gold nanoparticles incorporated in mesoporous silica thin films with accessible pore channels perpendicular to the substrate are prepared by a modified sol-gel method. The simple and easy spin coating technique is applied here to make homogeneous thin films. The surface characterization using FESEM shows crack-free films with a perpendicular pore arrangement. The applicability of these thin films as catalysts as well as a robust SERS active substrate for model catalysis study is tested. Compared to bare silica film our gold incorporated silica, GSM-23F gave an enhancement factor of 103 for RhB with a laser source 633 nm. The reduction reaction of p-nitrophenol with sodium borohydride from our thin films shows a decrease in peak intensity corresponding to –NO2 group as time proceeds, confirming the catalytic activity. Such model surfaces can potentially bridge the material gap between a real catalytic system and surface science studies.

Hydrostratigraphic modelling using multiple-point statistics and airborne transient electromagnetic methods

DEFF Research Database (Denmark)

Barfod, Adrian; Straubhaar, Julien; Høyer, Anne-Sophie

2017-01-01

the incorporation of elaborate datasets and provides a framework for stochastic hydrostratigraphic modelling. This paper focuses on comparing three MPS methods: snesim, DS and iqsim. The MPS methods are tested and compared on a real-world hydrogeophysical survey from Kasted in Denmark, which covers an area of 45 km......2. The comparison of the stochastic hydrostratigraphic MPS models is carried out in an elaborate scheme of visual inspection, mathematical similarity and consistency with boreholes. Using the Kasted survey data, a practical example for modelling new survey areas is presented. A cognitive...

Incorporating excitation-induced dephasing into the Maxwell-Bloch numerical modeling of photon echoes

International Nuclear Information System (INIS)

Burr, G.W.; Harris, Todd L.; Babbitt, Wm. Randall; Jefferson, C. Michael

2004-01-01

We describe the incorporation of excitation-induced dephasing (EID) into the Maxwell-Bloch numerical simulation of photon echoes. At each time step of the usual numerical integration, stochastic frequency jumps of ions--caused by excitation of neighboring ions--is modeled by convolving each Bloch vector with the Bloch vectors of nearby frequency detunings. The width of this convolution kernel follows the instantaneous change in overall population, integrated over the simulated bandwidth. This approach is validated by extensive comparison against published and original experimental results. The enhanced numerical model is then used to investigate the accuracy of experiments designed to extrapolate to the intrinsic dephasing time T 2 from data taken in the presence of EID. Such a modeling capability offers improved understanding of experimental results, and should allow quantitative analysis of engineering tradeoffs in realistic optical coherent transient applications

Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation

Directory of Open Access Journals (Sweden)

Min Yan

2016-07-01

Full Text Available This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17 model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST sensitivity analysis. Then the optimized MOD_17 model was used to calibrate the Biome-BGC model by adjusting the sensitive ecophysiological parameters. Once the best match was found for the 10 selected forest plots for the 8-day GPP estimates from the optimized MOD_17 and from the Biome-BGC, the values of sensitive ecophysiological parameters were determined. The calibrated Biome-BGC model agreed better with the eddy covariance (EC measurements (R2 = 0.87, RMSE = 1.583 gC·m−2·d−1 than the original model did (R2 = 0.72, RMSE = 2.419 gC·m−2·d−1. To provide a best estimate of the true state of the model, the Ensemble Kalman Filter (EnKF was used to assimilate five years (of eight-day periods between 2003 and 2007 of Global LAnd Surface Satellite (GLASS LAI products into the calibrated Biome-BGC model. The results indicated that LAI simulated through the assimilated Biome-BGC agreed well with GLASS LAI. GPP performances obtained from the assimilated Biome-BGC were further improved and verified by EC measurements at the Changbai Mountains forest flux site (R2 = 0.92, RMSE = 1.261 gC·m−2·d−1.

MULTIPLE SCALES FOR SUSTAINABLE RESULTS

Science.gov (United States)

This session will highlight recent research that incorporates the use of multiple scales and innovative environmental accounting to better inform decisions that affect sustainability, resilience, and vulnerability at all scales. Effective decision-making involves assessment at mu...

Incorporating an extended dendritic growth model into the CAFE model for rapidly solidified non-dilute alloys

International Nuclear Information System (INIS)

Ma, Jie; Wang, Bo; Zhao, Shunli; Wu, Guangxin; Zhang, Jieyu; Yang, Zhiliang

2016-01-01

We have extended the dendritic growth model first proposed by Boettinger, Coriell and Trivedi (here termed EBCT) for microstructure simulations of rapidly solidified non-dilute alloys. The temperature-dependent distribution coefficient, obtained from calculations of phase equilibria, and the continuous growth model (CGM) were adopted in the present EBCT model to describe the solute trapping behaviors. The temperature dependence of the physical properties, which were not used in previous dendritic growth models, were also considered in the present EBCT model. These extensions allow the present EBCT model to be used for microstructure simulations of non-dilute alloys. The comparison of the present EBCT model with the BCT model proves that the considerations of the distribution coefficient and physical properties are necessary for microstructure simulations, especially for small particles with high undercoolings. Finally, the EBCT model was incorporated into the cellular automaton-finite element (CAFE) model to simulate microstructures of gas-atomized ASP30 high speed steel particles that were then compared with experimental results. Both the simulated and experimental results reveal that a columnar dendritic microstructure preferentially forms in small particles and an equiaxed microstructure forms otherwise. The applications of the present EBCT model provide a convenient way to predict the microstructure of non-dilute alloys. - Highlights: • A dendritic growth model was developed considering non-equilibrium distribution coefficient. • The physical properties with temperature dependence were considered in the extended model. • The extended model can be used to non-dilute alloys and the extensions are necessary in small particles. • Microstructure of ASP30 steel was investigated using the present model and verified by experiment.

Incorporating an extended dendritic growth model into the CAFE model for rapidly solidified non-dilute alloys

Energy Technology Data Exchange (ETDEWEB)

Ma, Jie; Wang, Bo [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Zhao, Shunli [Research Institute, Baoshan Iron & Steel Co., Ltd, Shanghai 201900 (China); Wu, Guangxin [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Zhang, Jieyu, E-mail: zjy6162@staff.shu.edu.cn [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Yang, Zhiliang [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China)

2016-05-25

We have extended the dendritic growth model first proposed by Boettinger, Coriell and Trivedi (here termed EBCT) for microstructure simulations of rapidly solidified non-dilute alloys. The temperature-dependent distribution coefficient, obtained from calculations of phase equilibria, and the continuous growth model (CGM) were adopted in the present EBCT model to describe the solute trapping behaviors. The temperature dependence of the physical properties, which were not used in previous dendritic growth models, were also considered in the present EBCT model. These extensions allow the present EBCT model to be used for microstructure simulations of non-dilute alloys. The comparison of the present EBCT model with the BCT model proves that the considerations of the distribution coefficient and physical properties are necessary for microstructure simulations, especially for small particles with high undercoolings. Finally, the EBCT model was incorporated into the cellular automaton-finite element (CAFE) model to simulate microstructures of gas-atomized ASP30 high speed steel particles that were then compared with experimental results. Both the simulated and experimental results reveal that a columnar dendritic microstructure preferentially forms in small particles and an equiaxed microstructure forms otherwise. The applications of the present EBCT model provide a convenient way to predict the microstructure of non-dilute alloys. - Highlights: • A dendritic growth model was developed considering non-equilibrium distribution coefficient. • The physical properties with temperature dependence were considered in the extended model. • The extended model can be used to non-dilute alloys and the extensions are necessary in small particles. • Microstructure of ASP30 steel was investigated using the present model and verified by experiment.

Incorporation of oxygen contribution by plant roots into classical dissolved oxygen deficit model for a subsurface flow treatment wetland.

Science.gov (United States)

Bezbaruah, Achintya N; Zhang, Tian C

2009-01-01

It has been long established that plants play major roles in a treatment wetland. However, the role of plants has not been incorporated into wetland models. This study tries to incorporate wetland plants into a biochemical oxygen demand (BOD) model so that the relative contributions of the aerobic and anaerobic processes to meeting BOD can be quantitatively determined. The classical dissolved oxygen (DO) deficit model has been modified to simulate the DO curve for a field subsurface flow constructed wetland (SFCW) treating municipal wastewater. Sensitivities of model parameters have been analyzed. Based on the model it is predicted that in the SFCW under study about 64% BOD are degraded through aerobic routes and 36% is degraded anaerobically. While not exhaustive, this preliminary work should serve as a pointer for further research in wetland model development and to determine the values of some of the parameters used in the modified DO deficit and associated BOD model. It should be noted that nitrogen cycle and effects of temperature have not been addressed in these models for simplicity of model formulation. This paper should be read with this caveat in mind.

Towards Integration of CAx Systems and a Multiple-View Product Modeller in Mechanical Design

Directory of Open Access Journals (Sweden)

H. Song

2005-01-01

Full Text Available This paper deals with the development of an integration framework and its implementation for the connexion of CAx systems and multiple-view product modelling. The integration framework is presented regarding its conceptual level and the implementation level is described currently with the connexion of a functional modeller, a multiple-view product modeller, an optimisation module and a CAD system. The integration between the multiple-view product modeller and CATIA V5 based on the STEP standard is described in detail. Finally, the presented works are discussed and future research developments are suggested. 

Electronic transport in single-helical protein molecules: Effects of multiple charge conduction pathways and helical symmetry

Energy Technology Data Exchange (ETDEWEB)

Kundu, Sourav, E-mail: sourav.kunduphy@gmail.com; Karmakar, S.N.

2016-07-15

We propose a tight-binding model to investigate electronic transport properties of single helical protein molecules incorporating both the helical symmetry and the possibility of multiple charge transfer pathways. Our study reveals that due to existence of both the multiple charge transfer pathways and helical symmetry, the transport properties are quite rigid under influence of environmental fluctuations which indicates that these biomolecules can serve as better alternatives in nanoelectronic devices than its other biological counterparts e.g., single-stranded DNA.

Longitudinal comparative evaluation of the equivalence of an integrated peer-support and clinical staffing model for residential mental health rehabilitation: a mixed methods protocol incorporating multiple stakeholder perspectives.

Science.gov (United States)

Parker, Stephen; Dark, Frances; Newman, Ellie; Korman, Nicole; Meurk, Carla; Siskind, Dan; Harris, Meredith

2016-06-02

A novel staffing model integrating peer support workers and clinical staff within a unified team is being trialled at community based residential rehabilitation units in Australia. A mixed-methods protocol for the longitudinal evaluation of the outcomes, expectations and experiences of care by consumers and staff under this staffing model in two units will be compared to one unit operating a traditional clinical staffing. The study is unique with regards to the context, the longitudinal approach and consideration of multiple stakeholder perspectives. The longitudinal mixed methods design integrates a quantitative evaluation of the outcomes of care for consumers at three residential rehabilitation units with an applied qualitative research methodology. The quantitative component utilizes a prospective cohort design to explore whether equivalent outcomes are achieved through engagement at residential rehabilitation units operating integrated and clinical staffing models. Comparative data will be available from the time of admission, discharge and 12-month period post-discharge from the units. Additionally, retrospective data for the 12-month period prior to admission will be utilized to consider changes in functioning pre and post engagement with residential rehabilitation care. The primary outcome will be change in psychosocial functioning, assessed using the total score on the Health of the Nation Outcome Scales (HoNOS). Planned secondary outcomes will include changes in symptomatology, disability, recovery orientation, carer quality of life, emergency department presentations, psychiatric inpatient bed days, and psychological distress and wellbeing. Planned analyses will include: cohort description; hierarchical linear regression modelling of the predictors of change in HoNOS following CCU care; and descriptive comparisons of the costs associated with the two staffing models. The qualitative component utilizes a pragmatic approach to grounded theory, with

A constitutive mechanical model for gas hydrate bearing sediments incorporating inelastic mechanisms

KAUST Repository

Sánchez, Marcelo

2016-11-30

Gas hydrate bearing sediments (HBS) are natural soils formed in permafrost and sub-marine settings where the temperature and pressure conditions are such that gas hydrates are stable. If these conditions shift from the hydrate stability zone, hydrates dissociate and move from the solid to the gas phase. Hydrate dissociation is accompanied by significant changes in sediment structure and strongly affects its mechanical behavior (e.g., sediment stiffenss, strength and dilatancy). The mechanical behavior of HBS is very complex and its modeling poses great challenges. This paper presents a new geomechanical model for hydrate bearing sediments. The model incorporates the concept of partition stress, plus a number of inelastic mechanisms proposed to capture the complex behavior of this type of soil. This constitutive model is especially well suited to simulate the behavior of HBS upon dissociation. The model was applied and validated against experimental data from triaxial and oedometric tests conducted on manufactured and natural specimens involving different hydrate saturation, hydrate morphology, and confinement conditions. Particular attention was paid to model the HBS behavior during hydrate dissociation under loading. The model performance was highly satisfactory in all the cases studied. It managed to properly capture the main features of HBS mechanical behavior and it also assisted to interpret the behavior of this type of sediment under different loading and hydrate conditions.

Quantifying Uncertainty in Flood Inundation Mapping Using Streamflow Ensembles and Multiple Hydraulic Modeling Techniques

Science.gov (United States)

Hosseiny, S. M. H.; Zarzar, C.; Gomez, M.; Siddique, R.; Smith, V.; Mejia, A.; Demir, I.

2016-12-01

The National Water Model (NWM) provides a platform for operationalize nationwide flood inundation forecasting and mapping. The ability to model flood inundation on a national scale will provide invaluable information to decision makers and local emergency officials. Often, forecast products use deterministic model output to provide a visual representation of a single inundation scenario, which is subject to uncertainty from various sources. While this provides a straightforward representation of the potential inundation, the inherent uncertainty associated with the model output should be considered to optimize this tool for decision making support. The goal of this study is to produce ensembles of future flood inundation conditions (i.e. extent, depth, and velocity) to spatially quantify and visually assess uncertainties associated with the predicted flood inundation maps. The setting for this study is located in a highly urbanized watershed along the Darby Creek in Pennsylvania. A forecasting framework coupling the NWM with multiple hydraulic models was developed to produce a suite ensembles of future flood inundation predictions. Time lagged ensembles from the NWM short range forecasts were used to account for uncertainty associated with the hydrologic forecasts. The forecasts from the NWM were input to iRIC and HEC-RAS two-dimensional software packages, from which water extent, depth, and flow velocity were output. Quantifying the agreement between output ensembles for each forecast grid provided the uncertainty metrics for predicted flood water inundation extent, depth, and flow velocity. For visualization, a series of flood maps that display flood extent, water depth, and flow velocity along with the underlying uncertainty associated with each of the forecasted variables were produced. The results from this study demonstrate the potential to incorporate and visualize model uncertainties in flood inundation maps in order to identify the high flood risk zones.

A Novel Approach of Understanding and Incorporating Error of Chemical Transport Models into a Geostatistical Framework

Science.gov (United States)

Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.

2015-12-01

The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.

Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model

Science.gov (United States)

Graves, T.A.; Kendall, Katherine C.; Royle, J. Andrew; Stetz, J.B.; Macleod, A.C.

2011-01-01

Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.

Multiple Imputation of Predictor Variables Using Generalized Additive Models

NARCIS (Netherlands)

de Jong, Roel; van Buuren, Stef; Spiess, Martin

2016-01-01

The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

Model Seleksi Premi Asuransi Jiwa Dwiguna untuk Kasus Multiple Decrement

OpenAIRE

Cita, Devi Ramana; Pane, Rolan; ', Harison

2015-01-01

This article discusses a select survival model for the case of multiple decrements in evaluating endowment life insurance premium for person currently aged ( + ) years, who is selected at age with ℎ years selection period. The case of multiple decrements in this case is limited to two cases. The calculation of the annual premium is done by prior evaluating of the single premium, and the present value of annuity depends on theconstant force assumption.

A multiple shock model for common cause failures using discrete Markov chain

International Nuclear Information System (INIS)

Chung, Dae Wook; Kang, Chang Soon

1992-01-01

The most widely used models in common cause analysis are (single) shock models such as the BFR, and the MFR. But, single shock model can not treat the individual common cause separately and has some irrational assumptions. Multiple shock model for common cause failures is developed using Markov chain theory. This model treats each common cause shock as separately and sequently occuring event to implicate the change in failure probability distribution due to each common cause shock. The final failure probability distribution is evaluated and compared with that from the BFR model. The results show that multiple shock model which minimizes the assumptions in the BFR model is more realistic and conservative than the BFR model. The further work for application is the estimations of parameters such as common cause shock rate and component failure probability given a shock,p, through the data analysis

Formulation and characterization of a multiple emulsion containing 1 ...

African Journals Online (AJOL)

The purpose of the study was to prepare a stable multiple emulsion containing a skin anti-aging agent and using paraffin oil. Vitamin C, was incorporated into the inner aqueous phase of water-in-oil-in-water (w/o/w) multiple emulsion at a concentration of 1%. Multiple emulsion was prepared by two step method. Stability ...

Incorporation of Plasticity and Damage Into an Orthotropic Three-Dimensional Model with Tabulated Input Suitable for Use in Composite Impact Problems

Science.gov (United States)

Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Hoffarth, Canio; Rajan,Subramaniam; Blackenhorn, Gunther

2015-01-01

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased usage in the aerospace and automotive industries. While there are several composite material models currently available within commercial transient dynamic finite element codes, several features have been identified as being lacking in the currently available material models that could substantially enhance the predictive capability of the impact simulations. A specific desired feature pertains to the incorporation of both plasticity and damage within the material model. Another desired feature relates to using experimentally based tabulated stress-strain input to define the evolution of plasticity and damage as opposed to specifying discrete input properties (such as modulus and strength) and employing analytical functions to track the response of the material. To begin to address these needs, a combined plasticity and damage model suitable for use with both solid and shell elements is being developed for implementation within the commercial code LS-DYNA. The plasticity model is based on extending the Tsai-Wu composite failure model into a strain-hardening based orthotropic plasticity model with a non-associative flow rule. The evolution of the yield surface is determined based on tabulated stress-strain curves in the various normal and shear directions and is tracked using the effective plastic strain. The effective plastic strain is computed by using the non-associative flow rule in combination with appropriate numerical methods. To compute the evolution of damage, a strain equivalent semi-coupled formulation is used, in which a load in one direction results in a stiffness reduction in multiple coordinate directions. A specific laminated composite is examined to demonstrate the process of characterizing and analyzing the response of a composite using the developed

The Answering Process for Multiple-Choice Questions in Collaborative Learning: A Mathematical Learning Model Analysis

Science.gov (United States)

Nakamura, Yasuyuki; Nishi, Shinnosuke; Muramatsu, Yuta; Yasutake, Koichi; Yamakawa, Osamu; Tagawa, Takahiro

2014-01-01

In this paper, we introduce a mathematical model for collaborative learning and the answering process for multiple-choice questions. The collaborative learning model is inspired by the Ising spin model and the model for answering multiple-choice questions is based on their difficulty level. An intensive simulation study predicts the possibility of…

Protein structure modeling for CASP10 by multiple layers of global optimization.

Science.gov (United States)

Joo, Keehyoung; Lee, Juyong; Sim, Sangjin; Lee, Sun Young; Lee, Kiho; Heo, Seungryong; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2014-02-01

In the template-based modeling (TBM) category of CASP10 experiment, we introduced a new protocol called protein modeling system (PMS) to generate accurate protein structures in terms of side-chains as well as backbone trace. In the new protocol, a global optimization algorithm, called conformational space annealing (CSA), is applied to the three layers of TBM procedure: multiple sequence-structure alignment, 3D chain building, and side-chain re-modeling. For 3D chain building, we developed a new energy function which includes new distance restraint terms of Lorentzian type (derived from multiple templates), and new energy terms that combine (physical) energy terms such as dynamic fragment assembly (DFA) energy, DFIRE statistical potential energy, hydrogen bonding term, etc. These physical energy terms are expected to guide the structure modeling especially for loop regions where no template structures are available. In addition, we developed a new quality assessment method based on random forest machine learning algorithm to screen templates, multiple alignments, and final models. For TBM targets of CASP10, we find that, due to the combination of three stages of CSA global optimizations and quality assessment, the modeling accuracy of PMS improves at each additional stage of the protocol. It is especially noteworthy that the side-chains of the final PMS models are far more accurate than the models in the intermediate steps. Copyright © 2013 Wiley Periodicals, Inc.

A toolkit for incorporating genetics into mainstream medical services: Learning from service development pilots in England

Directory of Open Access Journals (Sweden)

Burton Hilary

2010-05-01

Full Text Available Abstract Background As advances in genetics are becoming increasingly relevant to mainstream healthcare, a major challenge is to ensure that these are integrated appropriately into mainstream medical services. In 2003, the Department of Health for England announced the availability of start-up funding for ten 'Mainstreaming Genetics' pilot services to develop models to achieve this. Methods Multiple methods were used to explore the pilots' experiences of incorporating genetics which might inform the development of new services in the future. A workshop with project staff, an email questionnaire, interviews and a thematic analysis of pilot final reports were carried out. Results Seven themes relating to the integration of genetics into mainstream medical services were identified: planning services to incorporate genetics; the involvement of genetics departments; the establishment of roles incorporating genetic activities; identifying and involving stakeholders; the challenges of working across specialty boundaries; working with multiple healthcare organisations; and the importance of cultural awareness of genetic conditions. Pilots found that the planning phase often included the need to raise awareness of genetic conditions and services and that early consideration of organisational issues such as clinic location was essential. The formal involvement of genetics departments was crucial to success; benefits included provision of clinical and educational support for staff in new roles. Recruitment and retention for new roles outside usual career pathways sometimes proved difficult. Differences in specialties' working practices and working with multiple healthcare organisations also brought challenges such as the 'genetic approach' of working with families, incompatible record systems and different approaches to health professionals' autonomous practice. 'Practice points' have been collated into a Toolkit which includes resources from the pilots

Interacting Multiple Model (IMM Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

Directory of Open Access Journals (Sweden)

Hua Liu

2017-06-01

Full Text Available For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF. The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF, the interacting multiple model cubature Kalman filter (IMMCKF and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF.

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

Science.gov (United States)

Liu, Hua; Wu, Wen

2017-06-13

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

Science.gov (United States)

Xu, Xueli; von Davier, Matthias

2008-01-01

The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…

Automatic treatment of multiple wound coils in 3D finite element problems including multiply connected regions

Energy Technology Data Exchange (ETDEWEB)

Leonard, P.J.; Lai, H.C.; Eastham, J.F.; Al-Akayshee, Q.H. [Univ. of Bath (United Kingdom)

1996-05-01

This paper describes an efficient scheme for incorporating multiple wire wound coils into 3D finite element models. The scheme is based on the magnetic scalar representation with an additional basis for each coil. There are no restrictions on the topology of coils with respect to ferromagnetic and conductor regions. Reduced scalar regions and cuts are automatically generated.

A Fibrocontractive Mechanochemical Model of Dermal Wound Closure Incorporating Realistic Growth Factor Kinetics

KAUST Repository

Murphy, Kelly E.

2012-01-13

Fibroblasts and their activated phenotype, myofibroblasts, are the primary cell types involved in the contraction associated with dermal wound healing. Recent experimental evidence indicates that the transformation from fibroblasts to myofibroblasts involves two distinct processes: The cells are stimulated to change phenotype by the combined actions of transforming growth factor β (TGFβ) and mechanical tension. This observation indicates a need for a detailed exploration of the effect of the strong interactions between the mechanical changes and growth factors in dermal wound healing. We review the experimental findings in detail and develop a model of dermal wound healing that incorporates these phenomena. Our model includes the interactions between TGFβ and collagenase, providing a more biologically realistic form for the growth factor kinetics than those included in previous mechanochemical descriptions. A comparison is made between the model predictions and experimental data on human dermal wound healing and all the essential features are well matched. © 2012 Society for Mathematical Biology.

A Fibrocontractive Mechanochemical Model of Dermal Wound Closure Incorporating Realistic Growth Factor Kinetics

KAUST Repository

Murphy, Kelly E.; Hall, Cameron L.; Maini, Philip K.; McCue, Scott W.; McElwain, D. L. Sean

2012-01-01

Fibroblasts and their activated phenotype, myofibroblasts, are the primary cell types involved in the contraction associated with dermal wound healing. Recent experimental evidence indicates that the transformation from fibroblasts to myofibroblasts involves two distinct processes: The cells are stimulated to change phenotype by the combined actions of transforming growth factor β (TGFβ) and mechanical tension. This observation indicates a need for a detailed exploration of the effect of the strong interactions between the mechanical changes and growth factors in dermal wound healing. We review the experimental findings in detail and develop a model of dermal wound healing that incorporates these phenomena. Our model includes the interactions between TGFβ and collagenase, providing a more biologically realistic form for the growth factor kinetics than those included in previous mechanochemical descriptions. A comparison is made between the model predictions and experimental data on human dermal wound healing and all the essential features are well matched. © 2012 Society for Mathematical Biology.

Linear systems with unstructured multiplicative uncertainty: Modeling and robust stability analysis.

Directory of Open Access Journals (Sweden)

Radek Matušů

Full Text Available This article deals with continuous-time Linear Time-Invariant (LTI Single-Input Single-Output (SISO systems affected by unstructured multiplicative uncertainty. More specifically, its aim is to present an approach to the construction of uncertain models based on the appropriate selection of a nominal system and a weight function and to apply the fundamentals of robust stability investigation for considered sort of systems. The initial theoretical parts are followed by three extensive illustrative examples in which the first order time-delay, second order and third order plants with parametric uncertainty are modeled as systems with unstructured multiplicative uncertainty and subsequently, the robust stability of selected feedback loops containing constructed models and chosen controllers is analyzed and obtained results are discussed.

Individual and combined effects of multiple global change drivers on terrestrial phosphorus pools: A meta-analysis.

Science.gov (United States)

Yue, Kai; Yang, Wanqin; Peng, Yan; Peng, Changhui; Tan, Bo; Xu, Zhenfeng; Zhang, Li; Ni, Xiangyin; Zhou, Wei; Wu, Fuzhong

2018-07-15

Human activity-induced global change drivers have dramatically changed terrestrial phosphorus (P) dynamics. However, our understanding of the interactive effects of multiple global change drivers on terrestrial P pools remains elusive, limiting their incorporation into ecological and biogeochemical models. We conducted a meta-analysis using 1751 observations extracted from 283 published articles to evaluate the individual, combined, and interactive effects of elevated CO 2 , warming, N addition, P addition, increased rainfall, and drought on P pools of plant (at both single-plant and plant-community levels), soil and microbial biomass. Our results suggested that (1) terrestrial P pools showed the most sensitive responses to the individual effects of warming and P addition; (2) P pools were consistently stimulated by P addition alone or in combination with simultaneous N addition; (3) environmental and experimental setting factors such as ecosystem type, climate, and latitude could significantly influence both the individual and combined effects; and (4) the interactive effects of two-driver pairs across multiple global change drivers are more likely to be additive rather than synergistic or antagonistic. Our findings highlighting the importance of additive interactive effects among multiple global change drivers on terrestrial P pools would be useful for incorporating P as controls on ecological processes such as photosynthesis and plant growth into ecosystem models used to analyze effects of multiple drivers under future global change. Copyright © 2018 Elsevier B.V. All rights reserved.

A latent class multiple constraint multiple discrete-continuous extreme value model of time use and goods consumption.

Science.gov (United States)

2016-06-01

This paper develops a microeconomic theory-based multiple discrete continuous choice model that considers: (a) that both goods consumption and time allocations (to work and non-work activities) enter separately as decision variables in the utility fu...

Hybrid approaches for multiple-species stochastic reaction-diffusion models

Science.gov (United States)

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

2015-10-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Hybrid approaches for multiple-species stochastic reaction-diffusion models.

KAUST Repository

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K; Byrne, Helen

2015-01-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Hybrid approaches for multiple-species stochastic reaction-diffusion models.

KAUST Repository

Spill, Fabian

2015-10-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Risk Prediction Models for Other Cancers or Multiple Sites

Science.gov (United States)

Developing statistical models that estimate the probability of developing other multiple cancers over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Exclusive description of multiple production on nuclei in the additive quark model. Multiplicity distributions in interactions with heavy nuclei

International Nuclear Information System (INIS)

Levchenko, B.B.; Nikolaev, N.N.

1985-01-01

In the framework of the additive quark model of multiple production on nuclei we calculate the multiplicity distributions of secondary particles and the correlations between secondary particles in πA and pA interactions with heavy nuclei. We show that intranuclear cascades are responsible for up to 50% of the nuclear increase of the multiplicity of fast particles. We analyze the sensitivity of the multiplicities and their correlations to the choice of the quark-hadronization function. We show that with good accuracy the yield of relativistic secondary particles from heavy and intermediate nuclei depends only on the number N/sub p/ of protons knocked out of the nucleus, and not on the mass number of the nucleus (N/sub p/ scaling)

Multiple attribute decision making model and application to food safety risk evaluation.

Science.gov (United States)

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Sensitivity studies on the approaches for addressing multiple initiating events in fire events PSA

Energy Technology Data Exchange (ETDEWEB)

Kang, Dae Il; Lim, Ho Gon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2016-10-15

A single fire event within a fire compartment or a fire scenario can cause multiple initiating events (IEs). As an example, a fire in a turbine building fire area can cause a loss of the main feed-water (LOMF) and loss of off-site power (LOOP) IEs. Previous domestic fire events PSA had considered only the most severe initiating event among multiple initiating events. NUREG/CR-6850 and ANS/ASME PRA Standard require that multiple IEs are to be addressed in fire events PSA. In this paper, sensitivity studies on the approaches for addressing multiple IEs in fire events PSA for Hanul Unit 3 were performed and their results were presented. In this paper, sensitivity studies on the approaches for addressing multiple IEs in fire events PSA are performed and their results were presented. From the sensitivity analysis results, we can find that the incorporations of multiple IEs into fire events PSA model result in the core damage frequency (CDF) increase and may lead to the generation of the duplicate cutsets. Multiple IEs also can occur at internal flooding event or other external events such as seismic event. They should be considered in the constructions of PSA models in order to realistically estimate risk due to flooding or seismic events.

A mathematical model for maximizing the value of phase 3 drug development portfolios incorporating budget constraints and risk.

Science.gov (United States)

Patel, Nitin R; Ankolekar, Suresh; Antonijevic, Zoran; Rajicic, Natasa

2013-05-10

We describe a value-driven approach to optimizing pharmaceutical portfolios. Our approach incorporates inputs from research and development and commercial functions by simultaneously addressing internal and external factors. This approach differentiates itself from current practices in that it recognizes the impact of study design parameters, sample size in particular, on the portfolio value. We develop an integer programming (IP) model as the basis for Bayesian decision analysis to optimize phase 3 development portfolios using expected net present value as the criterion. We show how this framework can be used to determine optimal sample sizes and trial schedules to maximize the value of a portfolio under budget constraints. We then illustrate the remarkable flexibility of the IP model to answer a variety of 'what-if' questions that reflect situations that arise in practice. We extend the IP model to a stochastic IP model to incorporate uncertainty in the availability of drugs from earlier development phases for phase 3 development in the future. We show how to use stochastic IP to re-optimize the portfolio development strategy over time as new information accumulates and budget changes occur. Copyright © 2013 John Wiley & Sons, Ltd.

Penerapan Model Pembelajaran Atraktif Berbasis Multiple Intelligences Tentang Pemantulan Cahaya pada Cermin

Directory of Open Access Journals (Sweden)

Intan Kusumawati

2016-03-01

Full Text Available Penelitian ini bertujuan untuk mengetahui efektivitas penerapan model pembelajaran atraktif berbasis multiple intelligences dalam meremediasi miskonsepsi siswa tentang pemantulan cahaya pada cermin. Pada penelitian ini digunakan bentuk pre-eksperimental design dengan rancangan one group pretest-post test design. Alat pengumpulan data berupa tes pilihan ganda dengan reasoning. Hasil validitas sebesar 4,08 dan reliabilitas 0,537. Siswa dibagi menjadi lima kelompok kecerdasan, yaitu kelompok linguistic intelligence, mathematical-logical intelligence, visual-spatial intelligence, bodily-khinestetic intelligence, dan musical intelligence. Siswa membahas konsep fisika sesuai kelompok kecerdasannya dalam bentuk pembuatan pantun-puisi, teka-teki silang, menggambar kreatif, drama, dan mengarang lirik lagu. Efektivitas penerapan model pembelajaran multiple intelligences menggunakan persamaan effect size. Ditemukan bahwa skor effect size masing-masing kelompok berkategori tinggi sebesar 5,76; 3,76; 4,60; 1,70; dan 1,34. Penerapan model pembelajaran atraktif berbasis multiple intelligences efektif dalam meremediasi miskonsepsi siswa. Penelitian ini diharapkan dapat digunakan pada materi fisika dan sekolah lainnya.

Efficacy in Teaching through "Multiple Intelligence" Instructional Strategies

Science.gov (United States)

Tamilselvi, B.; Geetha, D.

2015-01-01

Multiple intelligence is the theory that "people are smart in more ways than one has immense implication for educators". Howard Gardner proposed a new view of intelligence that is rapidly being incorporated in school curricula. In his theory of Multiple Intelligences, Gardner expanded the concept of intelligence with such areas as music,…

A basket two-part model to analyze medical expenditure on interdependent multiple sectors.

Science.gov (United States)

Sugawara, Shinya; Wu, Tianyi; Yamanishi, Kenji

2018-05-01

This study proposes a novel statistical methodology to analyze expenditure on multiple medical sectors using consumer data. Conventionally, medical expenditure has been analyzed by two-part models, which separately consider purchase decision and amount of expenditure. We extend the traditional two-part models by adding the step of basket analysis for dimension reduction. This new step enables us to analyze complicated interdependence between multiple sectors without an identification problem. As an empirical application for the proposed method, we analyze data of 13 medical sectors from the Medical Expenditure Panel Survey. In comparison with the results of previous studies that analyzed the multiple sector independently, our method provides more detailed implications of the impacts of individual socioeconomic status on the composition of joint purchases from multiple medical sectors; our method has a better prediction performance.

MMOSS-I: a CANDU multiple-channel thermosyphoning flow stability model

Energy Technology Data Exchange (ETDEWEB)

Gulshani, P [Atomic Energy of Canada Ltd., Mississauga, ON (Canada); Huynh, H [Hydro-Quebec, Montreal, PQ (Canada)

1996-12-31

This paper presents a multiple-channel flow stability model, dubbed MMOSS, developed to predict the conditions for the onset of flow oscillations in a CANDU-type multiple-channel heat transport system under thermosyphoning conditions. The model generalizes that developed previously to account for the effects of any channel flow reversal. Two-phase thermosyphoning conditions are predicted by thermalhydraulic codes for some postulated accident scenarios in CANDU. Two-phase thermosyphoning experiments in the multiple-channel RD-14M facility have indicated that pass-to-pass out-of-phase oscillations in the loop conditions caused the flow in some of the heated channels to undergo sustained reversal in direction. This channel flow reversal had significant effects on the channel and loop conditions. It is, therefore, important to understand the nature of the oscillations and be able to predict the conditions for the onset of the oscillations or for stable flow in RD-14M and the reactor. For stable flow conditions, oscillation-induced channel flow reversal is not expected. MMOSS was developed for a figure-of-eight system with any number of channels. The system characteristic equation was derived from a linearization of the conservation equations. In this paper, the MMOSS characteristic equation is solved for a system of N identical channel assemblies. The resulting model is called MMOSS-I. This simplification provides valuable physical insight and reasonably accurate results. MMOSS-I and a previously-developed steady-state model THERMOSYPHON are used to predict thermosyphoning flow stability maps for RD-14M and the Gentilly 2 reactor. (author). 11 refs., 7 figs.

Multivariate Receptor Models for Spatially Correlated Multipollutant Data

KAUST Repository

Jun, Mikyoung

2013-08-01

The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air pollutant data measured at a single monitoring site or measurements of a single pollutant collected at multiple monitoring sites. Despite the growing availability of multipollutant data collected from multiple monitoring sites, there has not yet been any attempt to incorporate spatial dependence that may exist in such data into multivariate receptor modeling. We propose a spatial statistics extension of multivariate receptor models that enables us to incorporate spatial dependence into estimation of source composition profiles and contributions given the prespecified number of sources and the model identification conditions. The proposed method yields more precise estimates of source profiles by accounting for spatial dependence in the estimation. More importantly, it enables predictions of source contributions at unmonitored sites as well as when there are missing values at monitoring sites. The method is illustrated with simulated data and real multipollutant data collected from eight monitoring sites in Harris County, Texas. Supplementary materials for this article, including data and R code for implementing the methods, are available online on the journal web site. © 2013 Copyright Taylor and Francis Group, LLC.

Incorporation of a Wind Generator Model into a Dynamic Power Flow Analysis

Directory of Open Access Journals (Sweden)

Angeles-Camacho C.

2011-07-01

Full Text Available Wind energy is nowadays one of the most cost-effective and practical options for electric generation from renewable resources. However, increased penetration of wind generation causes the power networks to be more depend on, and vulnerable to, the varying wind speed. Modeling is a tool which can provide valuable information about the interaction between wind farms and the power network to which they are connected. This paper develops a realistic characterization of a wind generator. The wind generator model is incorporated into an algorithm to investigate its contribution to the stability of the power network in the time domain. The tool obtained is termed dynamic power flow. The wind generator model takes on account the wind speed and the reactive power consumption by induction generators. Dynamic power flow analysis is carried-out using real wind data at 10-minute time intervals collected for one meteorological station. The generation injected at one point into the network provides active power locally and is found to reduce global power losses. However, the power supplied is time-varying and causes fluctuations in voltage magnitude and power fl ows in transmission lines.

Model for nucleus-nucleus, hadron-nucleus and hadron-proton multiplicity distributions

International Nuclear Information System (INIS)

Singh, C.P.; Shyam, M.; Tuli, S.K.

1986-07-01

A model relating hadron-proton, hadron-nucleus and nucleus-nucleus multiplicity distributions is proposed and some interesting consequences are derived. The values of the parameters are the same for all the processes and are given by the QCD hypothesis of ''universal'' hadronic multiplicities which are found to be asymptotically independent of target and beam in hadronic and current induced reactions in particle physics. (author)

Multiple attribute decision making model and application to food safety risk evaluation.

Directory of Open Access Journals (Sweden)

Lihua Ma

Full Text Available Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

The crowded sea: incorporating multiple marine activities in conservation plans can significantly alter spatial priorities.

Directory of Open Access Journals (Sweden)

Tessa Mazor

Full Text Available Successful implementation of marine conservation plans is largely inhibited by inadequate consideration of the broader social and economic context within which conservation operates. Marine waters and their biodiversity are shared by a host of stakeholders, such as commercial fishers, recreational users and offshore developers. Hence, to improve implementation success of conservation plans, we must incorporate other marine activities while explicitly examining trade-offs that may be required. In this study, we test how the inclusion of multiple marine activities can shape conservation plans. We used the entire Mediterranean territorial waters of Israel as a case study to compare four planning scenarios with increasing levels of complexity, where additional zones, threats and activities were added (e.g., commercial fisheries, hydrocarbon exploration interests, aquaculture, and shipping lanes. We applied the marine zoning decision support tool Marxan to each planning scenario and tested a the ability of each scenario to reach biodiversity targets, b the change in opportunity cost and c the alteration of spatial conservation priorities. We found that by including increasing numbers of marine activities and zones in the planning process, greater compromises are required to reach conservation objectives. Complex plans with more activities incurred greater opportunity cost and did not reach biodiversity targets as easily as simplified plans with less marine activities. We discovered that including hydrocarbon data in the planning process significantly alters spatial priorities. For the territorial waters of Israel we found that in order to protect at least 10% of the range of 166 marine biodiversity features there would be a loss of ∼15% of annual commercial fishery revenue and ∼5% of prospective hydrocarbon revenue. This case study follows an illustrated framework for adopting a transparent systematic process to balance biodiversity goals and

A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise

DEFF Research Database (Denmark)

Dong, Yiqiu; Tieyong Zeng

2013-01-01

In this paper, a new variational model for restoring blurred images with multiplicative noise is proposed. Based on the statistical property of the noise, a quadratic penalty function technique is utilized in order to obtain a strictly convex model under a mild condition, which guarantees...

A General Method for QTL Mapping in Multiple Related Populations Derived from Multiple Parents

Directory of Open Access Journals (Sweden)

Yan AO

2009-03-01

Full Text Available It's well known that incorporating some existing populations derived from multiple parents may improve QTL mapping and QTL-based breeding programs. However, no general maximum likelihood method has been available for this strategy. Based on the QTL mapping in multiple related populations derived from two parents, a maximum likelihood estimation method was proposed, which can incorporate several populations derived from three or more parents and also can be used to handle different mating designs. Taking a circle design as an example, we conducted simulation studies to study the effect of QTL heritability and sample size upon the proposed method. The results showed that under the same heritability, enhanced power of QTL detection and more precise and accurate estimation of parameters could be obtained when three F2 populations were jointly analyzed, compared with the joint analysis of any two F2 populations. Higher heritability, especially with larger sample sizes, would increase the ability of QTL detection and improve the estimation of parameters. Potential advantages of the method are as follows: firstly, the existing results of QTL mapping in single population can be compared and integrated with each other with the proposed method, therefore the ability of QTL detection and precision of QTL mapping can be improved. Secondly, owing to multiple alleles in multiple parents, the method can exploit gene resource more adequately, which will lay an important genetic groundwork for plant improvement.

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Directory of Open Access Journals (Sweden)

Conor P. McGowan

2017-10-01

Full Text Available Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises in transparent and explicit ways tailored to support decision making processes related to endangered species.

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Science.gov (United States)

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

2017-01-01

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Modeling water scarcity over south Asia: Incorporating crop growth and irrigation models into the Variable Infiltration Capacity (VIC) model

Science.gov (United States)

Troy, Tara J.; Ines, Amor V. M.; Lall, Upmanu; Robertson, Andrew W.

2013-04-01

Large-scale hydrologic models, such as the Variable Infiltration Capacity (VIC) model, are used for a variety of studies, from drought monitoring to projecting the potential impact of climate change on the hydrologic cycle decades in advance. The majority of these models simulates the natural hydrological cycle and neglects the effects of human activities such as irrigation, which can result in streamflow withdrawals and increased evapotranspiration. In some parts of the world, these activities do not significantly affect the hydrologic cycle, but this is not the case in south Asia where irrigated agriculture has a large water footprint. To address this gap, we incorporate a crop growth model and irrigation model into the VIC model in order to simulate the impacts of irrigated and rainfed agriculture on the hydrologic cycle over south Asia (Indus, Ganges, and Brahmaputra basin and peninsular India). The crop growth model responds to climate signals, including temperature and water stress, to simulate the growth of maize, wheat, rice, and millet. For the primarily rainfed maize crop, the crop growth model shows good correlation with observed All-India yields (0.7) with lower correlations for the irrigated wheat and rice crops (0.4). The difference in correlation is because irrigation provides a buffer against climate conditions, so that rainfed crop growth is more tied to climate than irrigated crop growth. The irrigation water demands induce hydrologic water stress in significant parts of the region, particularly in the Indus, with the streamflow unable to meet the irrigation demands. Although rainfall can vary significantly in south Asia, we find that water scarcity is largely chronic due to the irrigation demands rather than being intermittent due to climate variability.

A selenium-deficient Caco-2 cell model for assessing differential incorporation of chemical or food selenium into glutathione peroxidase.

Science.gov (United States)

Zeng, Huawei; Botnen, James H; Johnson, Luann K

2008-01-01

Assessing the ability of a selenium (Se) sample to induce cellular glutathione peroxidase (GPx) activity in Se-deficient animals is the most commonly used method to determine Se bioavailability. Our goal is to establish a Se-deficient cell culture model with differential incorporation of Se chemical forms into GPx, which may complement the in vivo studies. In the present study, we developed a Se-deficient Caco-2 cell model with a serum gradual reduction method. It is well recognized that selenomethionine (SeMet) is the major nutritional source of Se; therefore, SeMet, selenite, or methylselenocysteine (SeMSC) was added to cell culture media with different concentrations and treatment time points. We found that selenite and SeMSC induced GPx more rapidly than SeMet. However, SeMet was better retained as it is incorporated into proteins in place of methionine; compared with 8-, 24-, or 48-h treatment, 72-h Se treatment was a more sensitive time point to measure the potential of GPx induction in all tested concentrations. Based on induction of GPx activity, the cellular bioavailability of Se from an extract of selenobroccoli after a simulated gastrointestinal digestion was comparable with that of SeMSC and SeMet. These in vitro data are, for the first time, consistent with previous published data regarding selenite and SeMet bioavailability in animal models and Se chemical speciation studies with broccoli. Thus, Se-deficient Caco-2 cell model with differential incorporation of chemical or food forms of Se into GPx provides a new tool to study the cellular mechanisms of Se bioavailability.

The empirical content of models with multiple equilibria in economies with social interactions

OpenAIRE

Alberto Bisin; Andrea Moro; Giorgio Topa

2011-01-01

We study a general class of models with social interactions that might display multiple equilibria. We propose an estimation procedure for these models and evaluate its efficiency and computational feasibility relative to different approaches taken to the curse of dimensionality implied by the multiplicity. Using data on smoking among teenagers, we implement the proposed estimation procedure to understand how group interactions affect health-related choices. We find that interaction effects a...

Crossflow-induced vibrations of tube banks: hydrodynamic forces and mathematical models

International Nuclear Information System (INIS)

Chen, S.S.

1977-01-01

The objective of this paper is to present a method of analysis for the hydrodynamic forces acting on tube banks and a mathematical model for multiple tubes and multiple excitation mechanisms incorporating tube/fluid coupling. The hydrodynamic forces acting on tube banks are analyzed using the two dimensional potential flow theory

Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

Science.gov (United States)

Samoli, Evangelia; Butland, Barbara K

2017-12-01

Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.

Dynamic coordinated control laws in multiple agent models

International Nuclear Information System (INIS)

Morgan, David S.; Schwartz, Ira B.

2005-01-01

We present an active control scheme of a kinetic model of swarming. It has been shown previously that the global control scheme for the model, presented in [Systems Control Lett. 52 (2004) 25], gives rise to spontaneous collective organization of agents into a unified coherent swarm, via steering controls and utilizing long-range attractive and short-range repulsive interactions. We extend these results by presenting control laws whereby a single swarm is broken into independently functioning subswarm clusters. The transition between one coordinated swarm and multiple clustered subswarms is managed simply with a homotopy parameter. Additionally, we present as an alternate formulation, a local control law for the same model, which implements dynamic barrier avoidance behavior, and in which swarm coherence emerges spontaneously

Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

Science.gov (United States)

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

2014-01-01

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

Progresive diseases study using Markov´s multiple stage models

Directory of Open Access Journals (Sweden)

René Iral Palomino, Esp estadística

2005-12-01

Full Text Available Risk factors and their degree of association with a progressive disease,such as Alzheimerís disease or liver cancer, can be identifi edby using epidemiological models; some examples of these modelsinclude logistic and Poisson regression, log-linear, linear regression,and mixed models. Using models that take into account not onlythe different health status that a person could experience betweenvisits but also his/her characteristics (i.e. age, gender, genetic traits,etc. seems to be reasonable and justifi ed. In this paper we discussa methodology to estimate the effect of covariates that could beassociated with a disease when its progression or regression canbe idealized by means of a multi-state model that incorporates thelongitudinal nature of data. This method is based on the Markovproperty and it is illustrated using simulated data about Alzheimerísdisease. Finally, the merits and limitations of this method are discussed.

A feedback control model for network flow with multiple pure time delays

Science.gov (United States)

Press, J.

1972-01-01

A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.

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

Science.gov (United States)

Shahrooei, Abolfazl; Kazemi, Mohammad Hosein

2018-04-01

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

Discontinuous Galerkin Time-Domain Modeling of Graphene Nano-Ribbon Incorporating the Spatial Dispersion Effects

KAUST Repository

Li, Ping; Jiang, Li Jun; Bagci, Hakan

2018-01-01

It is well known that graphene demonstrates spatial dispersion properties, i.e., its conductivity is nonlocal and a function of spectral wave number (momentum operator) q. In this paper, to account for effects of spatial dispersion on transmission of high speed signals along graphene nano-ribbon (GNR) interconnects, a discontinuous Galerkin time-domain (DGTD) algorithm is proposed. The atomically-thick GNR is modeled using a nonlocal transparent surface impedance boundary condition (SIBC) incorporated into the DGTD scheme. Since the conductivity is a complicated function of q (and one cannot find an analytical Fourier transform pair between q and spatial differential operators), an exact time domain SIBC model cannot be derived. To overcome this problem, the conductivity is approximated by its Taylor series in spectral domain under low-q assumption. This approach permits expressing the time domain SIBC in the form of a second-order partial differential equation (PDE) in current density and electric field intensity. To permit easy incorporation of this PDE with the DGTD algorithm, three auxiliary variables, which degenerate the second-order (temporal and spatial) differential operators to first-order ones, are introduced. Regarding to the temporal dispersion effects, the auxiliary differential equation (ADE) method is utilized to eliminates the expensive temporal convolutions. To demonstrate the applicability of the proposed scheme, numerical results, which involve characterization of spatial dispersion effects on the transfer impedance matrix of GNR interconnects, are presented.

Discontinuous Galerkin Time-Domain Modeling of Graphene Nano-Ribbon Incorporating the Spatial Dispersion Effects

KAUST Repository

Li, Ping

2018-04-13

It is well known that graphene demonstrates spatial dispersion properties, i.e., its conductivity is nonlocal and a function of spectral wave number (momentum operator) q. In this paper, to account for effects of spatial dispersion on transmission of high speed signals along graphene nano-ribbon (GNR) interconnects, a discontinuous Galerkin time-domain (DGTD) algorithm is proposed. The atomically-thick GNR is modeled using a nonlocal transparent surface impedance boundary condition (SIBC) incorporated into the DGTD scheme. Since the conductivity is a complicated function of q (and one cannot find an analytical Fourier transform pair between q and spatial differential operators), an exact time domain SIBC model cannot be derived. To overcome this problem, the conductivity is approximated by its Taylor series in spectral domain under low-q assumption. This approach permits expressing the time domain SIBC in the form of a second-order partial differential equation (PDE) in current density and electric field intensity. To permit easy incorporation of this PDE with the DGTD algorithm, three auxiliary variables, which degenerate the second-order (temporal and spatial) differential operators to first-order ones, are introduced. Regarding to the temporal dispersion effects, the auxiliary differential equation (ADE) method is utilized to eliminates the expensive temporal convolutions. To demonstrate the applicability of the proposed scheme, numerical results, which involve characterization of spatial dispersion effects on the transfer impedance matrix of GNR interconnects, are presented.

Structured spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

DEFF Research Database (Denmark)

Møller, Jesper; Diaz-Avalos, Carlos

Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

Structured Spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires

DEFF Research Database (Denmark)

Møller, Jesper; Diaz-Avalos, Carlos

2010-01-01

Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....

Improving the Pattern Reproducibility of Multiple-Point-Based Prior Models Using Frequency Matching

DEFF Research Database (Denmark)

Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus

2014-01-01

Some multiple-point-based sampling algorithms, such as the snesim algorithm, rely on sequential simulation. The conditional probability distributions that are used for the simulation are based on statistics of multiple-point data events obtained from a training image. During the simulation, data...... events with zero probability in the training image statistics may occur. This is handled by pruning the set of conditioning data until an event with non-zero probability is found. The resulting probability distribution sampled by such algorithms is a pruned mixture model. The pruning strategy leads...... to a probability distribution that lacks some of the information provided by the multiple-point statistics from the training image, which reduces the reproducibility of the training image patterns in the outcome realizations. When pruned mixture models are used as prior models for inverse problems, local re...

Incorporating a Time Horizon in Rate-of-Return Estimations: Discounted Cash Flow Model in Electric Transmission Rate Cases

International Nuclear Information System (INIS)

Chatterjee, Bishu; Sharp, Peter A.

2006-01-01

Electric transmission and other rate cases use a form of the discounted cash flow model with a single long-term growth rate to estimate rates of return on equity. It cannot incorporate information about the appropriate time horizon for which analysts' estimates of earnings growth have predictive powers. Only a non-constant growth model can explicitly recognize the importance of the time horizon in an ROE calculation. (author)

The reverse effects of random perturbation on discrete systems for single and multiple population models

International Nuclear Information System (INIS)

Kang, Li; Tang, Sanyi

2016-01-01

Highlights: • The discrete single species and multiple species models with random perturbation are proposed. • The complex dynamics and interesting bifurcation behavior have been investigated. • The reverse effects of random perturbation on discrete systems have been discussed and revealed. • The main results can be applied for pest control and resources management. - Abstract: The natural species are likely to present several interesting and complex phenomena under random perturbations, which have been confirmed by simple mathematical models. The important questions are: how the random perturbations influence the dynamics of the discrete population models with multiple steady states or multiple species interactions? and is there any different effects for single species and multiple species models with random perturbation? To address those interesting questions, we have proposed the discrete single species model with two stable equilibria and the host-parasitoid model with Holling type functional response functions to address how the random perturbation affects the dynamics. The main results indicate that the random perturbation does not change the number of blurred orbits of the single species model with two stable steady states compared with results for the classical Ricker model with same random perturbation, but it can strength the stability. However, extensive numerical investigations depict that the random perturbation does not influence the complexities of the host-parasitoid models compared with the results for the models without perturbation, while it does increase the period of periodic orbits doubly. All those confirm that the random perturbation has a reverse effect on the dynamics of the discrete single and multiple population models, which could be applied in reality including pest control and resources management.

Theoretical Models of Protostellar Binary and Multiple Systems with AMR Simulations

Science.gov (United States)

Matsumoto, Tomoaki; Tokuda, Kazuki; Onishi, Toshikazu; Inutsuka, Shu-ichiro; Saigo, Kazuya; Takakuwa, Shigehisa

2017-05-01

We present theoretical models for protostellar binary and multiple systems based on the high-resolution numerical simulation with an adaptive mesh refinement (AMR) code, SFUMATO. The recent ALMA observations have revealed early phases of the binary and multiple star formation with high spatial resolutions. These observations should be compared with theoretical models with high spatial resolutions. We present two theoretical models for (1) a high density molecular cloud core, MC27/L1521F, and (2) a protobinary system, L1551 NE. For the model for MC27, we performed numerical simulations for gravitational collapse of a turbulent cloud core. The cloud core exhibits fragmentation during the collapse, and dynamical interaction between the fragments produces an arc-like structure, which is one of the prominent structures observed by ALMA. For the model for L1551 NE, we performed numerical simulations of gas accretion onto protobinary. The simulations exhibit asymmetry of a circumbinary disk. Such asymmetry has been also observed by ALMA in the circumbinary disk of L1551 NE.

Incorporating time-delays in S-System model for reverse engineering genetic networks.

Science.gov (United States)

Chowdhury, Ahsan Raja; Chetty, Madhu; Vinh, Nguyen Xuan

2013-06-18

In any gene regulatory network (GRN), the complex interactions occurring amongst transcription factors and target genes can be either instantaneous or time-delayed. However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. As a result, all these approaches cannot detect important interactions of the other type. S-System model, a differential equation based approach which has been increasingly applied for modeling GRNs, also suffers from this limitation. In fact, all S-System based existing modeling approaches have been designed to capture only instantaneous interactions, and are unable to infer time-delayed interactions. In this paper, we propose a novel Time-Delayed S-System (TDSS) model which uses a set of delay differential equations to represent the system dynamics. The ability to incorporate time-delay parameters in the proposed S-System model enables simultaneous modeling of both instantaneous and time-delayed interactions. Furthermore, the delay parameters are not limited to just positive integer values (corresponding to time stamps in the data), but can also take fractional values. Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time significantly but also improves model accuracy. The evaluation criterion systematically adapts the max-min in-degrees and also systematically balances the effect of network accuracy and complexity during optimization. The four well-known performance measures applied to the experimental studies on synthetic networks with various time-delayed regulations clearly demonstrate that the proposed method can capture both instantaneous and delayed interactions correctly with high precision. The experiments carried out on two well-known real-life networks, namely IRMA and SOS DNA repair network in

Vehicle coordinated transportation dispatching model base on multiple crisis locations

Science.gov (United States)

Tian, Ran; Li, Shanwei; Yang, Guoying

2018-05-01

Many disastrous events are often caused after unconventional emergencies occur, and the requirements of disasters are often different. It is difficult for a single emergency resource center to satisfy such requirements at the same time. Therefore, how to coordinate the emergency resources stored by multiple emergency resource centers to various disaster sites requires the coordinated transportation of emergency vehicles. In this paper, according to the problem of emergency logistics coordination scheduling, based on the related constraints of emergency logistics transportation, an emergency resource scheduling model based on multiple disasters is established.

Using Video-Based Modeling to Promote Acquisition of Fundamental Motor Skills

Science.gov (United States)

Obrusnikova, Iva; Rattigan, Peter J.

2016-01-01

Video-based modeling is becoming increasingly popular for teaching fundamental motor skills to children in physical education. Two frequently used video-based instructional strategies that incorporate modeling are video prompting (VP) and video modeling (VM). Both strategies have been used across multiple disciplines and populations to teach a…

A P-value model for theoretical power analysis and its applications in multiple testing procedures

Directory of Open Access Journals (Sweden)

Fengqing Zhang

2016-10-01

Full Text Available Abstract Background Power analysis is a critical aspect of the design of experiments to detect an effect of a given size. When multiple hypotheses are tested simultaneously, multiplicity adjustments to p-values should be taken into account in power analysis. There are a limited number of studies on power analysis in multiple testing procedures. For some methods, the theoretical analysis is difficult and extensive numerical simulations are often needed, while other methods oversimplify the information under the alternative hypothesis. To this end, this paper aims to develop a new statistical model for power analysis in multiple testing procedures. Methods We propose a step-function-based p-value model under the alternative hypothesis, which is simple enough to perform power analysis without simulations, but not too simple to lose the information from the alternative hypothesis. The first step is to transform distributions of different test statistics (e.g., t, chi-square or F to distributions of corresponding p-values. We then use a step function to approximate each of the p-value’s distributions by matching the mean and variance. Lastly, the step-function-based p-value model can be used for theoretical power analysis. Results The proposed model is applied to problems in multiple testing procedures. We first show how the most powerful critical constants can be chosen using the step-function-based p-value model. Our model is then applied to the field of multiple testing procedures to explain the assumption of monotonicity of the critical constants. Lastly, we apply our model to a behavioral weight loss and maintenance study to select the optimal critical constants. Conclusions The proposed model is easy to implement and preserves the information from the alternative hypothesis.

Incorporation of aqueous reaction kinetics and biodegradation intoTOUGHREACT: Application of a multi-region model to hydrobiogeoChemicaltransport of denitrification and sulfate reduction

Energy Technology Data Exchange (ETDEWEB)

Xu, Tianfu

2006-07-13

The need to consider aqueous and sorption kinetics andmicrobiological processes arises in many subsurface problems. Ageneral-rate expression has been implemented into the TOUGHREACTsimulator, which considers multiple mechanisms (pathways) and includesmultiple product, Monod, and inhibition terms. This paper presents aformulation for incorporating kinetic rates among primary species intomass-balance equations. The space discretization used is based on aflexible integral finite difference approach that uses irregular griddingto model bio-geologic structures. A general multi-region model forhydrological transport interacted with microbiological and geochemicalprocesses is proposed. A 1-D reactive transport problem with kineticbiodegradation and sorption was used to test the enhanced simulator,which involves the processes that occur when a pulse of water containingNTA (nitrylotriacetate) and cobalt is injected into a column. The currentsimulation results agree very well with those obtained with othersimulators. The applicability of this general multi-region model wasvalidated by results from a published column experiment ofdenitrification and sulfate reduction. The matches with measured nitrateand sulfate concentrations were adjusted with the interficial areabetween mobile hydrological and immobile biological regions. Resultssuggest that TOUGHREACT can not only be a useful interpretative tool forbiogeochemical experiments, but also can produce insight into processesand parameters of microscopic diffusion and their interplay withbiogeochemical reactions. The geometric- and process-based multi-regionmodel may provide a framework for understanding field-scalehydrobiogeochemical heterogeneities and upscaling parameters.

Challenges in LCA modelling of multiple loops for aluminium cans

DEFF Research Database (Denmark)

Niero, Monia; Olsen, Stig Irving

considered the case of closed-loop recycling for aluminium cans, where body and lid are different alloys, and discussed the abovementioned challenge. The Life Cycle Inventory (LCI) modelling of aluminium processes is traditionally based on a pure aluminium flow, therefore neglecting the presence of alloying...... elements. We included the effect of alloying elements on the LCA modelling of aluminium can recycling. First, we performed a mass balance of the main alloying elements (Mn, Fe, Si, Cu) in aluminium can recycling at increasing levels of recycling rate. The analysis distinguished between different aluminium...... packaging scrap sources (i.e. used beverage can and mixed aluminium packaging) to understand the limiting factors for multiple loop aluminium can recycling. Secondly, we performed a comparative LCA of aluminium can production and recycling in multiple loops considering the two aluminium packaging scrap...

A minimal unified model of disease trajectories captures hallmarks of multiple sclerosis

KAUST Repository

Kannan, Venkateshan

2017-03-29

Multiple Sclerosis (MS) is an autoimmune disease targeting the central nervous system (CNS) causing demyelination and neurodegeneration leading to accumulation of neurological disability. Here we present a minimal, computational model involving the immune system and CNS that generates the principal subtypes of the disease observed in patients. The model captures several key features of MS, especially those that distinguish the chronic progressive phase from that of the relapse-remitting. In addition, a rare subtype of the disease, progressive relapsing MS naturally emerges from the model. The model posits the existence of two key thresholds, one in the immune system and the other in the CNS, that separate dynamically distinct behavior of the model. Exploring the two-dimensional space of these thresholds, we obtain multiple phases of disease evolution and these shows greater variation than the clinical classification of MS, thus capturing the heterogeneity that is manifested in patients.

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

Science.gov (United States)

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

2018-03-01

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

Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?

Directory of Open Access Journals (Sweden)

Hayduk Leslie A

2012-10-01

Full Text Available Abstract Background Structural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling’s openness to fewer indicators. Discussion Multiple indicators hamper theory by unnecessarily restricting the number of modeled latents. Using the few best indicators – possibly even the single best indicator of each latent – encourages development of theoretically sophisticated models. Additional latent variables permit stronger statistical control of potential confounders, and encourage detailed investigation of mediating causal mechanisms. Summary We recommend the use of the few best indicators. One or two indicators are often sufficient, but three indicators may occasionally be helpful. More than three indicators are rarely warranted because additional redundant indicators provide less research benefit than single indicators of additional latent variables. Scales created from multiple indicators can introduce additional problems, and are prone to being less desirable than either single or multiple indicators.

A Model of Distraction using new Architectural Mechanisms to Manage Multiple Goals

NARCIS (Netherlands)

Taatgen, Niels; Katidioti, Ioanna; Borst, Jelmer; van Vugt, Marieke; Taatgen, Niels; van Vugt, Marieke; Borst, Jelmer; Mehlhorn, Katja

2015-01-01

Cognitive models assume a one-to-one correspondence between task and goals. We argue that modeling a task by combining multiple goals has several advantages: a task can be constructed from components that are reused from other tasks, and it enables modeling thought processes that compete with or

A hybrid regional approach to model discharge at multiple sub-basins within the Calapooia Watershed, Oregon, USA

Science.gov (United States)

Modeling is a useful tool for quantifying ecosystem services and understanding their temporal dynamics. Here we describe a hybrid regional modeling approach for sub-basins of the Calapooia watershed that incorporates both a precipitation-runoff model and an indexed regression mo...

Exciton delocalization incorporated drift-diffusion model for bulk-heterojunction organic solar cells

Science.gov (United States)

Wang, Zi Shuai; Sha, Wei E. I.; Choy, Wallace C. H.

2016-12-01

Modeling the charge-generation process is highly important to understand device physics and optimize power conversion efficiency of bulk-heterojunction organic solar cells (OSCs). Free carriers are generated by both ultrafast exciton delocalization and slow exciton diffusion and dissociation at the heterojunction interface. In this work, we developed a systematic numerical simulation to describe the charge-generation process by a modified drift-diffusion model. The transport, recombination, and collection of free carriers are incorporated to fully capture the device response. The theoretical results match well with the state-of-the-art high-performance organic solar cells. It is demonstrated that the increase of exciton delocalization ratio reduces the energy loss in the exciton diffusion-dissociation process, and thus, significantly improves the device efficiency, especially for the short-circuit current. By changing the exciton delocalization ratio, OSC performances are comprehensively investigated under the conditions of short-circuit and open-circuit. Particularly, bulk recombination dependent fill factor saturation is unveiled and understood. As a fundamental electrical analysis of the delocalization mechanism, our work is important to understand and optimize the high-performance OSCs.

Incorporating X–ray summing into gamma–gamma signature quantification

International Nuclear Information System (INIS)

Britton, R.; Jackson, M.J.; Davies, A.V.

2016-01-01

A method for quantifying coincidence signatures has been extended to incorporate the effects of X–ray summing, and tested using a high–efficiency γ–γ system. An X–ray library has been created, allowing all possible γ, X–ray and conversion electron cascades to be generated. The equations for calculating efficiency and cascade summing corrected coincidence signature probabilities have also been extended from a two γ, two detector ‘special case’ to an arbitrarily large system. The coincidence library generated is fully searchable by energy, nuclide, coincidence pair, γ multiplicity, cascade probability and the half–life of the cascade, allowing the user to quickly identify coincidence signatures of interest. The method and software described is inherently flexible, as it only requires evaluated nuclear data, an X–ray library, and accurate efficiency characterisations to quickly and easily calculate coincidence signature probabilities for a variety of systems. Additional uses for the software include the fast identification of γ coincidence signals with required multiplicities and branching ratios, identification of the optimal coincidence signatures to measure for a particular system, and the calculation of cascade summing corrections for single detector systems. - Highlights: • Method for incorporating X-ray summing into coincidence measurements developed. • Calculation routines have been extended to an arbitrarily large detector system, and re-written to take advantage of multiple computing cores. • Data collected in list-mode with all events timestamped for offline coincidence analysis. • Coincidence analysis of environmental samples will dramatically improve the detection sensitivity achievable.

Incorporating Context Dependency of Species Interactions in Species Distribution Models.

Science.gov (United States)

Lany, Nina K; Zarnetske, Phoebe L; Gouhier, Tarik C; Menge, Bruce A

2017-07-01

Species distribution models typically use correlative approaches that characterize the species-environment relationship using occurrence or abundance data for a single species. However, species distributions are determined by both abiotic conditions and biotic interactions with other species in the community. Therefore, climate change is expected to impact species through direct effects on their physiology and indirect effects propagated through their resources, predators, competitors, or mutualists. Furthermore, the sign and strength of species interactions can change according to abiotic conditions, resulting in context-dependent species interactions that may change across space or with climate change. Here, we incorporated the context dependency of species interactions into a dynamic species distribution model. We developed a multi-species model that uses a time-series of observational survey data to evaluate how abiotic conditions and species interactions affect the dynamics of three rocky intertidal species. The model further distinguishes between the direct effects of abiotic conditions on abundance and the indirect effects propagated through interactions with other species. We apply the model to keystone predation by the sea star Pisaster ochraceus on the mussel Mytilus californianus and the barnacle Balanus glandula in the rocky intertidal zone of the Pacific coast, USA. Our method indicated that biotic interactions between P. ochraceus and B. glandula affected B. glandula dynamics across >1000 km of coastline. Consistent with patterns from keystone predation, the growth rate of B. glandula varied according to the abundance of P. ochraceus in the previous year. The data and the model did not indicate that the strength of keystone predation by P. ochraceus varied with a mean annual upwelling index. Balanus glandula cover increased following years with high phytoplankton abundance measured as mean annual chlorophyll-a. M. californianus exhibited the same

A dynamical model of car-following with the consideration of the multiple information of preceding cars

International Nuclear Information System (INIS)

Peng, G.H.; Sun, D.H.

2010-01-01

An improved multiple car-following (MCF) model is proposed, based on the full velocity difference (FVD) model, but taking into consideration multiple information inputs from preceding vehicles. The linear stability condition of the model is obtained by using the linear stability theory. Through nonlinear analysis, the modified Korteweg-de Vries (mKdV) equation is derived to describe the traffic behavior near the critical point. Numerical simulation shows that the proposed model is theoretically an improvement over others, while retaining many strong points in the previous ones by adjusting the information of the multiple leading vehicles.

Multiple sequential failure model: A probabilistic approach to quantifying human error dependency

International Nuclear Information System (INIS)

Samanta

1985-01-01

This paper rpesents a probabilistic approach to quantifying human error dependency when multiple tasks are performed. Dependent human failures are dominant contributors to risks from nuclear power plants. An overview of the Multiple Sequential Failure (MSF) model developed and its use in probabilistic risk assessments (PRAs) depending on the available data are discussed. A small-scale psychological experiment was conducted on the nature of human dependency and the interpretation of the experimental data by the MSF model show remarkable accommodation of the dependent failure data. The model, which provides an unique method for quantification of dependent failures in human reliability analysis, can be used in conjunction with any of the general methods currently used for performing the human reliability aspect in PRAs

Energy system investment model incorporating heat pumps with thermal storage in buildings and buffer tanks

DEFF Research Database (Denmark)

Hedegaard, Karsten; Balyk, Olexandr

2013-01-01

Individual compression heat pumps constitute a potentially valuable resource in supporting wind power integration due to their economic competitiveness and possibilities for flexible operation. When analysing the system benefits of flexible heat pump operation, effects on investments should...... be taken into account. In this study, we present a model that facilitates analysing individual heat pumps and complementing heat storages in integration with the energy system, while optimising both investments and operation. The model incorporates thermal building dynamics and covers various heat storage...... of operating heat pumps flexibly. This includes prioritising heat pump operation for hours with low marginal electricity production costs, and peak load shaving resulting in a reduced need for peak and reserve capacity investments....

Multiple Surrogate Modeling for Wire-Wrapped Fuel Assembly Optimization

International Nuclear Information System (INIS)

Raza, Wasim; Kim, Kwang-Yong

2007-01-01

In this work, shape optimization of seven pin wire wrapped fuel assembly has been carried out in conjunction with RANS analysis in order to evaluate the performances of surrogate models. Previously, Ahmad and Kim performed the flow and heat transfer analysis based on the three-dimensional RANS analysis. But numerical optimization has not been applied to the design of wire-wrapped fuel assembly, yet. Surrogate models are being widely used in multidisciplinary optimization. Queipo et al. reviewed various surrogates based models used in aerospace applications. Goel et al. developed weighted average surrogate model based on response surface approximation (RSA), radial basis neural network (RBNN) and Krigging (KRG) models. In addition to the three basic models, RSA, RBNN and KRG, the multiple surrogate model, PBA also has been employed. Two geometric design variables and a multi-objective function with a weighting factor have been considered for this problem

Procurement-distribution model for perishable items with quantity discounts incorporating freight policies under fuzzy environment

Directory of Open Access Journals (Sweden)

Makkar Sandhya

2013-01-01

Full Text Available A significant issue of the supply chain problem is how to integrate different entities. Managing supply chain is a difficult task because of complex integrations, especially when the products are perishable in nature. Little attention has been paid on ordering specific perishable products jointly in uncertain environment with multiple sources and multiple destinations. In this article, we propose a supply chain coordination model through quantity and freight discount policy for perishable products under uncertain cost and demand information. A case is provided to validate the procedure.

Logisnet: A tool for multimethod, multiple soil layers slope stability analysis

Science.gov (United States)

Legorreta Paulin, G.; Bursik, M.

2009-05-01

Shallow landslides and slope failures have been studied from several points of view (inventory, heuristic, statistic, and deterministic). In particular, numerous methods embedded in Geographic Information Systems (GIS) applications have been developed to assess slope stability. However, little work has been done on the systematic comparison of different techniques and the incorporation of vertical contrasts of geotechnical properties in multiple soil layers. In this research, stability is modeled by using LOGISNET, an acronym for Multiple Logistic Regression, Geographic Information System, and Neural Network. The main purpose of LOGISNET is to provide government planners and decision makers a tool to assess landslide susceptibility. The system is fully operational for models handling an enhanced cartographic-hydrologic model (SINMAP) and multiple logistic regression. The enhanced implementation of SINMAP was tested at regional scale in the Highway 101 corridor in Del Norte County, California, and its susceptibility map was found to have improved factor of safety estimates based on comparison with landslide inventory maps. The enhanced SINMAP and multiple logistic regression subsystems have functions that allow the user to include vertical variation in geotechnical properties through summation of forces in specific soil layers acting on failure planes for a local or regional-scale mapping. The working group of LOGISNET foresees the development of an integrated tool system to handle and support the prognostic studies of slope instability, and communicate the results to the public through maps.

Multiple-point statistical simulation for hydrogeological models: 3-D training image development and conditioning strategies

Science.gov (United States)

Høyer, Anne-Sophie; Vignoli, Giulio; Mejer Hansen, Thomas; Thanh Vu, Le; Keefer, Donald A.; Jørgensen, Flemming

2017-12-01

Most studies on the application of geostatistical simulations based on multiple-point statistics (MPS) to hydrogeological modelling focus on relatively fine-scale models and concentrate on the estimation of facies-level structural uncertainty. Much less attention is paid to the use of input data and optimal construction of training images. For instance, even though the training image should capture a set of spatial geological characteristics to guide the simulations, the majority of the research still relies on 2-D or quasi-3-D training images. In the present study, we demonstrate a novel strategy for 3-D MPS modelling characterized by (i) realistic 3-D training images and (ii) an effective workflow for incorporating a diverse group of geological and geophysical data sets. The study covers an area of 2810 km2 in the southern part of Denmark. MPS simulations are performed on a subset of the geological succession (the lower to middle Miocene sediments) which is characterized by relatively uniform structures and dominated by sand and clay. The simulated domain is large and each of the geostatistical realizations contains approximately 45 million voxels with size 100 m × 100 m × 5 m. Data used for the modelling include water well logs, high-resolution seismic data, and a previously published 3-D geological model. We apply a series of different strategies for the simulations based on data quality, and develop a novel method to effectively create observed spatial trends. The training image is constructed as a relatively small 3-D voxel model covering an area of 90 km2. We use an iterative training image development strategy and find that even slight modifications in the training image create significant changes in simulations. Thus, this study shows how to include both the geological environment and the type and quality of input information in order to achieve optimal results from MPS modelling. We present a practical workflow to build the training image and

Modeling and optimization of a utility system containing multiple extractions steam turbines

International Nuclear Information System (INIS)

Luo, Xianglong; Zhang, Bingjian; Chen, Ying; Mo, Songping

2011-01-01

Complex turbines with multiple controlled and/or uncontrolled extractions are popularly used in the processing industry and cogeneration plants to provide steam of different levels, electric power, and driving power. To characterize thermodynamic behavior under varying conditions, nonlinear mathematical models are developed based on energy balance, thermodynamic principles, and semi-empirical equations. First, the complex turbine is decomposed into several simple turbines from the controlled extraction stages and modeled in series. THM (The turbine hardware model) developing concept is applied to predict the isentropic efficiency of the decomposed simple turbines. Stodola's formulation is also used to simulate the uncontrolled extraction steam parameters. The thermodynamic properties of steam and water are regressed through linearization or piece-wise linearization. Second, comparison between the simulated results using the proposed model and the data in the working condition diagram provided by the manufacturer is conducted over a wide range of operations. The simulation results yield small deviation from the data in the working condition diagram where the maximum modeling error is 0.87% among the compared seven operation conditions. Last, the optimization model of a utility system containing multiple extraction turbines is established and a detailed case is analyzed. Compared with the conventional operation strategy, a maximum of 5.47% of the total operation cost is saved using the proposed optimization model. -- Highlights: → We develop a complete simulation model for steam turbine with multiple extractions. → We test the simulation model using the performance data of commercial turbines. → The simulation error of electric power generation is no more than 0.87%. → We establish a utility system operational optimization model. → The optimal industrial operation scheme featured with 5.47% of cost saving.

Modelling the Dynamics of Intracellular Processes as an Organisation of Multiple Agents

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.; Armano, G.; Merelli, E.; Denzinger, J.; Martin, A.; Miles, S.; Tianfield, H.; Unland, R.

2005-01-01

This paper explores how the dynamics of complex biological processes can be modeled as an organisation of multiple agents. This modelling perspective identifies organisational structure occurring in complex decentralised processes and handles complexity of the analysis of the dynamics by structuring

A modeling and numerical algorithm for thermoporomechanics in multiple porosity media for naturally fractured reservoirs

Science.gov (United States)

Kim, J.; Sonnenthal, E. L.; Rutqvist, J.

2011-12-01

Rigorous modeling of coupling between fluid, heat, and geomechanics (thermo-poro-mechanics), in fractured porous media is one of the important and difficult topics in geothermal reservoir simulation, because the physics are highly nonlinear and strongly coupled. Coupled fluid/heat flow and geomechanics are investigated using the multiple interacting continua (MINC) method as applied to naturally fractured media. In this study, we generalize constitutive relations for the isothermal elastic dual porosity model proposed by Berryman (2002) to those for the non-isothermal elastic/elastoplastic multiple porosity model, and derive the coupling coefficients of coupled fluid/heat flow and geomechanics and constraints of the coefficients. When the off-diagonal terms of the total compressibility matrix for the flow problem are zero, the upscaled drained bulk modulus for geomechanics becomes the harmonic average of drained bulk moduli of the multiple continua. In this case, the drained elastic/elastoplastic moduli for mechanics are determined by a combination of the drained moduli and volume fractions in multiple porosity materials. We also determine a relation between local strains of all multiple porosity materials in a gridblock and the global strain of the gridblock, from which we can track local and global elastic/plastic variables. For elastoplasticity, the return mapping is performed for all multiple porosity materials in the gridblock. For numerical implementation, we employ and extend the fixed-stress sequential method of the single porosity model to coupled fluid/heat flow and geomechanics in multiple porosity systems, because it provides numerical stability and high accuracy. This sequential scheme can be easily implemented by using a porosity function and its corresponding porosity correction, making use of the existing robust flow and geomechanics simulators. We implemented the proposed modeling and numerical algorithm to the reaction transport simulator

Incorporation of a health economic modelling tool into public health commissioning: Evidence use in a politicised context.

Science.gov (United States)

Sanders, Tom; Grove, Amy; Salway, Sarah; Hampshaw, Susan; Goyder, Elizabeth

2017-08-01

This paper explores how commissioners working in an English local government authority (LA) viewed a health economic decision tool for planning services in relation to diabetes. We conducted 15 interviews and 2 focus groups between July 2015 and February 2016, with commissioners (including public health managers, data analysts and council members). Two overlapping themes were identified explaining the obstacles and enablers of using such a tool in commissioning: a) evidence cultures, and b) system interdependency. The former highlighted the diverse evidence cultures present in the LA with politicians influenced by the 'soft' social care agendas affecting their local population and treating local opinion as evidence, whilst public health managers prioritised the scientific view of evidence informed by research. System interdependency further complicated the decision making process by recognizing interlinking with departments and other disease groups. To achieve legitimacy within the commissioning arena health economic modelling needs to function effectively in a highly politicised environment where decisions are made not only on the basis of research evidence, but on grounds of 'soft' data, personal opinion and intelligence. In this context decisions become politicised, with multiple opinions seeking a voice. The way that such decisions are negotiated and which ones establish authority is of importance. We analyse the data using Larson's (1990) discursive field concept to show how the tool becomes an object of research push and pull likely to be used instrumentally by stakeholders to advance specific agendas, not a means of informing complex decisions. In conclusion, LA decision making is underpinned by a transactional business ethic which is a further potential 'pull' mechanism for the incorporation of health economic modelling in local commissioning. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases.

Science.gov (United States)

Mezlini, Aziz M; Goldenberg, Anna

2017-10-01

Discovering genetic mechanisms driving complex diseases is a hard problem. Existing methods often lack power to identify the set of responsible genes. Protein-protein interaction networks have been shown to boost power when detecting gene-disease associations. We introduce a Bayesian framework, Conflux, to find disease associated genes from exome sequencing data using networks as a prior. There are two main advantages to using networks within a probabilistic graphical model. First, networks are noisy and incomplete, a substantial impediment to gene discovery. Incorporating networks into the structure of a probabilistic models for gene inference has less impact on the solution than relying on the noisy network structure directly. Second, using a Bayesian framework we can keep track of the uncertainty of each gene being associated with the phenotype rather than returning a fixed list of genes. We first show that using networks clearly improves gene detection compared to individual gene testing. We then show consistently improved performance of Conflux compared to the state-of-the-art diffusion network-based method Hotnet2 and a variety of other network and variant aggregation methods, using randomly generated and literature-reported gene sets. We test Hotnet2 and Conflux on several network configurations to reveal biases and patterns of false positives and false negatives in each case. Our experiments show that our novel Bayesian framework Conflux incorporates many of the advantages of the current state-of-the-art methods, while offering more flexibility and improved power in many gene-disease association scenarios.

NCI collaborates with Multiple Myeloma Research Foundation

Science.gov (United States)

The National Cancer Institute (NCI) announced a collaboration with the Multiple Myeloma Research Foundation (MMRF) to incorporate MMRF's wealth of genomic and clinical data on the disease into the NCI Genomic Data Commons (GDC), a publicly available datab

Model for incorporating fuel swelling and clad shrinkage effects in diffusion theory calculations (LWBR Development Program)

International Nuclear Information System (INIS)

Schick, W.C. Jr.; Milani, S.; Duncombe, E.

1980-03-01

A model has been devised for incorporating into the thermal feedback procedure of the PDQ few-group diffusion theory computer program the explicit calculation of depletion and temperature dependent fuel-rod shrinkage and swelling at each mesh point. The model determines the effect on reactivity of the change in hydrogen concentration caused by the variation in coolant channel area as the rods contract and expand. The calculation of fuel temperature, and hence of Doppler-broadened cross sections, is improved by correcting the heat transfer coefficient of the fuel-clad gap for the effects of clad creep, fuel densification and swelling, and release of fission-product gases into the gap. An approximate calculation of clad stress is also included in the model

Model selection with multiple regression on distance matrices leads to incorrect inferences.

Directory of Open Access Journals (Sweden)

Ryan P Franckowiak

Full Text Available In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC, its small-sample correction (AICc, and the Bayesian information criterion (BIC to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Multiple Temperature Model for Near Continuum Flows

International Nuclear Information System (INIS)

XU, Kun; Liu, Hongwei; Jiang, Jianzheng

2007-01-01

In the near continuum flow regime, the flow may have different translational temperatures in different directions. It is well known that for increasingly rarefied flow fields, the predictions from continuum formulation, such as the Navier-Stokes equations, lose accuracy. These inaccuracies may be partially due to the single temperature assumption in the Navier-Stokes equations. Here, based on the gas-kinetic Bhatnagar-Gross-Krook (BGK) equation, a multitranslational temperature model is proposed and used in the flow calculations. In order to fix all three translational temperatures, two constraints are additionally proposed to model the energy exchange in different directions. Based on the multiple temperature assumption, the Navier-Stokes relation between the stress and strain is replaced by the temperature relaxation term, and the Navier-Stokes assumption is recovered only in the limiting case when the flow is close to the equilibrium with the same temperature in different directions. In order to validate the current model, both the Couette and Poiseuille flows are studied in the transition flow regime

A toy MCT model for multiple glass transitions: Double swallow tail singularity

Energy Technology Data Exchange (ETDEWEB)

Ryzhov, V.N. [Institute for High Pressure Physics, Russian Academy of Sciences, Troitsk 142190, Moscow region (Russian Federation); Moscow Institute of Physics and Technology, 141700 Moscow (Russian Federation); Tareyeva, E.E. [Institute for High Pressure Physics, Russian Academy of Sciences, Troitsk 142190, Moscow region (Russian Federation)

2014-11-07

We propose a toy model to describe in the frame of Mode Coupling Theory multiple glass transitions. The model is based on the postulated simple form for static structure factor as a sum of two delta-functions. This form makes it possible to solve the MCT equations in almost analytical way. The phase diagram is governed by two swallow tails resulting from two A{sub 4} singularities and includes liquid–glass transition and multiple glasses. The diagram has much in common with those of binary and quasibinary systems. - Highlights: • A simple toy model is proposed for description of glass–glass transitions. • The static structure factor of the model has the form of a sum of delta-functions. • The phase diagram contains A{sub 4} bifurcation singularities and A{sub 3} end points. • The results can be applied for the qualitative description of quasibinary systems.

Validation and calibration of structural models that combine information from multiple sources.

Science.gov (United States)

Dahabreh, Issa J; Wong, John B; Trikalinos, Thomas A

2017-02-01

Mathematical models that attempt to capture structural relationships between their components and combine information from multiple sources are increasingly used in medicine. Areas covered: We provide an overview of methods for model validation and calibration and survey studies comparing alternative approaches. Expert commentary: Model validation entails a confrontation of models with data, background knowledge, and other models, and can inform judgments about model credibility. Calibration involves selecting parameter values to improve the agreement of model outputs with data. When the goal of modeling is quantitative inference on the effects of interventions or forecasting, calibration can be viewed as estimation. This view clarifies issues related to parameter identifiability and facilitates formal model validation and the examination of consistency among different sources of information. In contrast, when the goal of modeling is the generation of qualitative insights about the modeled phenomenon, calibration is a rather informal process for selecting inputs that result in model behavior that roughly reproduces select aspects of the modeled phenomenon and cannot be equated to an estimation procedure. Current empirical research on validation and calibration methods consists primarily of methodological appraisals or case-studies of alternative techniques and cannot address the numerous complex and multifaceted methodological decisions that modelers must make. Further research is needed on different approaches for developing and validating complex models that combine evidence from multiple sources.

A new general methodology for incorporating physico-chemical transformations into multi-phase wastewater treatment process models.

Science.gov (United States)

Lizarralde, I; Fernández-Arévalo, T; Brouckaert, C; Vanrolleghem, P; Ikumi, D S; Ekama, G A; Ayesa, E; Grau, P

2015-05-01

This paper introduces a new general methodology for incorporating physico-chemical and chemical transformations into multi-phase wastewater treatment process models in a systematic and rigorous way under a Plant-Wide modelling (PWM) framework. The methodology presented in this paper requires the selection of the relevant biochemical, chemical and physico-chemical transformations taking place and the definition of the mass transport for the co-existing phases. As an example a mathematical model has been constructed to describe a system for biological COD, nitrogen and phosphorus removal, liquid-gas transfer, precipitation processes, and chemical reactions. The capability of the model has been tested by comparing simulated and experimental results for a nutrient removal system with sludge digestion. Finally, a scenario analysis has been undertaken to show the potential of the obtained mathematical model to study phosphorus recovery. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiplicative point process as a model of trading activity

Science.gov (United States)

Gontis, V.; Kaulakys, B.

2004-11-01

Signals consisting of a sequence of pulses show that inherent origin of the 1/ f noise is a Brownian fluctuation of the average interevent time between subsequent pulses of the pulse sequence. In this paper, we generalize the model of interevent time to reproduce a variety of self-affine time series exhibiting power spectral density S( f) scaling as a power of the frequency f. Furthermore, we analyze the relation between the power-law correlations and the origin of the power-law probability distribution of the signal intensity. We introduce a stochastic multiplicative model for the time intervals between point events and analyze the statistical properties of the signal analytically and numerically. Such model system exhibits power-law spectral density S( f)∼1/ fβ for various values of β, including β= {1}/{2}, 1 and {3}/{2}. Explicit expressions for the power spectra in the low-frequency limit and for the distribution density of the interevent time are obtained. The counting statistics of the events is analyzed analytically and numerically, as well. The specific interest of our analysis is related with the financial markets, where long-range correlations of price fluctuations largely depend on the number of transactions. We analyze the spectral density and counting statistics of the number of transactions. The model reproduces spectral properties of the real markets and explains the mechanism of power-law distribution of trading activity. The study provides evidence that the statistical properties of the financial markets are enclosed in the statistics of the time interval between trades. A multiplicative point process serves as a consistent model generating this statistics.

Competitive advantage for multiple-memory strategies in an artificial market

Science.gov (United States)

Mitman, Kurt E.; Choe, Sehyo C.; Johnson, Neil F.

2005-05-01

We consider a simple binary market model containing N competitive agents. The novel feature of our model is that it incorporates the tendency shown by traders to look for patterns in past price movements over multiple time scales, i.e. multiple memory-lengths. In the regime where these memory-lengths are all small, the average winnings per agent exceed those obtained for either (1) a pure population where all agents have equal memory-length, or (2) a mixed population comprising sub-populations of equal-memory agents with each sub-population having a different memory-length. Agents who consistently play strategies of a given memory-length, are found to win more on average -- switching between strategies with different memory lengths incurs an effective penalty, while switching between strategies of equal memory does not. Agents employing short-memory strategies can outperform agents using long-memory strategies, even in the regime where an equal-memory system would have favored the use of long-memory strategies. Using the many-body 'Crowd-Anticrowd' theory, we obtain analytic expressions which are in good agreement with the observed numerical results. In the context of financial markets, our results suggest that multiple-memory agents have a better chance of identifying price patterns of unknown length and hence will typically have higher winnings.

Simulating the Incorporation of Geochemical Proxies into Scleractinian Coral Skeletons: Effects of Different Environmental and Biological Factors and Implications for Paleo-reconstruction

Science.gov (United States)

Guo, W.

2017-12-01

Chemical and isotopic compositions of scleractinian coral skeletons reflect the physicochemical condition of the seawater in which corals grow. This makes coral skeleton one of the best archives of ocean climate and biogeochemical changes. A number of coral-based geochemical proxies have been developed and applied to reconstruct past seawater conditions, such as temperature, pH, carbonate chemistry and nutrient concentrations. Detailed laboratory and field-based studies of these proxies, however, indicate interpretation of the geochemistry of coral skeletons is not straightforward, due to the presence of `vital effects' and the variations of empirical proxy calibrations among and within different species. This poses challenges for the broad application of many geochemical proxies in corals, and highlights the need to better understand the fundamental processes governing the incorporation of different proxies. Here I present a numerical model that simulates the incorporation of a suite of geochemical proxies into coral skeletons, including δ11B, Mg/Ca, Sr/Ca, U/Ca, B/Ca and Ba/Ca. This model, building on previous theoretical studies of coral calcification, combines our current understanding of coral calcification mechanism with experimental constraints on the isotope and element partition during carbonate precipitation. It enables quantitative evaluation of the effects of different environmental and biological factors on each proxy. Specifically, this model shows that (1) the incorporation of every proxy is affected by multiple seawater parameters (e.g. temperature, pH, DIC) as opposed to one single parameter, and (2) biological factors, particularly the interplay between enzymatic alkalinity pumping and the exchange of coral calcifying fluid with external seawater, also exert significant controls. Based on these findings, I propose an inverse method for simultaneously reconstructing multiple seawater physicochemical parameters, and compare the performance of this

Health care in small prisons: incorporating high-quality standards.

Science.gov (United States)

Rieder, Jean-Pierre; Casillas, Alejandra; Mary, Gérard; Secretan, Anne-Dominique; Gaspoz, Jean-Michel; Wolff, Hans

2013-01-01

In the past, health management in Geneva's six post-trial prisons had been variable and inconsistent. In 2008, the unit of penitentiary medicine of the Geneva University Hospitals was mandated to re-organize and provide health care at all six prison facilities. The specific aim of this paper is to outline the example as a practical solution to some of the common challenges in unifying the structure and process of health services across multiple small facilities, while meeting European prison health and local quality standards. Geneva's post-trial prisons are small and close to one another in geographical proximity - ideal conditions for the construction of a health mobile team (HMT). This multidisciplinary mobile team operated like a community ambulatory care model; it was progressively launched in all prison facilities in Geneva. The authors incorporated an implementation strategy where health providers partnered with prison and community stakeholders in the health delivery model's development and adaption process. The model's strategic initiatives are described along the following areas, in light of other international prison health activity and prior care models: access to a health care professional, equivalence of care, patient consent, confidentiality, humanitarian interventions, and professional competence and independence. From the perspective of the HMT members, the authors provide the "lessons learned" through this experience, especially to providers who are working on prison health services reform and coordination improvement. The paper particularly stresses the importance of partnering with community health stakeholders and prison staff, a key component to the approach.

A stochastic MILP energy planning model incorporating power market dynamics

International Nuclear Information System (INIS)

Koltsaklis, Nikolaos E.; Nazos, Konstantinos

2017-01-01

Highlights: •Stochastic MILP model for the optimal energy planning of a power system. •Power market dynamics (offers/bids) are incorporated in the proposed model. •Monte Carlo method for capturing the uncertainty of some key parameters. •Analytical supply cost composition per power producer and activity. •Clean dark and spark spreads are calculated for each power unit. -- Abstract: This paper presents an optimization-based methodological approach to address the problem of the optimal planning of a power system at an annual level in competitive and uncertain power markets. More specifically, a stochastic mixed integer linear programming model (MILP) has been developed, combining advanced optimization techniques with Monte Carlo method in order to deal with uncertainty issues. The main focus of the proposed framework is the dynamic formulation of the strategy followed by all market participants in volatile market conditions, as well as detailed economic assessment of the power system’s operation. The applicability of the proposed approach has been tested on a real case study of the interconnected Greek power system, quantifying in detail all the relevant technical and economic aspects of the system’s operation. The proposed work identifies in the form of probability distributions the optimal power generation mix, electricity trade at a regional level, carbon footprint, as well as detailed total supply cost composition, according to the assumed market structure. The paper demonstrates that the proposed optimization approach is able to provide important insights into the appropriate energy strategies designed by market participants, as well as on the strategic long-term decisions to be made by investors and/or policy makers at a national and/or regional level, underscoring potential risks and providing appropriate price signals on critical energy projects under real market operating conditions.

Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

Science.gov (United States)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2018-03-01

Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

Incorporation of the time aspect into the liability-threshold model for case-control-family data

DEFF Research Database (Denmark)

Cederkvist, Luise; Holst, Klaus K.; Andersen, Klaus K.

2017-01-01

to estimates that are difficult to interpret and are potentially biased. We incorporate the time aspect into the liability-threshold model for case-control-family data following the same approach that has been applied in the twin setting. Thus, the data are considered as arising from a competing risks setting...... approach using simulation studies and apply it in the analysis of two Danish register-based case-control-family studies: one on cancer diagnosed in childhood and adolescence, and one on early-onset breast cancer....

Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

Directory of Open Access Journals (Sweden)

Edy Legowo

2017-03-01

Full Text Available Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilitasi guru dapat menstimulasi multiple intelligences siswa. Evaluasi hasil belajar siswa dari pandangan penerapan teori multiple intelligences seharusnya dilakukan menggunakan authentic assessment dan portofolio yang lebih memfasilitasi para siswa mengungkapkan atau mengaktualisasikan hasil belajarnya melalui berbagai cara sesuai dengan kekuatan jenis inteligensinya.

A multiple objective mixed integer linear programming model for power generation expansion planning

Energy Technology Data Exchange (ETDEWEB)

Antunes, C. Henggeler; Martins, A. Gomes [INESC-Coimbra, Coimbra (Portugal); Universidade de Coimbra, Dept. de Engenharia Electrotecnica, Coimbra (Portugal); Brito, Isabel Sofia [Instituto Politecnico de Beja, Escola Superior de Tecnologia e Gestao, Beja (Portugal)

2004-03-01

Power generation expansion planning inherently involves multiple, conflicting and incommensurate objectives. Therefore, mathematical models become more realistic if distinct evaluation aspects, such as cost and environmental concerns, are explicitly considered as objective functions rather than being encompassed by a single economic indicator. With the aid of multiple objective models, decision makers may grasp the conflicting nature and the trade-offs among the different objectives in order to select satisfactory compromise solutions. This paper presents a multiple objective mixed integer linear programming model for power generation expansion planning that allows the consideration of modular expansion capacity values of supply-side options. This characteristic of the model avoids the well-known problem associated with continuous capacity values that usually have to be discretized in a post-processing phase without feedback on the nature and importance of the changes in the attributes of the obtained solutions. Demand-side management (DSM) is also considered an option in the planning process, assuming there is a sufficiently large portion of the market under franchise conditions. As DSM full costs are accounted in the model, including lost revenues, it is possible to perform an evaluation of the rate impact in order to further inform the decision process (Author)

Incorporating human-water dynamics in a hyper-resolution land surface model

Science.gov (United States)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in

Multiple equilibria in a stochastic implementation of DICE with abrupt climate change

International Nuclear Information System (INIS)

Lempert, Robert J.; Sanstad, Alan H.; Schlesinger, Michael E.

2006-01-01

Integrated assessment modeling of global climate change has focused primarily on gradually occurring changes in the climate system. However, atmospheric and earth scientists have become increasingly concerned that the climate system may be subject to abrupt, discontinuous changes on short time scales, and that anthropogenic greenhouse-gas emissions could trigger such shifts. Incorporating this type of climate dynamics into economic or integrated assessment models can result in model non-convexity and multiple equilibria, and thus complicate policy analysis relative to models with unique, globally optimal policies. Using a version of the Nordhaus DICE model amended in previous research by Keller et al. (2004) [Keller, Klaus, Benjamin M. Bolker, David F. Bradford, 2004. Uncertain climate thresholds and optimal economic growth. Journal of environmental economics and management 48 (1), 723-741], in conjunction with a stochastic global optimization algorithm, we generate 'level sets' of solutions, which helps identify multiple equilibria resulting from the potential abrupt cessation of the North Atlantic Thermohaline Circulation. We discuss the implications of this model geometry for formulating greenhouse-gas abatement policy under uncertainty and suggest that this general approach may be useful for addressing a wide range of model non-convexities including those related to endogenous technological change

Multiplicative Attribute Graph Model of Real-World Networks

Energy Technology Data Exchange (ETDEWEB)

Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

2010-10-20

Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

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).

Internal cycle modeling and environmental assessment of multiple cycle consumer products

International Nuclear Information System (INIS)

Tsiliyannis, C.A.

2012-01-01

Highlights: ► Dynamic flow models are presented for remanufactured, reused or recycled products. ► Early loss and stochastic return are included for fast and slow cycling products. ► The reuse-to-input flow ratio (Internal Cycle Factor, ICF) is determined. ► The cycle rate, which is increasing with the ICF, monitors eco-performance. ► Early internal cycle losses diminish the ICF, the cycle rate and performance. - Abstract: Dynamic annual flow models incorporating consumer discard and usage loss and featuring deterministic and stochastic end-of-cycle (EOC) return by the consumer are developed for reused or remanufactured products (multiple cycle products, MCPs), including fast and slow cycling, short and long-lived products. It is shown that internal flows (reuse and overall consumption) increase proportionally to the dimensionless internal cycle factor (ICF) which is related to environmental impact reduction factors. The combined reuse/recycle (or cycle) rate is shown capable for shortcut, albeit effective, monitoring of environmental performance in terms of waste production, virgin material extraction and manufacturing impacts of all MCPs, a task, which physical variables (lifetime, cycling frequency, mean or total number of return trips) and conventional rates, via which environmental policy has been officially implemented (e.g. recycling rate) cannot accomplish. The cycle rate is shown to be an increasing (hyperbolic) function of ICF. The impact of the stochastic EOC return characteristics on total reuse and consumption flows, as well as on eco-performance, is assessed: symmetric EOC return has a small, positive effect on performance compared to deterministic, while early shifted EOC return is more beneficial. In order to be efficient, environmental policy should set higher minimum reuse targets for higher trippage MCPs. The results may serve for monitoring, flow accounting and comparative eco-assessment of MCPs. They may be useful in identifying

Constraining Distributed Catchment Models by Incorporating Perceptual Understanding of Spatial Hydrologic Behaviour

Science.gov (United States)

Hutton, Christopher; Wagener, Thorsten; Freer, Jim; Han, Dawei

2016-04-01

Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models tend to contain a large number of poorly defined and spatially varying model parameters which are therefore computationally expensive to calibrate. Insufficient data can result in model parameter and structural equifinality, particularly when calibration is reliant on catchment outlet discharge behaviour alone. Evaluating spatial patterns of internal hydrological behaviour has the potential to reveal simulations that, whilst consistent with measured outlet discharge, are qualitatively dissimilar to our perceptual understanding of how the system should behave. We argue that such understanding, which may be derived from stakeholder knowledge across different catchments for certain process dynamics, is a valuable source of information to help reject non-behavioural models, and therefore identify feasible model structures and parameters. The challenge, however, is to convert different sources of often qualitative and/or semi-qualitative information into robust quantitative constraints of model states and fluxes, and combine these sources of information together to reject models within an efficient calibration framework. Here we present the development of a framework to incorporate different sources of data to efficiently calibrate distributed catchment models. For each source of information, an interval or inequality is used to define the behaviour of the catchment system. These intervals are then combined to produce a hyper-volume in state space, which is used to identify behavioural models. We apply the methodology to calibrate the Penn State Integrated Hydrological Model (PIHM) at the Wye catchment, Plynlimon, UK. Outlet discharge behaviour is successfully simulated when perceptual understanding of relative groundwater levels between lowland peat, upland peat

Multiple-collision model for pion production in relativistic nucleus-nucleus collisions

International Nuclear Information System (INIS)

Vary, J.P.

1978-01-01

A simple model for pion production in relativistic heavy-ion collisions is developed based on nucleon-nucleon data, nuclear density distribution, and the assumption of straight-line trajectories. Multiplicity distributions for total pion production and for negative-pion production are predicted for 40 Ar incident on a Pb 3 O 4 target at 1.8 GeV/nucleon. Production through intermediate baryon resonances reduces the high-multiplicity region but insufficiently to yield agreement with data. This implies the need for a coherent production mechanism

Incorporating Multiple Energy Relay Dyes in Liquid Dye-Sensitized Solar Cells

KAUST Repository

Yum, Jun-Ho

2011-01-05

Panchromatic response is essential to increase the light-harvesting efficiency in solar conversion systems. Herein we show increased light harvesting from using multiple energy relay dyes inside dye-sensitized solar cells. Additional photoresponse from 400-590 nm matching the optical window of the zinc phthalocyanine sensitizer was observed due to Förster resonance energy transfer (FRET) from the two energy relay dyes to the sensitizing dye. The complementary absorption spectra of the energy relay dyes and high excitation transfer efficiencies result in a 35% increase in photovoltaic performance. © 2011 Wiley-VCH Verlag GmbH& Co. KGaA.

Problem solving based learning model with multiple representations to improve student's mental modelling ability on physics

Science.gov (United States)

Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran

2017-08-01

Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7Mental Modelling Ability (M-MMA) for 3Mental Modelling Ability (L-MMA) for 0 ≤ x ≤ 3 score. The result shows that problem solving based learning model with multiple representations approach can be an alternative to be applied in improving students' MMA.

Exploring the Use of Multiple Analogical Models when Teaching and Learning Chemical Equilibrium

Science.gov (United States)

Harrison, Allan G.; De Jong, Onno

2005-01-01

This study describes the multiple analogical models used to introduce and teach Grade 12 chemical equilibrium. We examine the teacher's reasons for using models, explain each model's development during the lessons, and analyze the understandings students derived from the models. A case study approach was used and the data were drawn from the…

The Student's Dilemma, Liver Edition: Incorporating the Sonographer's Language into Clinical Anatomy Education

Science.gov (United States)

Hall, M. Kennedy; Mirjalili, S. Ali; Moore, Christopher L.; Rizzolo, Lawrence J.

2015-01-01

Anatomy students are often confused by multiple names ascribed to the same structure by different clinical disciplines. Increasingly, sonography is being incorporated into clinical anatomical education, but ultrasound textbooks often use names unfamiliar to the anatomist. Confusion is worsened when ultrasound names ascribed to the same structure…

On the identification of multiple space dependent ionic parameters in cardiac electrophysiology modelling

Science.gov (United States)

Abidi, Yassine; Bellassoued, Mourad; Mahjoub, Moncef; Zemzemi, Nejib

2018-03-01

In this paper, we consider the inverse problem of space dependent multiple ionic parameters identification in cardiac electrophysiology modelling from a set of observations. We use the monodomain system known as a state-of-the-art model in cardiac electrophysiology and we consider a general Hodgkin-Huxley formalism to describe the ionic exchanges at the microscopic level. This formalism covers many physiological transmembrane potential models including those in cardiac electrophysiology. Our main result is the proof of the uniqueness and a Lipschitz stability estimate of ion channels conductance parameters based on some observations on an arbitrary subdomain. The key idea is a Carleman estimate for a parabolic operator with multiple coefficients and an ordinary differential equation system.

Learned helplessness, discouraged workers, and multiple unemployment equilibria in a search model

OpenAIRE

Bjørnstad, Roger

2001-01-01

Abstract: Unemployment varies strongly between countries with comparable economic structure. Some economists have tried to explain these differences with institutional differences in the labour market. Instead, this paper focuses on a model with multiple equilibria so that the same socioeconomic structure can give rise to different levels of unemployment. Unemployed workers' search efficiency are modelled within an equilibrium search model and lay behind these results. In the model learned...

A model for determination of human foetus irradiation during intrauterine development when the mother incorporates iodine 131

International Nuclear Information System (INIS)

Vasilev, V.; Doncheva, B.

1989-01-01

A model is presented for irradiation calculation of human foetus during weeks 8-15 of the intrauterine development, when the mother chronically incorporates iodine 131. This period is critical for the nervous system of the foetus. Compared to some other author's models, the method proposed eliminates some uncertainties and takes into account the changes in the activity of mother's thyroid in time. The model is built on the base of data from 131 I-kinetics of pregnant women and experimental mice. A formula is proposed for total foetus irradiation calculation including: the internal γ and β irradiation; the external γ and β irradiation from the mother as a whole; and the external γ irradiation from the mother's thyroid

Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

OpenAIRE

Edy Legowo

2017-01-01

Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilita...

Spinal motor control system incorporates an internal model of limb dynamics.

Science.gov (United States)

Shimansky, Y P

2000-10-01

The existence and utilization of an internal representation of the controlled object is one of the most important features of the functioning of neural motor control systems. This study demonstrates that this property already exists at the level of the spinal motor control system (SMCS), which is capable of generating motor patterns for reflex rhythmic movements, such as locomotion and scratching, without the aid of the peripheral afferent feedback, but substantially modifies the generated activity in response to peripheral afferent stimuli. The SMCS is presented as an optimal control system whose optimality requires that it incorporate an internal model (IM) of the controlled object's dynamics. A novel functional mechanism for the integration of peripheral sensory signals with the corresponding predictive output from the IM, the summation of information precision (SIP) is proposed. In contrast to other models in which the correction of the internal representation of the controlled object's state is based on the calculation of a mismatch between the internal and external information sources, the SIP mechanism merges the information from these sources in order to optimize the precision of the controlled object's state estimate. It is demonstrated, based on scratching in decerebrate cats as an example of the spinal control of goal-directed movements, that the results of computer modeling agree with the experimental observations related to the SMCS's reactions to phasic and tonic peripheral afferent stimuli. It is also shown that the functional requirements imposed by the mathematical model of the SMCS comply with the current knowledge about the related properties of spinal neuronal circuitry. The crucial role of the spinal presynaptic inhibition mechanism in the neuronal implementation of SIP is elucidated. Important differences between the IM and a state predictor employed for compensating for a neural reflex time delay are discussed.

Testing effect of a drug using multiple nested models for the dose–response

DEFF Research Database (Denmark)

Baayen, C.; Hougaard, P.; Pipper, C. B.

2015-01-01

of the assumed dose–response model. Bretz et al. (2005, Biometrics 61, 738–748) suggested a combined approach, which selects one or more suitable models from a set of candidate models using a multiple comparison procedure. The method initially requires a priori estimates of any non-linear parameters...

A new spatial multiple discrete-continuous modeling approach to land use change analysis.

Science.gov (United States)

2013-09-01

This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

Using hidden Markov models to align multiple sequences.

Science.gov (United States)

Mount, David W

2009-07-01

A hidden Markov model (HMM) is a probabilistic model of a multiple sequence alignment (msa) of proteins. In the model, each column of symbols in the alignment is represented by a frequency distribution of the symbols (called a "state"), and insertions and deletions are represented by other states. One moves through the model along a particular path from state to state in a Markov chain (i.e., random choice of next move), trying to match a given sequence. The next matching symbol is chosen from each state, recording its probability (frequency) and also the probability of going to that state from a previous one (the transition probability). State and transition probabilities are multiplied to obtain a probability of the given sequence. The hidden nature of the HMM is due to the lack of information about the value of a specific state, which is instead represented by a probability distribution over all possible values. This article discusses the advantages and disadvantages of HMMs in msa and presents algorithms for calculating an HMM and the conditions for producing the best HMM.

Hair length, facial attractiveness, personality attribution: A multiple fitness model of hairdressing

OpenAIRE

Bereczkei, Tamas; Mesko, Norbert

2007-01-01

Multiple Fitness Model states that attractiveness varies across multiple dimensions, with each feature representing a different aspect of mate value. In the present study, male raters judged the attractiveness of young females with neotenous and mature facial features, with various hair lengths. Results revealed that the physical appearance of long-haired women was rated high, regardless of their facial attractiveness being valued high or low. Women rated as most attractive were those whose f...

Fitting PAC spectra with stochastic models: PolyPacFit

Energy Technology Data Exchange (ETDEWEB)

Zacate, M. O., E-mail: zacatem1@nku.edu [Northern Kentucky University, Department of Physics and Geology (United States); Evenson, W. E. [Utah Valley University, College of Science and Health (United States); Newhouse, R.; Collins, G. S. [Washington State University, Department of Physics and Astronomy (United States)

2010-04-15

PolyPacFit is an advanced fitting program for time-differential perturbed angular correlation (PAC) spectroscopy. It incorporates stochastic models and provides robust options for customization of fits. Notable features of the program include platform independence and support for (1) fits to stochastic models of hyperfine interactions, (2) user-defined constraints among model parameters, (3) fits to multiple spectra simultaneously, and (4) any spin nuclear probe.

Steam consumption minimization model in a multiple evaporation effect in a sugar plant

International Nuclear Information System (INIS)

Villada, Fernando; Valencia, Jaime A; Moreno, German; Murillo, J. Joaquin

1992-01-01

In this work, a mathematical model to minimize the steam consumption in a multiple effect evaporation system is shown. The model is based in the dynamic programming technique and the results are tested in a Colombian sugar mill

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

Directory of Open Access Journals (Sweden)

Diego Fernandez Slezak

2018-03-01

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

Eikonal multiple scattering model within the framework of Feynman's positron theory

International Nuclear Information System (INIS)

Tekou, A.

1986-07-01

The Bethe Salpeter equation for nucleon-nucleon, nucleon-nucleus and nucleus-nucleus scattering is eikonalized. Multiple scattering series is obtained. Contributions of three body interations are included. The model presented below may be used to investigate atomic collisions. (author)

Effects of the 5E Instructional Model Incorporated with Multiple Levels of Representations on Thai Students with Different Levels of Cognitive Development

Science.gov (United States)

Wichaidit, Patcharee Rompayom; Wichaidit, Sittichai

2016-01-01

Learning chemistry may be difficult for students for several reasons, such as the abstract nature of many chemistry concepts and the fact that students may view chemistry as irrelevant to their everyday lives. Teaching chemistry in familiar contexts and the use of multiple representations are seen as effective approaches for enhancing students'…

A multiple relevance feedback strategy with positive and negative models.

Directory of Open Access Journals (Sweden)

Yunlong Ma

Full Text Available A commonly used strategy to improve search accuracy is through feedback techniques. Most existing work on feedback relies on positive information, and has been extensively studied in information retrieval. However, when a query topic is difficult and the results from the first-pass retrieval are very poor, it is impossible to extract enough useful terms from a few positive documents. Therefore, the positive feedback strategy is incapable to improve retrieval in this situation. Contrarily, there is a relatively large number of negative documents in the top of the result list, and it has been confirmed that negative feedback strategy is an important and useful way for adapting this scenario by several recent studies. In this paper, we consider a scenario when the search results are so poor that there are at most three relevant documents in the top twenty documents. Then, we conduct a novel study of multiple strategies for relevance feedback using both positive and negative examples from the first-pass retrieval to improve retrieval accuracy for such difficult queries. Experimental results on these TREC collections show that the proposed language model based multiple model feedback method which is generally more effective than both the baseline method and the methods using only positive or negative model.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

2017-01-01

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza

2017-02-08

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Shared Authentic Leadership in Research Teams: Testing a Multiple Mediation Model

NARCIS (Netherlands)

Günter, Hannes; Gardner, William L.; Davis McCauley, Kelly; Randolph-Seng, Brandon; P. Prahbu, Veena

2017-01-01

Research teams face complex leadership and coordination challenges. We propose shared authentic leadership (SAL) as a timely approach to addressing these challenges. Drawing from authentic and functional leadership theories, we posit a multiple mediation model that suggests three mechanisms whereby

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

Science.gov (United States)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

Incorporating teleconnection information into reservoir operating policies using Stochastic Dynamic Programming and a Hidden Markov Model

Science.gov (United States)

Turner, Sean; Galelli, Stefano; Wilcox, Karen

2015-04-01

Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating

Incorporating Speech Recognition into a Natural User Interface

Science.gov (United States)

Chapa, Nicholas

2017-01-01

The Augmented/ Virtual Reality (AVR) Lab has been working to study the applicability of recent virtual and augmented reality hardware and software to KSC operations. This includes the Oculus Rift, HTC Vive, Microsoft HoloLens, and Unity game engine. My project in this lab is to integrate voice recognition and voice commands into an easy to modify system that can be added to an existing portion of a Natural User Interface (NUI). A NUI is an intuitive and simple to use interface incorporating visual, touch, and speech recognition. The inclusion of speech recognition capability will allow users to perform actions or make inquiries using only their voice. The simplicity of needing only to speak to control an on-screen object or enact some digital action means that any user can quickly become accustomed to using this system. Multiple programs were tested for use in a speech command and recognition system. Sphinx4 translates speech to text using a Hidden Markov Model (HMM) based Language Model, an Acoustic Model, and a word Dictionary running on Java. PocketSphinx had similar functionality to Sphinx4 but instead ran on C. However, neither of these programs were ideal as building a Java or C wrapper slowed performance. The most ideal speech recognition system tested was the Unity Engine Grammar Recognizer. A Context Free Grammar (CFG) structure is written in an XML file to specify the structure of phrases and words that will be recognized by Unity Grammar Recognizer. Using Speech Recognition Grammar Specification (SRGS) 1.0 makes modifying the recognized combinations of words and phrases very simple and quick to do. With SRGS 1.0, semantic information can also be added to the XML file, which allows for even more control over how spoken words and phrases are interpreted by Unity. Additionally, using a CFG with SRGS 1.0 produces a Finite State Machine (FSM) functionality limiting the potential for incorrectly heard words or phrases. The purpose of my project was to

Incorporation of defects into the central atoms model of a metallic glass

International Nuclear Information System (INIS)

Lass, Eric A.; Zhu Aiwu; Shiflet, G.J.; Joseph Poon, S.

2011-01-01

The central atoms model (CAM) of a metallic glass is extended to incorporate thermodynamically stable defects, similar to vacancies in a crystalline solid, within the amorphous structure. A bond deficiency (BD), which is the proposed defect present in all metallic glasses, is introduced into the CAM equations. Like vacancies in a crystalline solid, BDs are thermodynamically stable entities because of the increase in entropy associated with their creation, and there is an equilibrium concentration present in the glassy phase. When applied to Cu-Zr and Ni-Zr binary metallic glasses, the concentration of thermally induced BDs surrounding Zr atoms reaches a relatively constant value at the glass transition temperature, regardless of composition within a given glass system. Using this 'critical' defect concentration, the predicted temperatures at which the glass transition is expected to occur are in good agreement with the experimentally determined glass transition temperatures for both alloy systems.

Radiometric study of the incorporation of labelled precursors of DNA, RNA and proteins in cell cultures inoculated with Herpes simplex virus

International Nuclear Information System (INIS)

Dundarov, S.; Todorov, S.; Kavaklova, L.; Tsilka, E.; Rangelova, S.; Dundarova, D.

1976-01-01

Results are reported of a comparative investigation of tritium-labelled thymidine, uridine and leucine incorporation in cells inoculated with HSV-1 and HSV-2. There were no essential differences in the dynamics of the biosynthesis processes in either type of herpes viruses. Viral infection led to a marked activation of DNA synthesis and progressive inhibition of overall RNA synthesis. The rate of labelled amino-acid incorporation remained almost unchanged. There was a gradual increase in 3 H-thymidine incorporation, reaching a minimum by the 12th-16th hour and a rapid decrese thereafter. After the 12th hour part of the thymidine already incorporated in DNA (the thymidine pool) starts leaving the cells as a result of increased cell membrane permeability. The rate of changes in the biosynthesis processes in HSV-inoculated cells depends on infection multiplicity. Even in high inoculation multiplicity the blockade of cell biosynthesis is incomplete which furnishes a better opportunity for HSV reproduction. (author)

Incorporating plant fossil data into species distribution models is not straightforward: Pitfalls and possible solutions

Science.gov (United States)

Moreno-Amat, Elena; Rubiales, Juan Manuel; Morales-Molino, César; García-Amorena, Ignacio

2017-08-01

The increasing development of species distribution models (SDMs) using palaeodata has created new prospects to address questions of evolution, ecology and biogeography from wider perspectives. Palaeobotanical data provide information on the past distribution of taxa at a given time and place and its incorporation on modelling has contributed to advancing the SDM field. This has allowed, for example, to calibrate models under past climate conditions or to validate projected models calibrated on current species distributions. However, these data also bear certain shortcomings when used in SDMs that may hinder the resulting ecological outcomes and eventually lead to misleading conclusions. Palaeodata may not be equivalent to present data, but instead frequently exhibit limitations and biases regarding species representation, taxonomy and chronological control, and their inclusion in SDMs should be carefully assessed. The limitations of palaeobotanical data applied to SDM studies are infrequently discussed and often neglected in the modelling literature; thus, we argue for the more careful selection and control of these data. We encourage authors to use palaeobotanical data in their SDMs studies and for doing so, we propose some recommendations to improve the robustness, reliability and significance of palaeo-SDM analyses.

Affordances perspective and grammaticalization: Incorporation of language, environment and users in the model of semantic paths

Directory of Open Access Journals (Sweden)

Alexander Andrason

2015-12-01

Full Text Available The present paper demonstrates that insights from the affordances perspective can contribute to developing a more comprehensive model of grammaticalization. The authors argue that the grammaticalization process is afforded differently depending on the values of three contributing parameters: the factor (schematized as a qualitative-quantitative map or a wave of a gram, environment (understood as the structure of the stream along which the gram travels, and actor (narrowed to certain cognitive-epistemological capacities of the users, in particular to the fact of being a native speaker. By relating grammaticalization to these three parameters and by connecting it to the theory of optimization, the proposed model offers a better approximation to realistic cases of grammaticalization: The actor and environment are overtly incorporated into the model and divergences from canonical grammaticalization paths are both tolerated and explicable.

Laplace transform analysis of a multiplicative asset transfer model

Science.gov (United States)

Sokolov, Andrey; Melatos, Andrew; Kieu, Tien

2010-07-01

We analyze a simple asset transfer model in which the transfer amount is a fixed fraction f of the giver’s wealth. The model is analyzed in a new way by Laplace transforming the master equation, solving it analytically and numerically for the steady-state distribution, and exploring the solutions for various values of f∈(0,1). The Laplace transform analysis is superior to agent-based simulations as it does not depend on the number of agents, enabling us to study entropy and inequality in regimes that are costly to address with simulations. We demonstrate that Boltzmann entropy is not a suitable (e.g. non-monotonic) measure of disorder in a multiplicative asset transfer system and suggest an asymmetric stochastic process that is equivalent to the asset transfer model.

Modelling of diffuse solar fraction with multiple predictors

Energy Technology Data Exchange (ETDEWEB)

Ridley, Barbara; Boland, John [Centre for Industrial and Applied Mathematics, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, SA 5095 (Australia); Lauret, Philippe [Laboratoire de Physique du Batiment et des Systemes, University of La Reunion, Reunion (France)

2010-02-15

For some locations both global and diffuse solar radiation are measured. However, for many locations, only global radiation is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from direct on some other plane using trigonometry, we need to have diffuse radiation on the horizontal plane available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia. Boland et al. developed a validated model for Australian conditions. Boland et al. detailed our recent advances in developing the theoretical framework for the use of the logistic function instead of piecewise linear or simple nonlinear functions and was the first step in identifying the means for developing a generic model for estimating diffuse from global and other predictors. We have developed a multiple predictor model, which is much simpler than previous models, and uses hourly clearness index, daily clearness index, solar altitude, apparent solar time and a measure of persistence of global radiation level as predictors. This model performs marginally better than currently used models for locations in the Northern Hemisphere and substantially better for Southern Hemisphere locations. We suggest it can be used as a universal model. (author)

Assessments of Future Maize Yield Potential Changes in the Korean Peninsula Using Multiple Crop Models

Science.gov (United States)

Kim, S. H.; Lim, C. H.; Kim, J.; Lee, W. K.; Kafatos, M.

2016-12-01

The Korean Peninsula has unique agricultural environment due to the differences of political and socio-economical system between Republic of Korea (SK, hereafter) and Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering lack of food supplies caused by natural disasters, land degradation and political failure. The neighboring developed country SK has better agricultural system but very low food self-sufficiency rate. Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore, evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we utilized multiple process-based crop models, having ability of regional scale assessment, to evaluate maize Yp and assess the model uncertainties -EPIC, GEPIC, DSSAT, and APSIM model that has capability of regional scale expansion (apsimRegions). First we evaluated each crop model for 3 years from 2012 to 2014 using reanalysis data (RDAPS; Regional Data Assimilation and Prediction System produced by Korea Meteorological Agency) and observed yield data. Each model performances were compared over the different regions in the Korean Peninsula having different local climate characteristics. To quantify of the major influence of at each climate variables, we also conducted sensitivity test using 20 years of climatology in historical period from 1981 to 2000. Lastly, the multi-crop model ensemble analysis was performed for future period from 2031 to 2050. The required weather variables projected for mid-century were employed from COordinated Regional climate Downscaling EXperiment (CORDEX) East Asia. The high-resolution climate data were obtained from multiple regional climate models (RCM) driven by multiple climate scenarios projected from multiple global climate models (GCMs) in conjunction with multiple greenhouse gas

The biokinetic of incorporates radionuclides; Die Biokinetik von inkorporierten Radionukliden

Energy Technology Data Exchange (ETDEWEB)

Breustedt, Bastian [Karlsruher Institut fuer Technologie (KIT), Eggenstein-Leopoldshafen (Germany). Inst. fuer Strahlenforschung; Giussani, Augusto [Bundesamt fuer Strahlenschutz, Oberschleissheim (Germany). Arbeitsgruppe ' ' Externe und interne Dosimetrie, Biokinetik' '

2017-08-01

Incorporated radionuclides from nuclear accidents, fission product releases or nuclear medical administration are distributed in the human body in organs and tissue, absorbed 9or excreted. The interpretation of incorporation monitoring results and the estimation of the internal doses that cannot be measured directly need mathematical methods and the formulation of biokinetic models.

An explicit statistical model of learning lexical segmentation using multiple cues

NARCIS (Netherlands)

Çöltekin, Ça ̆grı; Nerbonne, John; Lenci, Alessandro; Padró, Muntsa; Poibeau, Thierry; Villavicencio, Aline

2014-01-01

This paper presents an unsupervised and incremental model of learning segmentation that combines multiple cues whose use by children and adults were attested by experimental studies. The cues we exploit in this study are predictability statistics, phonotactics, lexical stress and partial lexical

Multiple imputation to account for measurement error in marginal structural models

Science.gov (United States)

Edwards, Jessie K.; Cole, Stephen R.; Westreich, Daniel; Crane, Heidi; Eron, Joseph J.; Mathews, W. Christopher; Moore, Richard; Boswell, Stephen L.; Lesko, Catherine R.; Mugavero, Michael J.

2015-01-01

Background Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and non-differential measurement error in a marginal structural model. Methods We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. Results In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality [hazard ratio (HR): 1.2 (95% CI: 0.6, 2.3)]. The HR for current smoking and therapy (0.4 (95% CI: 0.2, 0.7)) was similar to the HR for no smoking and therapy (0.4; 95% CI: 0.2, 0.6). Conclusions Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies. PMID:26214338

Multiple Imputation to Account for Measurement Error in Marginal Structural Models.

Science.gov (United States)

Edwards, Jessie K; Cole, Stephen R; Westreich, Daniel; Crane, Heidi; Eron, Joseph J; Mathews, W Christopher; Moore, Richard; Boswell, Stephen L; Lesko, Catherine R; Mugavero, Michael J

2015-09-01

Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and nondifferential measurement error in a marginal structural model. We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3,686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality (hazard ratio [HR]: 1.2 [95% confidence interval [CI] = 0.6, 2.3]). The HR for current smoking and therapy [0.4 (95% CI = 0.2, 0.7)] was similar to the HR for no smoking and therapy (0.4; 95% CI = 0.2, 0.6). Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies.

A minimal unified model of disease trajectories captures hallmarks of multiple sclerosis

KAUST Repository

Kannan, Venkateshan; Kiani, Narsis A.; Piehl, Fredrik; Tegner, Jesper

2017-01-01

Multiple Sclerosis (MS) is an autoimmune disease targeting the central nervous system (CNS) causing demyelination and neurodegeneration leading to accumulation of neurological disability. Here we present a minimal, computational model involving

The Color Mutation Model for soft interaction

International Nuclear Information System (INIS)

Hwa, R.C.

1998-01-01

A comprehensive model for soft interaction is presented. It overcomes all the shortcomings of the existing models - in particular, the failure of Fritiof and Venus models in predicting the correct multiplicity fluctuations as observed in the intermittency data. The Color Mutation Model incorporates all the main features of hadronic interaction: eikonal formalism, parton model, evolution in color space according to QCD, branching of color neutral clusters, contraction due to confinement forces, dynamical self-similarity, resonance production, and power-law behavior of factorial moments. (author)

Adaptation of Boynton's mathematical model to hydrogen isotope separation column by cryogenic distillation

International Nuclear Information System (INIS)

Kinoshita, Masahiro; Naruse, Yuji

1981-08-01

Boynton's mathematical simulation procedure for multi-component distillation calculations has the advantage that the Jacobian matrix is calculated analytically. The purpose of the present study is to adapt this procedure to hydrogen isotope separation columns by cryogenic distillation. The Boynton's model is modified so that the model can incorporate decay heat of tritium, nonideality of the hydrogen isotope solutions, multiple feeds and multiple sidestreams. Basic equations are derived and the mathematical simulation procedure is briefly explained. (author)

An extension of the Néel-Brown model for systems with multiple switching pathways

Energy Technology Data Exchange (ETDEWEB)

Roy, Arnab; Kumar, P.S. Anil, E-mail: anil@physics.iisc.ernet.in

2017-02-15

TheNéel-Brown model is the most widely accepted model for the description of magnetization reversal by thermal excitation. This model predicts a decreasing average switching field and an increasing width ΔH of switching field distribution as the temperature is increased, and has been found to hold good on several occasions. However, for a few classes of systems, the temperature dependence of ΔH shows the opposite trend, and so far no satisfactory explanation exists. We present here an experimental study of switching field statistics of permalloy (Ni{sub 80}Fe{sub 20}) thin films on Si(100) grown by pulsed laser ablation. It was seen that the sample deviates from the Neel-Brown behavior in the manner described above. We performed calculations based on a natural extension of the Néel-Brown model, which incorporated multiple reversal pathways characterized by a Gaussian distribution of coercive fields. Calculations based on this model for different values of the width parameter σ{sub HSW} show two distinct kinds of behavior. At low values of σ{sub HSW}, the total width ΔH is limited by thermal broadening according to the traditional Neel-Brown expression. This regime is characterized by an increasing ΔH with temperature. For high σ{sub HSW}, the broadening is dominated by σ{sub HSW}, which masks thermal broadening. In this regime, ΔH decreases with increasing temperature. Whereas the experimentally observed temperature dependence of the average switching field was found to be in good agreement with this model, qualitative agreement with regard to the temperature dependence of ΔH could be observed only for relaxation times lower than ~10{sup −40} s, which is much smaller than Néel-Brown relaxation times (10{sup −9}–10{sup −19} s) usually encountered in the literature. - Highlights: • The Néel-Brown model for magnetization reversal over an energy barrier due to thermal excitation is a widely accepted mechanism for magnetization reversal, and has

Multiple-point statistical simulation for hydrogeological models: 3-D training image development and conditioning strategies

Directory of Open Access Journals (Sweden)

A.-S. Høyer

2017-12-01

Full Text Available Most studies on the application of geostatistical simulations based on multiple-point statistics (MPS to hydrogeological modelling focus on relatively fine-scale models and concentrate on the estimation of facies-level structural uncertainty. Much less attention is paid to the use of input data and optimal construction of training images. For instance, even though the training image should capture a set of spatial geological characteristics to guide the simulations, the majority of the research still relies on 2-D or quasi-3-D training images. In the present study, we demonstrate a novel strategy for 3-D MPS modelling characterized by (i realistic 3-D training images and (ii an effective workflow for incorporating a diverse group of geological and geophysical data sets. The study covers an area of 2810 km2 in the southern part of Denmark. MPS simulations are performed on a subset of the geological succession (the lower to middle Miocene sediments which is characterized by relatively uniform structures and dominated by sand and clay. The simulated domain is large and each of the geostatistical realizations contains approximately 45 million voxels with size 100 m  ×  100 m  ×  5 m. Data used for the modelling include water well logs, high-resolution seismic data, and a previously published 3-D geological model. We apply a series of different strategies for the simulations based on data quality, and develop a novel method to effectively create observed spatial trends. The training image is constructed as a relatively small 3-D voxel model covering an area of 90 km2. We use an iterative training image development strategy and find that even slight modifications in the training image create significant changes in simulations. Thus, this study shows how to include both the geological environment and the type and quality of input information in order to achieve optimal results from MPS modelling. We present a practical

Modeling single versus multiple systems in implicit and explicit memory.

Science.gov (United States)

Starns, Jeffrey J; Ratcliff, Roger; McKoon, Gail

2012-04-01

It is currently controversial whether priming on implicit tasks and discrimination on explicit recognition tests are supported by a single memory system or by multiple, independent systems. In a Psychological Review article, Berry and colleagues used mathematical modeling to address this question and provide compelling evidence against the independent-systems approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Incorporation of an organic MAGIC (Model of Acidification of Groundwater in Catchments) and testing of the revised model using independent data sources]. Progress report, March 16, 1992--September 15, 1992

Energy Technology Data Exchange (ETDEWEB)

Sullivan, T.J.

1992-09-01

A project was initiated in March, 1992 to (1) incorporate a rigorous organic acid representation, based on empirical data and geochemical considerations, into the MAGIC model of acidification response, and (2) test the revised model using three sets of independent data. After six months of performance, the project is on schedule and the majority of the tasks outlined for Year 1 have been successfully completed. Major accomplishments to data include development of the organic acid modeling approach, using data from the Adirondack Lakes Survey Corporation (ALSC), and coupling the organic acid model with MAGIC for chemical hindcast comparisons. The incorporation of an organic acid representation into MAGIC can account for much of the discrepancy earlier observed between MAGIC hindcasts and paleolimnological reconstructions of preindustrial pH and alkalinity for 33 statistically-selected Adirondack lakes. Additional work is on-going for model calibration and testing with data from two whole-catchment artificial acidification projects. Results obtained thus far are being prepared as manuscripts for submission to the peer-reviewed scientific literature.

On the practical modeling of conceptual overlap among multiple facets in ontology domain concepts (Mini-thesis)

OpenAIRE

Rodriguez-Castro, Benedicto; Glaser, Hugh; Carr, Leslie

2007-01-01

This report presents a study on the practical modelling of the conceptual overlap that might exist among the multiple facets that define a particular ontology domain concept. The notions of conceptual overlap and facet are defined, together with their relation to scenarios of multiple inheritance in ontology models. Starting from the notion of a value partition, a terminology of ontology modelling constructs is introduced that allows the characterization of two types of conceptual overlap wit...

Teaching Genetic Counseling Skills: Incorporating a Genetic Counseling Adaptation Continuum Model to Address Psychosocial Complexity.

Science.gov (United States)

Shugar, Andrea

2017-04-01

Genetic counselors are trained health care professionals who effectively integrate both psychosocial counseling and information-giving into their practice. Preparing genetic counseling students for clinical practice is a challenging task, particularly when helping them develop effective and active counseling skills. Resistance to incorporating these skills may stem from decreased confidence, fear of causing harm or a lack of clarity of psycho-social goals. The author reflects on the personal challenges experienced in teaching genetic counselling students to work with psychological and social complexity, and proposes a Genetic Counseling Adaptation Continuum model and methodology to guide students in the use of advanced counseling skills.

Model for Volatile Incorporation into Soils and Dust on Mars

Science.gov (United States)

Clark, B. C.; Yen, A.

2006-12-01

Martian soils with high content of compounds of sulfur and chlorine are ubiquitous on Mars, having been found at all five landing sites. Sulfate and chloride salts are implicated by a variety of evidence, but few conclusive specific identifications have been made. Discovery of jarosite and Mg-Ca sulfates in outcrops at Meridiani Planum (MER mission) and regional-scale beds of kieserite and gypsum (Mars Express mission) notwithstanding, the sulfates in soils are uncertain. Chlorides or other Cl-containing minerals have not been uniquely identified directly by any method. Viking and Pathfinder missions found trends in the elemental analytical data consistent with MgSO4, but Viking results are biased by duricrust samples and Pathfinder by soil contamination of rock surfaces. The Mars Exploration Rovers (MER) missions have taken extensive data on soils with no confirmation of trends implicating any particular cation. In our model of martian dust and soil, the S and Cl are initially incorporated by condensation or chemisorption on grains directly from gas phase molecules in the atmosphere. It is shown by modeling that the coatings thus formed cannot quantitatively explain the apparent elemental composition of these materials, and therefore involve the migration of ions and formation of microscopic weathering rinds. Original cation inventories of unweathered particles are isochemically conserved. Exposed rock surfaces should also have micro rinds, depending upon the length of time of exposure. Martian soils may therefore have unusual chemical properties when interacting with aqueous layers or infused fluids. Potential ramifications to the quantitative accuracy of x-ray fluorescence and Moessbauer spectroscopy on unprocessed samples are also assessed.

Modelling and simulation of multiple single - phase induction motor in parallel connection

Directory of Open Access Journals (Sweden)

Sujitjorn, S.

2006-11-01

Full Text Available A mathematical model for parallel connected n-multiple single-phase induction motors in generalized state-space form is proposed in this paper. The motor group draws electric power from one inverter. The model is developed by the dq-frame theory and was tested against four loading scenarios in which satisfactory results were obtained.

A Fractional Supervision Game Model of Multiple Stakeholders and Numerical Simulation

Directory of Open Access Journals (Sweden)

Rongwu Lu

2017-01-01

Full Text Available Considering the popular use of a certain kind of supervision management problem in many fields, we firstly build an ordinary supervision game model of multiple stakeholders. Secondly, a fractional supervision game model is set up and solved based on the theory of fractional calculus and a predictor-corrector numerical approach. Thirdly, the methods of phase diagram and time series graph were applied to simulate and analyse the dynamic process of the fractional order game model. Results of numerical solutions are given to illustrate our conclusions and referred to the practice.

Efficient surrogate models for reliability analysis of systems with multiple failure modes

International Nuclear Information System (INIS)

Bichon, Barron J.; McFarland, John M.; Mahadevan, Sankaran

2011-01-01

Despite many advances in the field of computational reliability analysis, the efficient estimation of the reliability of a system with multiple failure modes remains a persistent challenge. Various sampling and analytical methods are available, but they typically require accepting a tradeoff between accuracy and computational efficiency. In this work, a surrogate-based approach is presented that simultaneously addresses the issues of accuracy, efficiency, and unimportant failure modes. The method is based on the creation of Gaussian process surrogate models that are required to be locally accurate only in the regions of the component limit states that contribute to system failure. This approach to constructing surrogate models is demonstrated to be both an efficient and accurate method for system-level reliability analysis. - Highlights: → Extends efficient global reliability analysis to systems with multiple failure modes. → Constructs locally accurate Gaussian process models of each response. → Highly efficient and accurate method for assessing system reliability. → Effectiveness is demonstrated on several test problems from the literature.

Multiplicity distributions in a thermodynamical model of hadron production in e+e- collisions

International Nuclear Information System (INIS)

Becattini, F.; Giovannini, A.; Lupia, S.

1996-01-01

Predictions of a thermodynamical model of hadron production for multiplicity distributions in e + e - annihilations at LEP and PEP-PETRA centre of mass energies are shown. The production process is described as a two-step process in which primary hadrons emitted from the thermal source decay into final observable particles. The final charged track multiplicity distributions turn out to be of negative binomial type and are in quite good agreement with experimental observations. The average number of clans calculated from fitted negative binomial coincides with the average number of primary hadrons predicted by the thermodynamical model, suggesting that clans should be identified with primary hadrons. (orig.)

Inference regarding multiple structural changes in linear models with endogenous regressors

NARCIS (Netherlands)

Boldea, O.; Hall, A.R.; Han, S.

2012-01-01

This paper considers the linear model with endogenous regressors and multiple changes in the parameters at unknown times. It is shown that minimization of a Generalized Method of Moments criterion yields inconsistent estimators of the break fractions, but minimization of the Two Stage Least Squares

Land-use change arising from rural land exchange : an agent-based simulation model

NARCIS (Netherlands)

Bakker, Martha M.; Alam, Shah Jamal; van Dijk, Jerry|info:eu-repo/dai/nl/29612642X; Rounsevell, Mark D. A.

Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing

A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints

International Nuclear Information System (INIS)

Koltsaklis, Nikolaos E.; Georgiadis, Michael C.

2015-01-01

Highlights: • A short-term structured investment planning model has been developed. • Unit commitment problem is incorporated into the long-term planning horizon. • Inherent intermittency of renewables is modelled in a comprehensive way. • The impact of CO_2 emission pricing in long-term investment decisions is quantified. • The evolution of system’s marginal price is evaluated for all the planning horizon. - Abstract: This work presents a generic mixed integer linear programming (MILP) model that integrates the unit commitment problem (UCP), i.e., daily energy planning with the long-term generation expansion planning (GEP) framework. Typical daily constraints at an hourly level such as start-up and shut-down related decisions (start-up type, minimum up and down time, synchronization, soak and desynchronization time constraints), ramping limits, system reserve requirements are combined with representative yearly constraints such as power capacity additions, power generation bounds of each unit, peak reserve requirements, and energy policy issues (renewables penetration limits, CO_2 emissions cap and pricing). For modelling purposes, a representative day (24 h) of each month over a number of years has been employed in order to determine the optimal capacity additions, electricity market clearing prices, and daily operational planning of the studied power system. The model has been tested on an illustrative case study of the Greek power system. Our approach aims to provide useful insight into strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level by providing the optimal energy roadmap under real operating and design constraints.

Incorporating the CALPHAD sublattice approach of ordering into the phase-field model with finite interface dissipation

International Nuclear Information System (INIS)

Zhang, Lijun; Stratmann, Matthias; Du, Yong; Sundman, Bo; Steinbach, Ingo

2015-01-01

A new approach to incorporate the sublattice models in the CALPHAD (CALculation of PHAse Diagram) formalism directly into the phase-field formalism is developed. In binary alloys, the sublattice models can be classified into two types (i.e., “Type I” and “Type II”), depending on whether a direct one-to-one relation between the element site fraction in the CALPHAD database and the phase concentration in the phase-field model exists (Type I), or not (Type II). For “Type II” sublattice models, the specific site fractions, corresponding to a given mole fraction, have to be established via internal relaxation between different sublattices. Internal minimization of sublattice occupancy and solute evolution during microstructure transformation leads, in general, to a solution superior to the separate solution of the individual problems. The present coupling technique is validated for Fe–C and Ni–Al alloys. Finally, the model is extended into multicomponent alloys and applied to simulate the nucleation process of VC monocarbide from austenite matrix in a steel containing vanadium

Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

Directory of Open Access Journals (Sweden)

Tang Xiaofeng

2014-01-01

Full Text Available The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.

Egg white powder-stabilised multiple (water-in-olive oil-in-water) emulsions as beef fat replacers in model system meat emulsions.

Science.gov (United States)

Öztürk, Burcu; Urgu, Müge; Serdaroğlu, Meltem

2017-05-01

Today, multiple emulsions are believed to have a considerable application potential in food industry. We aimed to investigate physical, chemical and textural quality characteristics of model system meat emulsions (MSME) in which beef fat (C) was totally replaced by 10% (E-10), 20% (E-20) or 30% (E-30) multiple emulsions (W 1 /O/W 2 ) prepared with olive oil and egg white powder (EWP). Incorporation of W 1 /O/W 2 emulsion resulted in reduced fat (from 11.54% to 4.01%), increased protein content (from 13.66% to 14.74%), and modified fatty acid composition, significantly increasing mono- and polyunsaturated fatty acid content and decreasing saturated fatty acid content. E-20 and E-30 samples had lower jelly and fat separation (5.77% and 5.25%) compared to C and E-10 (9.67% and 8.55%). W 1 /O/W 2 emulsion treatments had higher water-holding capacity (93.96-94.35%) than C samples (91.84%), and also showed the desired storage stability over time. Emulsion stability results showed that E-20 and E-30 samples had lower total expressible fluid (14.05% and 14.53%) and lower total expressible fat (5.06% and 5.33%) compared to C samples (19.13% and 6.09%). Increased concentrations of W 1 /O/W 2 emulsions led to alterations in colour and texture parameters. TBA values of samples were lower in W 1 /O/W 2 emulsion treatments than control treatment during 60 days of storage. Our results indicated that multiple emulsions prepared with olive oil and EWP had promising impacts on reducing fat, modifying the lipid composition and developing both technologically and oxidatively stable meat systems. These are the first findings concerning beef matrix fat replacement with multiple emulsions stabilised by EWP. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

KRYPTON INCORPORATION IN SPUTTERED SILICON FILMS

NARCIS (Netherlands)

GREUTER, MJW; NIESEN, L; HAKVOORT, RA; DEROODE, J; VANVEEN, A; BERNTSEN, AJM; SLOOF, WG

1993-01-01

The incorporation of Kr in sputtered a-Si films has been investigated in a systematic way by varying the Kr to Si flux, yielding Kr concentrations up to 5 at %. Compositions were determined with X-ray microanalysis. A model has been applied to describe the composition of the growing film. The layers

Robust anti-synchronization of uncertain chaotic systems based on multiple-kernel least squares support vector machine modeling

International Nuclear Information System (INIS)

Chen Qiang; Ren Xuemei; Na Jing

2011-01-01

Highlights: Model uncertainty of the system is approximated by multiple-kernel LSSVM. Approximation errors and disturbances are compensated in the controller design. Asymptotical anti-synchronization is achieved with model uncertainty and disturbances. Abstract: In this paper, we propose a robust anti-synchronization scheme based on multiple-kernel least squares support vector machine (MK-LSSVM) modeling for two uncertain chaotic systems. The multiple-kernel regression, which is a linear combination of basic kernels, is designed to approximate system uncertainties by constructing a multiple-kernel Lagrangian function and computing the corresponding regression parameters. Then, a robust feedback control based on MK-LSSVM modeling is presented and an improved update law is employed to estimate the unknown bound of the approximation error. The proposed control scheme can guarantee the asymptotic convergence of the anti-synchronization errors in the presence of system uncertainties and external disturbances. Numerical examples are provided to show the effectiveness of the proposed method.

Incorporating remote sensing-based ET estimates into the Community Land Model version 4.5

Directory of Open Access Journals (Sweden)

D. Wang

2017-07-01

Full Text Available Land surface models bear substantial biases in simulating surface water and energy budgets despite the continuous development and improvement of model parameterizations. To reduce model biases, Parr et al. (2015 proposed a method incorporating satellite-based evapotranspiration (ET products into land surface models. Here we apply this bias correction method to the Community Land Model version 4.5 (CLM4.5 and test its performance over the conterminous US (CONUS. We first calibrate a relationship between the observational ET from the Global Land Evaporation Amsterdam Model (GLEAM product and the model ET from CLM4.5, and assume that this relationship holds beyond the calibration period. During the validation or application period, a simulation using the default CLM4.5 (CLM is conducted first, and its output is combined with the calibrated observational-vs.-model ET relationship to derive a corrected ET; an experiment (CLMET is then conducted in which the model-generated ET is overwritten with the corrected ET. Using the observations of ET, runoff, and soil moisture content as benchmarks, we demonstrate that CLMET greatly improves the hydrological simulations over most of the CONUS, and the improvement is stronger in the eastern CONUS than the western CONUS and is strongest over the Southeast CONUS. For any specific region, the degree of the improvement depends on whether the relationship between observational and model ET remains time-invariant (a fundamental hypothesis of the Parr et al. (2015 method and whether water is the limiting factor in places where ET is underestimated. While the bias correction method improves hydrological estimates without improving the physical parameterization of land surface models, results from this study do provide guidance for physically based model development effort.

A LabVIEW model incorporating an open-loop arterial impedance and a closed-loop circulatory system.

Science.gov (United States)

Cole, R T; Lucas, C L; Cascio, W E; Johnson, T A

2005-11-01

While numerous computer models exist for the circulatory system, many are limited in scope, contain unwanted features or incorporate complex components specific to unique experimental situations. Our purpose was to develop a basic, yet multifaceted, computer model of the left heart and systemic circulation in LabVIEW having universal appeal without sacrificing crucial physiologic features. The program we developed employs Windkessel-type impedance models in several open-loop configurations and a closed-loop model coupling a lumped impedance and ventricular pressure source. The open-loop impedance models demonstrate afterload effects on arbitrary aortic pressure/flow inputs. The closed-loop model catalogs the major circulatory waveforms with changes in afterload, preload, and left heart properties. Our model provides an avenue for expanding the use of the ventricular equations through closed-loop coupling that includes a basic coronary circuit. Tested values used for the afterload components and the effects of afterload parameter changes on various waveforms are consistent with published data. We conclude that this model offers the ability to alter several circulatory factors and digitally catalog the most salient features of the pressure/flow waveforms employing a user-friendly platform. These features make the model a useful instructional tool for students as well as a simple experimental tool for cardiovascular research.

Simultaneous small-sample comparisons in longitudinal or multi-endpoint trials using multiple marginal models

DEFF Research Database (Denmark)

Pallmann, Philip; Ritz, Christian; Hothorn, Ludwig A

2018-01-01

, however only asymptotically. In this paper, we show how to make the approach also applicable to small-sample data problems. Specifically, we discuss the computation of adjusted P values and simultaneous confidence bounds for comparisons of randomised treatment groups as well as for levels......Simultaneous inference in longitudinal, repeated-measures, and multi-endpoint designs can be onerous, especially when trying to find a reasonable joint model from which the interesting effects and covariances are estimated. A novel statistical approach known as multiple marginal models greatly...... simplifies the modelling process: the core idea is to "marginalise" the problem and fit multiple small models to different portions of the data, and then estimate the overall covariance matrix in a subsequent, separate step. Using these estimates guarantees strong control of the family-wise error rate...

Quantum-Mechanical Methods for Quantifying Incorporation of Contaminants in Proximal Minerals

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Lindsay C. Shuller-Nickles

2014-07-01

Full Text Available Incorporation reactions play an important role in dictating immobilization and release pathways for chemical species in low-temperature geologic environments. Quantum-mechanical investigations of incorporation seek to characterize the stability and geometry of incorporated structures, as well as the thermodynamics and kinetics of the reactions themselves. For a thermodynamic treatment of incorporation reactions, a source of the incorporated ion and a sink for the released ion is necessary. These sources/sinks in a real geochemical system can be solids, but more commonly, they are charged aqueous species. In this contribution, we review the current methods for ab initio calculations of incorporation reactions, many of which do not consider incorporation from aqueous species. We detail a recently-developed approach for the calculation of incorporation reactions and expand on the part that is modeling the interaction of periodic solids with aqueous source and sink phases and present new research using this approach. To model these interactions, a systematic series of calculations must be done to transform periodic solid source and sink phases to aqueous-phase clusters. Examples of this process are provided for three case studies: (1 neptunyl incorporation into studtite and boltwoodite: for the layered boltwoodite, the incorporation energies are smaller (more favorable for reactions using environmentally relevant source and sink phases (i.e., ΔErxn(oxides > ΔErxn(silicates > ΔErxn(aqueous. Estimates of the solid-solution behavior of Np5+/P5+- and U6+/Si4+-boltwoodite and Np5+/Ca2+- and U6+/K+-boltwoodite solid solutions are used to predict the limit of Np-incorporation into boltwoodite (172 and 768 ppm at 300 °C, respectively; (2 uranyl and neptunyl incorporation into carbonates and sulfates: for both carbonates and sulfates, it was found that actinyl incorporation into a defect site is more favorable than incorporation into defect-free periodic