WorldWideScience

Sample records for generalized additive models

  1. Generalized Additive Models for Nowcasting Cloud Shading

    Czech Academy of Sciences Publication Activity Database

    Brabec, Marek; Paulescu, M.; Badescu, V.

    2014-01-01

    Roč. 101, March (2014), s. 272-282 ISSN 0038-092X R&D Projects: GA MŠk LD12009 Grant - others:European Cooperation in Science and Technology(XE) COST ES1002 Institutional support: RVO:67985807 Keywords : sunshine number * nowcasting * generalized additive model * Markov chain Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.469, year: 2014

  2. A generalized additive regression model for survival times

    DEFF Research Database (Denmark)

    Scheike, Thomas H.

    2001-01-01

    Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models......Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models...

  3. Generalized additive model of air pollution to daily mortality

    International Nuclear Information System (INIS)

    Kim, J.; Yang, H.E.

    2005-01-01

    The association of air pollution with daily mortality due to cardiovascular disease, respiratory disease, and old age (65 or older) in Seoul, Korea was investigated in 1999 using daily values of TSP, PM10, O 3 , SO 2 , NO 2 , and CO. Generalized additive Poisson models were applied to allow for the highly flexible fitting of daily trends in air pollution as well as nonlinear association with meteorological variables such as temperature, humidity, and wind speed. To estimate the effect of air pollution and weather on mortality, LOESS smoothing was used in generalized additive models. The findings suggest that air pollution levels affect significantly the daily mortality. (orig.)

  4. Estimation and variable selection for generalized additive partial linear models

    KAUST Repository

    Wang, Li

    2011-08-01

    We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.

  5. Generalized bi-additive modelling for categorical data

    NARCIS (Netherlands)

    P.J.F. Groenen (Patrick); A.J. Koning (Alex)

    2004-01-01

    textabstractGeneralized linear modelling (GLM) is a versatile technique, which may be viewed as a generalization of well-known techniques such as least squares regression, analysis of variance, loglinear modelling, and logistic regression. In may applications, low-order interaction (such as

  6. 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

  7. Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data

    KAUST Repository

    Cheng, Guang; Zhou, Lan; Huang, Jianhua Z.

    2014-01-01

    We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based

  8. Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro.

    Directory of Open Access Journals (Sweden)

    Niels Hadrup

    Full Text Available Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA, independent action (IA and generalized concentration addition (GCA models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot

  9. An introduction to modeling longitudinal data with generalized additive models: applications to single-case designs.

    Science.gov (United States)

    Sullivan, Kristynn J; Shadish, William R; Steiner, Peter M

    2015-03-01

    Single-case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time in both the presence and absence of treatment. This article introduces a statistical technique for analyzing SCD data that has not been much used in psychological and educational research: generalized additive models (GAMs). In parametric regression, the researcher must choose a functional form to impose on the data, for example, that trend over time is linear. GAMs reverse this process by letting the data inform the choice of functional form. In this article we review the problem that trend poses in SCDs, discuss how current SCD analytic methods approach trend, describe GAMs as a possible solution, suggest a GAM model testing procedure for examining the presence of trend in SCDs, present a small simulation to show the statistical properties of GAMs, and illustrate the procedure on 3 examples of different lengths. Results suggest that GAMs may be very useful both as a form of sensitivity analysis for checking the plausibility of assumptions about trend and as a primary data analysis strategy for testing treatment effects. We conclude with a discussion of some problems with GAMs and some future directions for research on the application of GAMs to SCDs. (c) 2015 APA, all rights reserved).

  10. Incorporating shape constraints in generalized additive modelling of the height-diameter relationship for Norway spruce

    Directory of Open Access Journals (Sweden)

    Natalya Pya

    2016-02-01

    Full Text Available Background: Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height (dbh can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter (h-d models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions. Methods: We develop unconstrained generalized additive models (GAM and shape constrained generalized additive models (SCAM for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany. Results: Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand. The definition of constraints leads only to marginal or minor decline in the model statistics like AIC. An observed structured spatial trend in tree height is modelled via 2-dimensional surface

  11. Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

    Science.gov (United States)

    Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

    2017-09-11

    Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

  12. The regression-calibration method for fitting generalized linear models with additive measurement error

    OpenAIRE

    James W. Hardin; Henrik Schmeidiche; Raymond J. Carroll

    2003-01-01

    This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on s...

  13. Vector generalized linear and additive models with an implementation in R

    CERN Document Server

    Yee, Thomas W

    2015-01-01

    This book presents a statistical framework that expands generalized linear models (GLMs) for regression modelling. The framework shared in this book allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole. This is possible through the approximately half-a-dozen major classes of statistical models included in the book and the software infrastructure component, which makes the models easily operable.    The book’s methodology and accompanying software (the extensive VGAM R package) are directed at these limitations, and this is the first time the methodology and software are covered comprehensively in one volume. Since their advent in 1972, GLMs have unified important distributions under a single umbrella with enormous implications. The demands of practical data analysis, however, require a flexibility that GLMs do not have. Data-driven GLMs, in the form of generalized additive models (GAMs), are also largely confined to the exponential family. This book ...

  14. Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.

    Science.gov (United States)

    Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

    2013-01-01

    Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.

  15. Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data

    KAUST Repository

    Cheng, Guang

    2014-02-01

    We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based on a spline approximation of the nonparametric part of the model and the generalized estimating equations (GEE). Although the model in consideration is natural and useful in many practical applications, the literature on this model is very limited because of challenges in dealing with dependent data for nonparametric additive models. We show that the proposed estimators are consistent and asymptotically normal even if the covariance structure is misspecified. An explicit consistent estimate of the asymptotic variance is also provided. Moreover, we derive the semiparametric efficiency score and information bound under general moment conditions. By showing that our estimators achieve the semiparametric information bound, we effectively establish their efficiency in a stronger sense than what is typically considered for GEE. The derivation of our asymptotic results relies heavily on the empirical processes tools that we develop for the longitudinal/clustered data. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2014 ISI/BS.

  16. Generalized neurofuzzy network modeling algorithms using Bézier-Bernstein polynomial functions and additive decomposition.

    Science.gov (United States)

    Hong, X; Harris, C J

    2000-01-01

    This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

  17. Predicting mastitis in dairy cows using neural networks and generalized additive models

    DEFF Research Database (Denmark)

    Anantharama Ankinakatte, Smitha; Norberg, Elise; Løvendahl, Peter

    2013-01-01

    The aim of this paper is to develop and compare methods for early detection of oncoming mastitis with automated recorded data. The data were collected at the Danish Cattle Research Center (Tjele, Denmark). As indicators of mastitis, electrical conductivity (EC), somatic cell scores (SCS), lactate...... that combines residual components into a score to improve the model. To develop and verify the model, the data are randomly divided into training and validation data sets. To predict the occurrence of mastitis, neural network models (NNs) and generalized additive models (GAMs) are developed using the training...... classification with all indicators, using individual residuals rather than factor scores. When SCS is excluded, GAMs shows better classification result when milk yield is also excluded. In conclusion, the study shows that NNs and GAMs are similar in their ability to detect mastitis, a sensitivity of almost 75...

  18. Generalized additive models and Lucilia sericata growth: assessing confidence intervals and error rates in forensic entomology.

    Science.gov (United States)

    Tarone, Aaron M; Foran, David R

    2008-07-01

    Forensic entomologists use blow fly development to estimate a postmortem interval. Although accurate, fly age estimates can be imprecise for older developmental stages and no standard means of assigning confidence intervals exists. Presented here is a method for modeling growth of the forensically important blow fly Lucilia sericata, using generalized additive models (GAMs). Eighteen GAMs were created to predict the extent of juvenile fly development, encompassing developmental stage, length, weight, strain, and temperature data, collected from 2559 individuals. All measures were informative, explaining up to 92.6% of the deviance in the data, though strain and temperature exerted negligible influences. Predictions made with an independent data set allowed for a subsequent examination of error. Estimates using length and developmental stage were within 5% of true development percent during the feeding portion of the larval life cycle, while predictions for postfeeding third instars were less precise, but within expected error.

  19. GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis.

    Science.gov (United States)

    Stricker, Georg; Engelhardt, Alexander; Schulz, Daniel; Schmid, Matthias; Tresch, Achim; Gagneur, Julien

    2017-08-01

    Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used approach to study protein-DNA interactions. Often, the quantities of interest are the differential occupancies relative to controls, between genetic backgrounds, treatments, or combinations thereof. Current methods for differential occupancy of ChIP-Seq data rely however on binning or sliding window techniques, for which the choice of the window and bin sizes are subjective. Here, we present GenoGAM (Genome-wide Generalized Additive Model), which brings the well-established and flexible generalized additive models framework to genomic applications using a data parallelism strategy. We model ChIP-Seq read count frequencies as products of smooth functions along chromosomes. Smoothing parameters are objectively estimated from the data by cross-validation, eliminating ad hoc binning and windowing needed by current approaches. GenoGAM provides base-level and region-level significance testing for full factorial designs. Application to a ChIP-Seq dataset in yeast showed increased sensitivity over existing differential occupancy methods while controlling for type I error rate. By analyzing a set of DNA methylation data and illustrating an extension to a peak caller, we further demonstrate the potential of GenoGAM as a generic statistical modeling tool for genome-wide assays. Software is available from Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/GenoGAM.html . gagneur@in.tum.de. Supplementary information is available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  20. Analysis of time to event outcomes in randomized controlled trials by generalized additive models.

    Directory of Open Access Journals (Sweden)

    Christos Argyropoulos

    Full Text Available Randomized Controlled Trials almost invariably utilize the hazard ratio calculated with a Cox proportional hazard model as a treatment efficacy measure. Despite the widespread adoption of HRs, these provide a limited understanding of the treatment effect and may even provide a biased estimate when the assumption of proportional hazards in the Cox model is not verified by the trial data. Additional treatment effect measures on the survival probability or the time scale may be used to supplement HRs but a framework for the simultaneous generation of these measures is lacking.By splitting follow-up time at the nodes of a Gauss Lobatto numerical quadrature rule, techniques for Poisson Generalized Additive Models (PGAM can be adopted for flexible hazard modeling. Straightforward simulation post-estimation transforms PGAM estimates for the log hazard into estimates of the survival function. These in turn were used to calculate relative and absolute risks or even differences in restricted mean survival time between treatment arms. We illustrate our approach with extensive simulations and in two trials: IPASS (in which the proportionality of hazards was violated and HEMO a long duration study conducted under evolving standards of care on a heterogeneous patient population.PGAM can generate estimates of the survival function and the hazard ratio that are essentially identical to those obtained by Kaplan Meier curve analysis and the Cox model. PGAMs can simultaneously provide multiple measures of treatment efficacy after a single data pass. Furthermore, supported unadjusted (overall treatment effect but also subgroup and adjusted analyses, while incorporating multiple time scales and accounting for non-proportional hazards in survival data.By augmenting the HR conventionally reported, PGAMs have the potential to support the inferential goals of multiple stakeholders involved in the evaluation and appraisal of clinical trial results under proportional and

  1. “Skill of Generalized Additive Model to Detect PM2.5 Health ...

    Science.gov (United States)

    Summary. Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables of interest (and by implication scales and periods that are not shared). Hospital admissions, meteorology (temperature and relative humidity), and air quality (PM2.5 and daily maximum ozone) for New York City during the period 2000-2006 were decomposed into temporal scales ranging from 2 days to greater than two years using a complex wavelet transform. Health effects were modeled as functions of the wavelet components of meteorology and air quality using the generalized additive model (GAM) framework. This simulation study showed that GAM is extremely successful at extracting and estimating a health effect embedded in a dataset. It also shows that, if the objective in mind is to estimate the health signal but not to fully explain this signal, a simple GAM model with a single confounder (calendar time) whose smooth representation includes a sufficient number of constraints is as good as a more complex model.Introduction. In the context of wavelet regression, confounding occurs when two or more independent variables interact with the dependent variable at the same frequency. Confounding also acts on a variety of time scales, changing the PM2.5 coefficient (magnitude and sign) and its significance ac

  2. A habitat suitability model for Chinese sturgeon determined using the generalized additive method

    Science.gov (United States)

    Yi, Yujun; Sun, Jie; Zhang, Shanghong

    2016-03-01

    The Chinese sturgeon is a type of large anadromous fish that migrates between the ocean and rivers. Because of the construction of dams, this sturgeon's migration path has been cut off, and this species currently is on the verge of extinction. Simulating suitable environmental conditions for spawning followed by repairing or rebuilding its spawning grounds are effective ways to protect this species. Various habitat suitability models based on expert knowledge have been used to evaluate the suitability of spawning habitat. In this study, a two-dimensional hydraulic simulation is used to inform a habitat suitability model based on the generalized additive method (GAM). The GAM is based on real data. The values of water depth and velocity are calculated first via the hydrodynamic model and later applied in the GAM. The final habitat suitability model is validated using the catch per unit effort (CPUEd) data of 1999 and 2003. The model results show that a velocity of 1.06-1.56 m/s and a depth of 13.33-20.33 m are highly suitable ranges for the Chinese sturgeon to spawn. The hydraulic habitat suitability indexes (HHSI) for seven discharges (4000; 9000; 12,000; 16,000; 20,000; 30,000; and 40,000 m3/s) are calculated to evaluate integrated habitat suitability. The results show that the integrated habitat suitability reaches its highest value at a discharge of 16,000 m3/s. This study is the first to apply a GAM to evaluate the suitability of spawning grounds for the Chinese sturgeon. The study provides a reference for the identification of potential spawning grounds in the entire basin.

  3. Exposure as Duration and Distance in Telematics Motor Insurance Using Generalized Additive Models

    Directory of Open Access Journals (Sweden)

    Jean-Philippe Boucher

    2017-09-01

    Full Text Available In Pay-As-You-Drive (PAYD automobile insurance, the premium is fixed based on the distance traveled, while in usage-based insurance (UBI the driving patterns of the policyholder are also considered. In those schemes, drivers who drive more pay a higher premium compared to those with the same characteristics who drive only occasionally, because the former are more exposed to the risk of accident. In this paper, we analyze the simultaneous effect of the distance traveled and exposure time on the risk of accident by using Generalized Additive Models (GAM. We carry out an empirical application and show that the expected number of claims (1 stabilizes once a certain number of accumulated distance-driven is reached and (2 it is not proportional to the duration of the contract, which is in contradiction to insurance practice. Finally, we propose to use a rating system that takes into account simultaneously exposure time and distance traveled in the premium calculation. We think that this is the trend the automobile insurance market is going to follow with the eruption of telematics data.

  4. Gadolinium deposition in the brain: association with various GBCAs using a generalized additive model

    Energy Technology Data Exchange (ETDEWEB)

    Bae, Sohi; Lee, Ho-Joon; Han, Kyunghwa; Park, Yae-Won; Choi, Yoon Seong; Ahn, Sung Soo; Kim, Jinna; Lee, Seung-Koo [Yonsei University College of Medicine, Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Seoul (Korea, Republic of)

    2017-08-15

    To determine the relationship between the number of administrations of various gadolinium-based contrast agents (GBCAs) and increased T1 signal intensity in the globus pallidus (GP) and dentate nucleus (DN). This retrospective study included 122 patients who underwent double-dose GBCA-enhanced magnetic resonance imaging. Two radiologists calculated GP-to-thalamus (TH) signal intensity ratio, DN-to-pons signal intensity ratio and relative change (R{sub change}) between the baseline and final examinations. Interobserver agreement was evaluated. The relationships between R{sub change} and several factors, including number of each GBCA administrations, were analysed using a generalized additive model. Six patients (4.9%) received linear GBCAs (mean 20.8 number of administration; range 15-30), 44 patients (36.1%) received macrocyclic GBCAs (mean 26.1; range 14-51) and 72 patients (59.0%) received both types of GBCAs (mean 31.5; range 12-65). Interobserver agreement was almost perfect (0.99; 95% CI: 0.99-0.99). R{sub change} (DN:pons) was associated with gadodiamide (p = 0.006) and gadopentetate dimeglumine (p < 0.001), but not with other GBCAs. R{sub change} (GP:TH) was not associated with GBCA administration. Previous administration of linear agents gadoiamide and gadopentetate dimeglumine is associated with increased T1 signal intensity in the DN, whereas macrocyclic GBCAs do not show an association. (orig.)

  5. Method for mapping population-based case-control studies: an application using generalized additive models

    Directory of Open Access Journals (Sweden)

    Aschengrau Ann

    2006-06-01

    Full Text Available Abstract Background Mapping spatial distributions of disease occurrence and risk can serve as a useful tool for identifying exposures of public health concern. Disease registry data are often mapped by town or county of diagnosis and contain limited data on covariates. These maps often possess poor spatial resolution, the potential for spatial confounding, and the inability to consider latency. Population-based case-control studies can provide detailed information on residential history and covariates. Results Generalized additive models (GAMs provide a useful framework for mapping point-based epidemiologic data. Smoothing on location while controlling for covariates produces adjusted maps. We generate maps of odds ratios using the entire study area as a reference. We smooth using a locally weighted regression smoother (loess, a method that combines the advantages of nearest neighbor and kernel methods. We choose an optimal degree of smoothing by minimizing Akaike's Information Criterion. We use a deviance-based test to assess the overall importance of location in the model and pointwise permutation tests to locate regions of significantly increased or decreased risk. The method is illustrated with synthetic data and data from a population-based case-control study, using S-Plus and ArcView software. Conclusion Our goal is to develop practical methods for mapping population-based case-control and cohort studies. The method described here performs well for our synthetic data, reproducing important features of the data and adequately controlling the covariate. When applied to the population-based case-control data set, the method suggests spatial confounding and identifies statistically significant areas of increased and decreased odds ratios.

  6. Generalized Additive Models for Location Scale and Shape (GAMLSS) in R

    OpenAIRE

    D. Mikis Stasinopoulos; Robert A. Rigby

    2007-01-01

    GAMLSS is a general framework for fitting regression type models where the distribution of the response variable does not have to belong to the exponential family and includes highly skew and kurtotic continuous and discrete distribution. GAMLSS allows all the parameters of the distribution of the response variable to be modelled as linear/non-linear or smooth functions of the explanatory variables. This paper starts by defining the statistical framework of GAMLSS, then describes the curren...

  7. The relation between air pollution and respiratory deaths in Tehran, Iran- using generalized additive models.

    Science.gov (United States)

    Dehghan, Azizallah; Khanjani, Narges; Bahrampour, Abbas; Goudarzi, Gholamreza; Yunesian, Masoud

    2018-03-20

    Some epidemiological evidence has shown a relation between ambient air pollution and adverse health outcomes. The aim of this study was to investigate the effect of air pollution on mortality from respiratory diseases in Tehran, Iran. In this ecological study, air pollution data was inquired from the Tehran Province Environmental Protection Agency and the Tehran Air Quality Control Company. Meteorological data was collected from the Tehran Meteorology Organization and mortality data from the Tehran Cemetery Mortality Registration. Generalized Additive Models (GAM) was used for data analysis with different lags, up to 15 days. A 10-unit increase in all pollutants except CO (1-unit) was used to compute the Relative Risk of deaths. During 2005 until 2014, 37,967 respiratory deaths occurred in Tehran in which 21,913 (57.7%) were male. The strongest relationship between NO 2 and PM 10 and respiratory death was seen on the same day (lag 0), and was respectively (RR = 1.04, 95% CI: 1.02-1.07) and (RR = 1.03, 95% CI: 1.02-1.04). O 3 and PM 2.5 had the strongest relationship with respiratory deaths on lag 2 and 1 respectively, and the RR was equal to 1.03, 95% CI: 1.01-1.05 and 1.06, 95% CI: 1.02-1.10 respectively. NO 2 , O 3 , PM 10 and PM 2.5 also showed significant relations with respiratory deaths in the older age groups. The findings of this study showed that O 3 , NO 2 , PM 10 and PM 2.5 air pollutants were related to respiratory deaths in Tehran. Reducing ambient air pollution can save lives in Tehran.

  8. Generalized Additive Models for Location Scale and Shape (GAMLSS in R

    Directory of Open Access Journals (Sweden)

    D. Mikis Stasinopoulos

    2007-11-01

    Full Text Available GAMLSS is a general framework for fitting regression type models where the distribution of the response variable does not have to belong to the exponential family and includes highly skew and kurtotic continuous and discrete distribution. GAMLSS allows all the parameters of the distribution of the response variable to be modelled as linear/non-linear or smooth functions of the explanatory variables. This paper starts by defining the statistical framework of GAMLSS, then describes the current implementation of GAMLSS in R and finally gives four different data examples to demonstrate how GAMLSS can be used for statistical modelling.

  9. Generalized additive models used to predict species abundance in the Gulf of Mexico: an ecosystem modeling tool.

    Directory of Open Access Journals (Sweden)

    Michael Drexler

    Full Text Available Spatially explicit ecosystem models of all types require an initial allocation of biomass, often in areas where fisheries independent abundance estimates do not exist. A generalized additive modelling (GAM approach is used to describe the abundance of 40 species groups (i.e. functional groups across the Gulf of Mexico (GoM using a large fisheries independent data set (SEAMAP and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. Despite the presence of a large number of zeros in the data, a single GAM using a negative binomial distribution was suitable to make predictions of abundance for multiple functional groups. We present an example case study using pink shrimp (Farfantepenaeus duroarum and compare the results to known distributions. The model successfully predicts the known areas of high abundance in the GoM, including those areas where no data was inputted into the model fitting. Overall, the model reliably captures areas of high and low abundance for the large majority of functional groups observed in SEAMAP. The result of this method allows for the objective setting of spatial distributions for numerous functional groups across a modeling domain, even where abundance data may not exist.

  10. Distributional modeling and short-term forecasting of electricity prices by Generalized Additive Models for Location, Scale and Shape

    International Nuclear Information System (INIS)

    Serinaldi, Francesco

    2011-01-01

    In the context of the liberalized and deregulated electricity markets, price forecasting has become increasingly important for energy company's plans and market strategies. Within the class of the time series models that are used to perform price forecasting, the subclasses of methods based on stochastic time series and causal models commonly provide point forecasts, whereas the corresponding uncertainty is quantified by approximate or simulation-based confidence intervals. Aiming to improve the uncertainty assessment, this study introduces the Generalized Additive Models for Location, Scale and Shape (GAMLSS) to model the dynamically varying distribution of prices. The GAMLSS allow fitting a variety of distributions whose parameters change according to covariates via a number of linear and nonlinear relationships. In this way, price periodicities, trends and abrupt changes characterizing both the position parameter (linked to the expected value of prices), and the scale and shape parameters (related to price volatility, skewness, and kurtosis) can be explicitly incorporated in the model setup. Relying on the past behavior of the prices and exogenous variables, the GAMLSS enable the short-term (one-day ahead) forecast of the entire distribution of prices. The approach was tested on two datasets from the widely studied California Power Exchange (CalPX) market, and the less mature Italian Power Exchange (IPEX). CalPX data allow comparing the GAMLSS forecasting performance with published results obtained by different models. The study points out that the GAMLSS framework can be a flexible alternative to several linear and nonlinear stochastic models. - Research Highlights: ► Generalized Additive Models for Location, Scale and Shape (GAMLSS) are used to model electricity prices' time series. ► GAMLSS provide the entire dynamicaly varying distribution function of prices resorting to a suitable set of covariates that drive the instantaneous values of the parameters

  11. Modeling the Short-Term Effect of Traffic and Meteorology on Air Pollution in Turin with Generalized Additive Models

    Directory of Open Access Journals (Sweden)

    Pancrazio Bertaccini

    2012-01-01

    Full Text Available Vehicular traffic plays an important role in atmospheric pollution and can be used as one of the key predictors in air-quality forecasting models. The models that can account for the role of traffic are especially valuable in urban areas, where high pollutant concentrations are often observed during particular times of day (rush hour and year (winter. In this paper, we develop a generalized additive models approach to analyze the behavior of concentrations of nitrogen dioxide (NO2, and particulate matter (PM10, collected at the environmental monitoring stations distributed throughout the city of Turin, Italy, from December 2003 to April 2005. We describe nonlinear relationships between predictors and pollutants, that are adjusted for unobserved time-varying confounders. We examine several functional forms for the traffic variable and find that a simple form can often provide adequate modeling power. Our analysis shows that there is a saturation effect of traffic on NO2, while such saturation is less evident in models linking traffic to PM10 behavior, having adjusted for meteorological covariates. Moreover, we consider the proposed models separately by seasons and highlight similarities and differences in the predictors’ partial effects. Finally, we show how forecasting can help in evaluating traffic regulation policies.

  12. Shape of the BMI-mortality association by cause of death, using generalized additive models: NHIS 1986-2006.

    Science.gov (United States)

    Zajacova, Anna; Burgard, Sarah A

    2012-03-01

    Numerous studies have examined the association between body mass index (BMI) and mortality. The precise shape of their association, however, has not been established. We use nonparametric methods to determine the relationship between BMI and mortality. Data from the National Health Interview Survey-Linked Mortality Files 1986-2006 for adults aged 50 to 80 are analyzed using a Poisson approach to survival modeling within the generalized additive model (GAM) framework. The BMI-mortality association is more V shaped than U shaped, with the odds of dying rising steeply from the lowest risk point at BMIs of 23 to 26. The association varies considerably by time since interview and cause of death. For instance, the association has an inverted J shape for respiratory causes but is monotonically increasing for diabetes deaths. Our findings have implications for interpreting results from BMI-mortality studies and suggest caution in translating the findings into public health messages.

  13. Applied mixed generalized additive model to assess the effect of temperature on the incidence of bacillary dysentery and its forecast.

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    Weiping Ma

    Full Text Available BACKGROUND: Association between bacillary dysentery (BD disease and temperature has been reported in some studies applying Poisson regression model, however the effect estimation might be biased due to the data autocorrelation. Furthermore the temperature effect distributed in the time of different lags has not been studied either. The purpose of this work was to obtaining the association between the BD counts and the climatic factors such as temperature in the form of the weighted averages, concerning the autocorrelation pattern of the model residuals, and to make short term predictions using the model. The data was collected in the city of Shanghai from 2004 to 2008. METHODS: We used mixed generalized additive model (MGAM to analyze data on bacillary dysentery, temperature and other covariates with autoregressive random effect. Short term predictions were made using MGAM with the moving average of the BD counts. MAIN RESULTS: Our results showed that temperature was significant linearly associated with the logarithm of BD count for temperature in the range from 12°C to 22°C. Optimal weights in the temperature effect have been obtained, in which the one of 1-day-lag was close to 0, and the one of 2-days-lag was the maximum (p-value of the difference was less than 0.05. The predictive model was showing good fitness on the internal data with R(2 value 0.875, and the good short term prediction effect on the external data with correlation coefficient to be 0.859. CONCLUSION: According to the model estimation, corresponding Risk Ratio to affect BD was close to 1.1 when temperature effect goes up for 1°C in the range from 12°C to 22°C. And the 1-day incubation period could be inferred from the model estimation. Good prediction has been made using the predictive MGAM.

  14. Analysis of habitat characteristics of small pelagic fish based on generalized additive models in Kepulauan Seribu Waters

    Science.gov (United States)

    Rivai, A. A.; Siregar, V. P.; Agus, S. B.; Yasuma, H.

    2018-03-01

    One of the required information for sustainable fisheries management is about the habitat characteristics of a fish species. This information can be used to map the distribution of fish and map the potential fishing ground. This study aimed to analyze the habitat characteristics of small pelagic fishes (anchovy, squid, sardine and scads) which were mainly caught by lift net in Kepulauan Seribu waters. Research on habitat characteristics had been widely done, but the use of total suspended solid (TSS) parameters in this analysis is still lacking. TSS parameter which was extracted from Landsat 8 along with five other oceanographic parameters, CPUE data and location of fishing ground data from lift net fisheries in Kepulauan Seribu were included in this analysis. This analysis used Generalized Additive Models (GAMs) to evaluate the relationship between CPUE and oceanographic parameters. The results of the analysis showed that each fish species had different habitat characteristics. TSS and sea surface height had a great influence on the value of CPUE from each species. All the oceanographic parameters affected the CPUE of each species. This study demonstrated the effective use of GAMs to identify the essential habitat of a fish species.

  15. Spatio-temporal modelling of zero-inflated deep-sea shrimp data by Tweedie generalized additive

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    Simona Arcuti

    2013-10-01

    Full Text Available In theMediterrean Sea the population features of demersal resources fluctuate over spatial and temporal scales due to the variability of abiotic and biotic factors as well as to human activities. The two shrimps Parapenaeus longirostris and Aristaeomorpha foliacea are among the most important deep-sea demersal resources in the North-Western Ionian Sea. Their changes in terms of density, biomass andmedian length induced by anthropogenic and environmental variables (fishing effort, sea surface temperature, precipitations, Winter North Atlantic Oscillation (NAO and Annual MediterraneanOscillation (MO indices were investigated. Biological data were collected during trawl surveys carried out from 1995 to 2006 as part of the international program MEDITS (International Bottom Trawl Survey in the Mediterranean. Generalized AdditiveModels were used to evaluate the spatio-temporal variation of both species, together with the possible nonlinear effects of biotic and abiotic factors. Density and biomass were assumed to be distributed according to a member of the Tweedie family in order to account for zero-inflation in the relative data. Spacetime interaction was consideredwithin a non-separablemodel with smooth spatio-temporal component based on tensor product splines. The results show significant spatio-temporal and depth effects in the three population parameters of these resources. Winter NAO index significantly influenced the density, biomass and length of P. longirostris. Sea surface temperature significantly influenced the size of this species and the three population features of A. foliacea. The size of this shrimp resulted also influenced negatively by fishing effort and positively by the MO index.

  16. A power comparison of generalized additive models and the spatial scan statistic in a case-control setting

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    Ozonoff Al

    2010-07-01

    Full Text Available Abstract Background A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. Results This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. Conclusions The GAM

  17. A power comparison of generalized additive models and the spatial scan statistic in a case-control setting.

    Science.gov (United States)

    Young, Robin L; Weinberg, Janice; Vieira, Verónica; Ozonoff, Al; Webster, Thomas F

    2010-07-19

    A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. The GAM permutation testing methods provide a regression

  18. Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling.

    Science.gov (United States)

    Thelen, Brian; French, Nancy H F; Koziol, Benjamin W; Billmire, Michael; Owen, Robert Chris; Johnson, Jeffrey; Ginsberg, Michele; Loboda, Tatiana; Wu, Shiliang

    2013-11-05

    A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. The model developed in this study allows a

  19. Model Additional Protocol

    International Nuclear Information System (INIS)

    Rockwood, Laura

    2001-01-01

    Since the end of the cold war a series of events has changed the circumstances and requirements of the safeguards system. The discovery of a clandestine nuclear weapons program in Iraq, the continuing difficulty in verifying the initial report of Democratic People's Republic of Korea upon entry into force of their safeguards agreement, and the decision of the South African Government to give up its nuclear weapons program and join the Treaty on the Non-Proliferation of Nuclear Weapons have all played a role in an ambitious effort by IAEA Member States and the Secretariat to strengthen the safeguards system. A major milestone in this effort was reached in May 1997 when the IAEA Board of Governors approved a Model Protocol Additional to Safeguards Agreements. The Model Additional Protocol was negotiated over a period of less than a year by an open-ended committee of the Board involving some 70 Member States and two regional inspectorates. The IAEA is now in the process of negotiating additional protocols, State by State, and implementing them. These additional protocols will provide the IAEA with rights of access to information about all activities related to the use of nuclear material in States with comprehensive safeguards agreements and greatly expanded physical access for IAEA inspectors to confirm or verify this information. In conjunction with this, the IAEA is working on the integration of these measures with those provided for in comprehensive safeguards agreements, with a view to maximizing the effectiveness and efficiency, within available resources, the implementation of safeguards. Details concerning the Model Additional Protocol are given. (author)

  20. Implementing Generalized Additive Models to Estimate the Expected Value of Sample Information in a Microsimulation Model: Results of Three Case Studies.

    Science.gov (United States)

    Rabideau, Dustin J; Pei, Pamela P; Walensky, Rochelle P; Zheng, Amy; Parker, Robert A

    2018-02-01

    The expected value of sample information (EVSI) can help prioritize research but its application is hampered by computational infeasibility, especially for complex models. We investigated an approach by Strong and colleagues to estimate EVSI by applying generalized additive models (GAM) to results generated from a probabilistic sensitivity analysis (PSA). For 3 potential HIV prevention and treatment strategies, we estimated life expectancy and lifetime costs using the Cost-effectiveness of Preventing AIDS Complications (CEPAC) model, a complex patient-level microsimulation model of HIV progression. We fitted a GAM-a flexible regression model that estimates the functional form as part of the model fitting process-to the incremental net monetary benefits obtained from the CEPAC PSA. For each case study, we calculated the expected value of partial perfect information (EVPPI) using both the conventional nested Monte Carlo approach and the GAM approach. EVSI was calculated using the GAM approach. For all 3 case studies, the GAM approach consistently gave similar estimates of EVPPI compared with the conventional approach. The EVSI behaved as expected: it increased and converged to EVPPI for larger sample sizes. For each case study, generating the PSA results for the GAM approach required 3 to 4 days on a shared cluster, after which EVPPI and EVSI across a range of sample sizes were evaluated in minutes. The conventional approach required approximately 5 weeks for the EVPPI calculation alone. Estimating EVSI using the GAM approach with results from a PSA dramatically reduced the time required to conduct a computationally intense project, which would otherwise have been impractical. Using the GAM approach, we can efficiently provide policy makers with EVSI estimates, even for complex patient-level microsimulation models.

  1. Study of the association of atmospheric temperature and relative humidity with bulk tank milk somatic cell count in dairy herds using Generalized additive mixed models.

    Science.gov (United States)

    Testa, Francesco; Marano, Giuseppe; Ambrogi, Federico; Boracchi, Patrizia; Casula, Antonio; Biganzoli, Elia; Moroni, Paolo

    2017-10-01

    Elevated bulk tank milk somatic cell count (BMSCC) has a negative impact on milk production, milk quality, and animal health. Seasonal increases in herd level somatic cell count (SCC) are commonly associated with elevated environmental temperature and humidity. The Temperature Humidity Index (THI) has been developed to measure general environmental stress in dairy cattle; however, additional work is needed to determine a specific effect of the heat stress index on herd-level SCC. Generalized Additive Model methods were used for a flexible exploration of the relationships between daily temperature, relative humidity, and bulk milk somatic cell count. The data consist of BMSCC and meteorological recordings collected between March 2009 and October 2011 of 10 dairy farms. The results indicate that, an average increase of 0.16% of BMSCC is expected for an increase of 1°C degree of temperature. A complex relationship was found for relative humidity. For example, increase of 0.099%, 0.037% and 0.020% are expected in correspondence to an increase of relative humidity from 50% to 51%, 80% to 81%; and 90% to 91%, respectively. Using this model, it will be possible to provide evidence-based advice to dairy farmers for the use of THI control charts created on the basis of our statistical model. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques

    Science.gov (United States)

    Chen, Wei; Pourghasemi, Hamid Reza; Panahi, Mahdi; Kornejady, Aiding; Wang, Jiale; Xie, Xiaoshen; Cao, Shubo

    2017-11-01

    The spatial prediction of landslide susceptibility is an important prerequisite for the analysis of landslide hazards and risks in any area. This research uses three data mining techniques, such as an adaptive neuro-fuzzy inference system combined with frequency ratio (ANFIS-FR), a generalized additive model (GAM), and a support vector machine (SVM), for landslide susceptibility mapping in Hanyuan County, China. In the first step, in accordance with a review of the previous literature, twelve conditioning factors, including slope aspect, altitude, slope angle, topographic wetness index (TWI), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, land use, normalized difference vegetation index (NDVI), and lithology, were selected. In the second step, a collinearity test and correlation analysis between the conditioning factors and landslides were applied. In the third step, we used three advanced methods, namely, ANFIS-FR, GAM, and SVM, for landslide susceptibility modeling. Subsequently, the results of their accuracy were validated using a receiver operating characteristic curve. The results showed that all three models have good prediction capabilities, while the SVM model has the highest prediction rate of 0.875, followed by the ANFIS-FR and GAM models with prediction rates of 0.851 and 0.846, respectively. Thus, the landslide susceptibility maps produced in the study area can be applied for management of hazards and risks in landslide-prone Hanyuan County.

  3. Spatial prediction of Soil Organic Carbon contents in croplands, grasslands and forests using environmental covariates and Generalized Additive Models (Southern Belgium)

    Science.gov (United States)

    Chartin, Caroline; Stevens, Antoine; van Wesemael, Bas

    2015-04-01

    Providing spatially continuous Soil Organic Carbon data (SOC) is needed to support decisions regarding soil management, and inform the political debate with quantified estimates of the status and change of the soil resource. Digital Soil Mapping techniques are based on relations existing between a soil parameter (measured at different locations in space at a defined period) and relevant covariates (spatially continuous data) that are factors controlling soil formation and explaining the spatial variability of the target variable. This study aimed at apply DSM techniques to recent SOC content measurements (2005-2013) in three different landuses, i.e. cropland, grassland, and forest, in the Walloon region (Southern Belgium). For this purpose, SOC databases of two regional Soil Monitoring Networks (CARBOSOL for croplands and grasslands, and IPRFW for forests) were first harmonized, totalising about 1,220 observations. Median values of SOC content for croplands, grasslands, and forests, are respectively of 12.8, 29.0, and 43.1 g C kg-1. Then, a set of spatial layers were prepared with a resolution of 40 meters and with the same grid topology, containing environmental covariates such as, landuses, Digital Elevation Model and its derivatives, soil texture, C factor, carbon inputs by manure, and climate. Here, in addition to the three classical texture classes (clays, silt, and sand), we tested the use of clays + fine silt content (particles < 20 µm and related to stable carbon fraction) as soil covariate explaining SOC variations. For each of the three land uses (cropland, grassland and forest), a Generalized Additive Model (GAM) was calibrated on two thirds of respective dataset. The remaining samples were assigned to a test set to assess model performance. A backward stepwise procedure was followed to select the relevant environmental covariates using their approximate p-values (the level of significance was set at p < 0.05). Standard errors were estimated for each of

  4. Spatial analysis of lung, colorectal, and breast cancer on Cape Cod: An application of generalized additive models to case-control data

    Directory of Open Access Journals (Sweden)

    Aschengrau Ann

    2005-06-01

    Full Text Available Abstract Background The availability of geographic information from cancer and birth defect registries has increased public demands for investigation of perceived disease clusters. Many neighborhood-level cluster investigations are methodologically problematic, while maps made from registry data often ignore latency and many known risk factors. Population-based case-control and cohort studies provide a stronger foundation for spatial epidemiology because potential confounders and disease latency can be addressed. Methods We investigated the association between residence and colorectal, lung, and breast cancer on upper Cape Cod, Massachusetts (USA using extensive data on covariates and residential history from two case-control studies for 1983–1993. We generated maps using generalized additive models, smoothing on longitude and latitude while adjusting for covariates. The resulting continuous surface estimates disease rates relative to the whole study area. We used permutation tests to examine the overall importance of location in the model and identify areas of increased and decreased risk. Results Maps of colorectal cancer were relatively flat. Assuming 15 years of latency, lung cancer was significantly elevated just northeast of the Massachusetts Military Reservation, although the result did not hold when we restricted to residences of longest duration. Earlier non-spatial epidemiology had found a weak association between lung cancer and proximity to gun and mortar positions on the reservation. Breast cancer hot spots tended to increase in magnitude as we increased latency and adjusted for covariates, indicating that confounders were partly hiding these areas. Significant breast cancer hot spots were located near known groundwater plumes and the Massachusetts Military Reservation. Discussion Spatial epidemiology of population-based case-control studies addresses many methodological criticisms of cluster studies and generates new exposure

  5. The influence of environmental variables on the presence of white sharks, Carcharodon carcharias at two popular Cape Town bathing beaches: a generalized additive mixed model.

    Directory of Open Access Journals (Sweden)

    Kay Weltz

    Full Text Available Shark attacks on humans are high profile events which can significantly influence policies related to the coastal zone. A shark warning system in South Africa, Shark Spotters, recorded 378 white shark (Carcharodon carcharias sightings at two popular beaches, Fish Hoek and Muizenberg, during 3690 six-hour long spotting shifts, during the months September to May 2006 to 2011. The probabilities of shark sightings were related to environmental variables using Binomial Generalized Additive Mixed Models (GAMMs. Sea surface temperature was significant, with the probability of shark sightings increasing rapidly as SST exceeded 14 °C and approached a maximum at 18 °C, whereafter it remains high. An 8 times (Muizenberg and 5 times (Fish Hoek greater likelihood of sighting a shark was predicted at 18 °C than at 14 °C. Lunar phase was also significant with a prediction of 1.5 times (Muizenberg and 4 times (Fish Hoek greater likelihood of a shark sighting at new moon than at full moon. At Fish Hoek, the probability of sighting a shark was 1.6 times higher during the afternoon shift compared to the morning shift, but no diel effect was found at Muizenberg. A significant increase in the number of shark sightings was identified over the last three years, highlighting the need for ongoing research into shark attack mitigation. These patterns will be incorporated into shark awareness and bather safety campaigns in Cape Town.

  6. A combined approach of generalized additive model and bootstrap with small sample sets for fault diagnosis in fermentation process of glutamate.

    Science.gov (United States)

    Liu, Chunbo; Pan, Feng; Li, Yun

    2016-07-29

    Glutamate is of great importance in food and pharmaceutical industries. There is still lack of effective statistical approaches for fault diagnosis in the fermentation process of glutamate. To date, the statistical approach based on generalized additive model (GAM) and bootstrap has not been used for fault diagnosis in fermentation processes, much less the fermentation process of glutamate with small samples sets. A combined approach of GAM and bootstrap was developed for the online fault diagnosis in the fermentation process of glutamate with small sample sets. GAM was first used to model the relationship between glutamate production and different fermentation parameters using online data from four normal fermentation experiments of glutamate. The fitted GAM with fermentation time, dissolved oxygen, oxygen uptake rate and carbon dioxide evolution rate captured 99.6 % variance of glutamate production during fermentation process. Bootstrap was then used to quantify the uncertainty of the estimated production of glutamate from the fitted GAM using 95 % confidence interval. The proposed approach was then used for the online fault diagnosis in the abnormal fermentation processes of glutamate, and a fault was defined as the estimated production of glutamate fell outside the 95 % confidence interval. The online fault diagnosis based on the proposed approach identified not only the start of the fault in the fermentation process, but also the end of the fault when the fermentation conditions were back to normal. The proposed approach only used a small sample sets from normal fermentations excitements to establish the approach, and then only required online recorded data on fermentation parameters for fault diagnosis in the fermentation process of glutamate. The proposed approach based on GAM and bootstrap provides a new and effective way for the fault diagnosis in the fermentation process of glutamate with small sample sets.

  7. Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

    Science.gov (United States)

    Coupé, Christophe

    2018-01-01

    As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we

  8. Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

    Directory of Open Access Journals (Sweden)

    Christophe Coupé

    2018-04-01

    Full Text Available As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM, which address grouping of observations, and generalized linear mixed-effects models (GLMM, which offer a family of distributions for the dependent variable. Generalized additive models (GAM are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS. We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships

  9. Estimating PM2.5 Concentrations in Xi'an City Using a Generalized Additive Model with Multi-Source Monitoring Data.

    Directory of Open Access Journals (Sweden)

    Yong-Ze Song

    Full Text Available Particulate matter with an aerodynamic diameter <2.5 μm (PM2.5 represents a severe environmental problem and is of negative impact on human health. Xi'an City, with a population of 6.5 million, is among the highest concentrations of PM2.5 in China. In 2013, in total, there were 191 days in Xi'an City on which PM2.5 concentrations were greater than 100 μg/m3. Recently, a few studies have explored the potential causes of high PM2.5 concentration using remote sensing data such as the MODIS aerosol optical thickness (AOT product. Linear regression is a commonly used method to find statistical relationships among PM2.5 concentrations and other pollutants, including CO, NO2, SO2, and O3, which can be indicative of emission sources. The relationships of these variables, however, are usually complicated and non-linear. Therefore, a generalized additive model (GAM is used to estimate the statistical relationships between potential variables and PM2.5 concentrations. This model contains linear functions of SO2 and CO, univariate smoothing non-linear functions of NO2, O3, AOT and temperature, and bivariate smoothing non-linear functions of location and wind variables. The model can explain 69.50% of PM2.5 concentrations, with R2 = 0.691, which improves the result of a stepwise linear regression (R2 = 0.582 by 18.73%. The two most significant variables, CO concentration and AOT, represent 20.65% and 19.54% of the deviance, respectively, while the three other gas-phase concentrations, SO2, NO2, and O3 account for 10.88% of the total deviance. These results show that in Xi'an City, the traffic and other industrial emissions are the primary source of PM2.5. Temperature, location, and wind variables also non-linearly related with PM2.5.

  10. Business models for additive manufacturing

    DEFF Research Database (Denmark)

    Hadar, Ronen; Bilberg, Arne; Bogers, Marcel

    2015-01-01

    Digital fabrication — including additive manufacturing (AM), rapid prototyping and 3D printing — has the potential to revolutionize the way in which products are produced and delivered to the customer. Therefore, it challenges companies to reinvent their business model — describing the logic...... of creating and capturing value. In this paper, we explore the implications that AM technologies have for manufacturing systems in the new business models that they enable. In particular, we consider how a consumer goods manufacturer can organize the operations of a more open business model when moving from...... a manufacturer-centric to a consumer-centric value logic. A major shift includes a move from centralized to decentralized supply chains, where consumer goods manufacturers can implement a “hybrid” approach with a focus on localization and accessibility or develop a fully personalized model where the consumer...

  11. The General Aggression Model

    NARCIS (Netherlands)

    Allen, Johnie J.; Anderson, Craig A.; Bushman, Brad J.

    The General Aggression Model (GAM) is a comprehensive, integrative, framework for understanding aggression. It considers the role of social, cognitive, personality, developmental, and biological factors on aggression. Proximate processes of GAM detail how person and situation factors influence

  12. Generalization of boson-fermion equivalence and Fay's addition theorem

    International Nuclear Information System (INIS)

    Kato, Hideyuki; Saito, Satoru

    1989-01-01

    Generalizations of Fay's addition theorem for Abel functions are obtained by using generalized boson-fermion equivalence of off-shell string amplitudes. A simple example of such generalizations is presented explicitly which relates derivatives of a Riemann θ-function to its determinant. (orig.)

  13. The generalized circular model

    NARCIS (Netherlands)

    Webers, H.M.

    1995-01-01

    In this paper we present a generalization of the circular model. In this model there are two concentric circular markets, which enables us to study two types of markets simultaneously. There are switching costs involved for moving from one circle to the other circle, which can also be thought of as

  14. Generalized Nonlinear Yule Models

    OpenAIRE

    Lansky, Petr; Polito, Federico; Sacerdote, Laura

    2016-01-01

    With the aim of considering models with persistent memory we propose a fractional nonlinear modification of the classical Yule model often studied in the context of macrovolution. Here the model is analyzed and interpreted in the framework of the development of networks such as the World Wide Web. Nonlinearity is introduced by replacing the linear birth process governing the growth of the in-links of each specific webpage with a fractional nonlinear birth process with completely general birth...

  15. Generalized Nonlinear Yule Models

    Science.gov (United States)

    Lansky, Petr; Polito, Federico; Sacerdote, Laura

    2016-11-01

    With the aim of considering models related to random graphs growth exhibiting persistent memory, we propose a fractional nonlinear modification of the classical Yule model often studied in the context of macroevolution. Here the model is analyzed and interpreted in the framework of the development of networks such as the World Wide Web. Nonlinearity is introduced by replacing the linear birth process governing the growth of the in-links of each specific webpage with a fractional nonlinear birth process with completely general birth rates. Among the main results we derive the explicit distribution of the number of in-links of a webpage chosen uniformly at random recognizing the contribution to the asymptotics and the finite time correction. The mean value of the latter distribution is also calculated explicitly in the most general case. Furthermore, in order to show the usefulness of our results, we particularize them in the case of specific birth rates giving rise to a saturating behaviour, a property that is often observed in nature. The further specialization to the non-fractional case allows us to extend the Yule model accounting for a nonlinear growth.

  16. The general dynamic model

    DEFF Research Database (Denmark)

    Borregaard, Michael K.; Matthews, Thomas J.; Whittaker, Robert James

    2016-01-01

    Aim: Island biogeography focuses on understanding the processes that underlie a set of well-described patterns on islands, but it lacks a unified theoretical framework for integrating these processes. The recently proposed general dynamic model (GDM) of oceanic island biogeography offers a step...... towards this goal. Here, we present an analysis of causality within the GDM and investigate its potential for the further development of island biogeographical theory. Further, we extend the GDM to include subduction-based island arcs and continental fragment islands. Location: A conceptual analysis...... of evolutionary processes in simulations derived from the mechanistic assumptions of the GDM corresponded broadly to those initially suggested, with the exception of trends in extinction rates. Expanding the model to incorporate different scenarios of island ontogeny and isolation revealed a sensitivity...

  17. Anomaly General Circulation Models.

    Science.gov (United States)

    Navarra, Antonio

    The feasibility of the anomaly model is assessed using barotropic and baroclinic models. In the barotropic case, both a stationary and a time-dependent model has been formulated and constructed, whereas only the stationary, linear case is considered in the baroclinic case. Results from the barotropic model indicate that a relation between the stationary solution and the time-averaged non-linear solution exists. The stationary linear baroclinic solution can therefore be considered with some confidence. The linear baroclinic anomaly model poses a formidable mathematical problem because it is necessary to solve a gigantic linear system to obtain the solution. A new method to find solution of large linear system, based on a projection on the Krylov subspace is shown to be successful when applied to the linearized baroclinic anomaly model. The scheme consists of projecting the original linear system on the Krylov subspace, thereby reducing the dimensionality of the matrix to be inverted to obtain the solution. With an appropriate setting of the damping parameters, the iterative Krylov method reaches a solution even using a Krylov subspace ten times smaller than the original space of the problem. This generality allows the treatment of the important problem of linear waves in the atmosphere. A larger class (nonzonally symmetric) of basic states can now be treated for the baroclinic primitive equations. These problem leads to large unsymmetrical linear systems of order 10000 and more which can now be successfully tackled by the Krylov method. The (R7) linear anomaly model is used to investigate extensively the linear response to equatorial and mid-latitude prescribed heating. The results indicate that the solution is deeply affected by the presence of the stationary waves in the basic state. The instability of the asymmetric flows, first pointed out by Simmons et al. (1983), is active also in the baroclinic case. However, the presence of baroclinic processes modifies the

  18. The General Aggression Model.

    Science.gov (United States)

    Allen, Johnie J; Anderson, Craig A; Bushman, Brad J

    2018-02-01

    The General Aggression Model (GAM) is a comprehensive, integrative, framework for understanding aggression. It considers the role of social, cognitive, personality, developmental, and biological factors on aggression. Proximate processes of GAM detail how person and situation factors influence cognitions, feelings, and arousal, which in turn affect appraisal and decision processes, which in turn influence aggressive or nonaggressive behavioral outcomes. Each cycle of the proximate processes serves as a learning trial that affects the development and accessibility of aggressive knowledge structures. Distal processes of GAM detail how biological and persistent environmental factors can influence personality through changes in knowledge structures. GAM has been applied to understand aggression in many contexts including media violence effects, domestic violence, intergroup violence, temperature effects, pain effects, and the effects of global climate change. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. The generalized collective model

    International Nuclear Information System (INIS)

    Troltenier, D.

    1992-07-01

    In this thesis a new way of proceeding, basing on the method of the finite elements, for the solution of the collective Schroedinger equation in the framework of the Generalized Collective Model was presented. The numerically reachable accuracy was illustrated by the comparison to analytically known solutions by means of numerous examples. Furthermore the potential-energy surfaces of the 182-196 Hg, 242-248 Cm, and 242-246 Pu isotopes were determined by the fitting of the parameters of the Gneuss-Greiner potential to the experimental data. In the Hg isotopes a shape consistency of nearly spherical and oblate deformations is shown, while the Cm and Pu isotopes possess an essentially equal remaining prolate deformation. By means of the pseudo-symplectic model the potential-energy surfaces of 24 Mg, 190 Pt, and 238 U were microscopically calculated. Using a deformation-independent kinetic energy so the collective excitation spectra and the electrical properties (B(E2), B(E4) values, quadrupole moments) of these nuclei were calculated and compared with the experiment. Finally an analytic relation between the (g R -Z/A) value and the quadrupole moment was derived. The study of the experimental data of the 166-170 Er isotopes shows an in the framework of the measurement accuracy a sufficient agreement with this relation. Furthermore it is by this relation possible to determine the effective magnetic dipole moment parameter-freely. (orig./HSI) [de

  20. Glauber model and its generalizations

    International Nuclear Information System (INIS)

    Bialkowski, G.

    The physical aspects of the Glauber model problems are studied: potential model, profile function and Feynman diagrams approaches. Different generalizations of the Glauber model are discussed: particularly higher and lower energy processes and large angles [fr

  1. Multivariate generalized linear mixed models using R

    CERN Document Server

    Berridge, Damon Mark

    2011-01-01

    Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model...

  2. Generalized Markov branching models

    OpenAIRE

    Li, Junping

    2005-01-01

    In this thesis, we first considered a modified Markov branching process incorporating both state-independent immigration and resurrection. After establishing the criteria for regularity and uniqueness, explicit expressions for the extinction probability and mean extinction time are presented. The criteria for recurrence and ergodicity are also established. In addition, an explicit expression for the equilibrium distribution is presented.\\ud \\ud We then moved on to investigate the basic proper...

  3. Generalized, Linear, and Mixed Models

    CERN Document Server

    McCulloch, Charles E; Neuhaus, John M

    2011-01-01

    An accessible and self-contained introduction to statistical models-now in a modernized new editionGeneralized, Linear, and Mixed Models, Second Edition provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified coverage of the theory behind generalized, linear, and mixed models and highlights their similarities and differences in various construction, application, and computational aspects.A clear introduction to the basic ideas of fixed effects models, random effects models, and mixed m

  4. 21 CFR 70.5 - General restrictions on use of color additives.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 1 2010-04-01 2010-04-01 false General restrictions on use of color additives. 70... GENERAL COLOR ADDITIVES General Provisions § 70.5 General restrictions on use of color additives. (a) Color additives for use in the area of the eye. No listing or certification of a color additive shall be...

  5. Introduction to generalized linear models

    CERN Document Server

    Dobson, Annette J

    2008-01-01

    Introduction Background Scope Notation Distributions Related to the Normal Distribution Quadratic Forms Estimation Model Fitting Introduction Examples Some Principles of Statistical Modeling Notation and Coding for Explanatory Variables Exponential Family and Generalized Linear Models Introduction Exponential Family of Distributions Properties of Distributions in the Exponential Family Generalized Linear Models Examples Estimation Introduction Example: Failure Times for Pressure Vessels Maximum Likelihood Estimation Poisson Regression Example Inference Introduction Sampling Distribution for Score Statistics Taylor Series Approximations Sampling Distribution for MLEs Log-Likelihood Ratio Statistic Sampling Distribution for the Deviance Hypothesis Testing Normal Linear Models Introduction Basic Results Multiple Linear Regression Analysis of Variance Analysis of Covariance General Linear Models Binary Variables and Logistic Regression Probability Distributions ...

  6. Generalized Ordinary Differential Equation Models.

    Science.gov (United States)

    Miao, Hongyu; Wu, Hulin; Xue, Hongqi

    2014-10-01

    Existing estimation methods for ordinary differential equation (ODE) models are not applicable to discrete data. The generalized ODE (GODE) model is therefore proposed and investigated for the first time. We develop the likelihood-based parameter estimation and inference methods for GODE models. We propose robust computing algorithms and rigorously investigate the asymptotic properties of the proposed estimator by considering both measurement errors and numerical errors in solving ODEs. The simulation study and application of our methods to an influenza viral dynamics study suggest that the proposed methods have a superior performance in terms of accuracy over the existing ODE model estimation approach and the extended smoothing-based (ESB) method.

  7. Cosmological models in general relativity

    Indian Academy of Sciences (India)

    Cosmological models in general relativity. B B PAUL. Department of Physics, Nowgong College, Nagaon, Assam, India. MS received 4 October 2002; revised 6 March 2003; accepted 21 May 2003. Abstract. LRS Bianchi type-I space-time filled with perfect fluid is considered here with deceler- ation parameter as variable.

  8. 21 CFR 172.5 - General provisions for direct food additives.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 3 2010-04-01 2009-04-01 true General provisions for direct food additives. 172.5... (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) FOOD ADDITIVES PERMITTED FOR DIRECT ADDITION TO FOOD FOR HUMAN CONSUMPTION General Provisions § 172.5 General provisions for direct food additives. (a...

  9. Additive action model for mixed irradiation

    International Nuclear Information System (INIS)

    Lam, G.K.Y.

    1984-01-01

    Recent experimental results indicate that a mixture of high and low LET radiation may have some beneficial features (such as lower OER but with skin sparing) for clinical use, and interest has been renewed in the study of mixtures of high and low LET radiation. Several standard radiation inactivation models can readily accommodate interaction between two mixed radiations, however, this is usually handled by postulating extra free parameters, which can only be determined by fitting to experimental data. A model without any free parameter is proposed to explain the biological effect of mixed radiations, based on the following two assumptions: (a) The combined biological action due to two radiations is additive, assuming no repair has taken place during the interval between the two irradiations; and (b) The initial physical damage induced by radiation develops into final biological effect (e.g. cell killing) over a relatively long period (hours) after irradiation. This model has been shown to provide satisfactory fit to the experiment results of previous studies

  10. Computational Process Modeling for Additive Manufacturing (OSU)

    Science.gov (United States)

    Bagg, Stacey; Zhang, Wei

    2015-01-01

    Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

  11. A ¤flexible additive multiplicative hazard model

    DEFF Research Database (Denmark)

    Martinussen, T.; Scheike, T. H.

    2002-01-01

    Aalen's additive model; Counting process; Cox regression; Hazard model; Proportional excess harzard model; Time-varying effect......Aalen's additive model; Counting process; Cox regression; Hazard model; Proportional excess harzard model; Time-varying effect...

  12. Generalized waste package containment model

    International Nuclear Information System (INIS)

    Liebetrau, A.M.; Apted, M.J.

    1985-02-01

    The US Department of Energy (DOE) is developing a performance assessment strategy to demonstrate compliance with standards and technical requirements of the Environmental Protection Agency (EPA) and the Nuclear Regulatory Commission (NRC) for the permanent disposal of high-level nuclear wastes in geologic repositories. One aspect of this strategy is the development of a unified performance model of the entire geologic repository system. Details of a generalized waste package containment (WPC) model and its relationship with other components of an overall repository model are presented in this paper. The WPC model provides stochastically determined estimates of the distributions of times-to-failure of the barriers of a waste package by various corrosion mechanisms and degradation processes. The model consists of a series of modules which employ various combinations of stochastic (probabilistic) and mechanistic process models, and which are individually designed to reflect the current state of knowledge. The WPC model is designed not only to take account of various site-specific conditions and processes, but also to deal with a wide range of site, repository, and waste package configurations. 11 refs., 3 figs., 2 tabs

  13. Multivariate covariance generalized linear models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Jørgensen, Bent

    2016-01-01

    are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...

  14. Fermions as generalized Ising models

    Directory of Open Access Journals (Sweden)

    C. Wetterich

    2017-04-01

    Full Text Available We establish a general map between Grassmann functionals for fermions and probability or weight distributions for Ising spins. The equivalence between the two formulations is based on identical transfer matrices and expectation values of products of observables. The map preserves locality properties and can be realized for arbitrary dimensions. We present a simple example where a quantum field theory for free massless Dirac fermions in two-dimensional Minkowski space is represented by an asymmetric Ising model on a euclidean square lattice.

  15. Anisotropic charged generalized polytropic models

    Science.gov (United States)

    Nasim, A.; Azam, M.

    2018-06-01

    In this paper, we found some new anisotropic charged models admitting generalized polytropic equation of state with spherically symmetry. An analytic solution of the Einstein-Maxwell field equations is obtained through the transformation introduced by Durgapal and Banerji (Phys. Rev. D 27:328, 1983). The physical viability of solutions corresponding to polytropic index η =1/2, 2/3, 1, 2 is analyzed graphically. For this, we plot physical quantities such as radial and tangential pressure, anisotropy, speed of sound which demonstrated that these models achieve all the considerable physical conditions required for a relativistic star. Further, it is mentioned here that previous results for anisotropic charged matter with linear, quadratic and polytropic equation of state can be retrieved.

  16. 21 CFR 174.5 - General provisions applicable to indirect food additives.

    Science.gov (United States)

    2010-04-01

    ... additives. 174.5 Section 174.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) INDIRECT FOOD ADDITIVES: GENERAL § 174.5 General provisions applicable to indirect food additives. (a) Regulations prescribing conditions under...

  17. 75 FR 30844 - General Mills, Inc.; Withdrawal of Food Additive Petition

    Science.gov (United States)

    2010-06-02

    ...] (formerly Docket No. 2007F-0454) General Mills, Inc.; Withdrawal of Food Additive Petition AGENCY: Food and... 7M4770) had been filed by General Mills, Inc., One General Mills Blvd., Minneapolis, MN 55426. The... use in food production. General Mills, Inc., has now withdrawn the petition without prejudice to a...

  18. Average bit error probability of binary coherent signaling over generalized fading channels subject to additive generalized gaussian noise

    KAUST Repository

    Soury, Hamza

    2012-06-01

    This letter considers the average bit error probability of binary coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closed form expression in terms of the Fox\\'s H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading and Nakagami-m fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters. © 2012 IEEE.

  19. Exact Symbol Error Probability of Square M-QAM Signaling over Generalized Fading Channels subject to Additive Generalized Gaussian Noise

    KAUST Repository

    Soury, Hamza

    2013-07-01

    This paper considers the average symbol error probability of square Quadrature Amplitude Modulation (QAM) coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closedform expression in terms of the Fox H function and the bivariate Fox H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading, Nakagami-m fading, and Rayleigh fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters.

  20. An Additive-Multiplicative Cox-Aalen Regression Model

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects...

  1. Generalized model of island biodiversity

    Science.gov (United States)

    Kessler, David A.; Shnerb, Nadav M.

    2015-04-01

    The dynamics of a local community of competing species with weak immigration from a static regional pool is studied. Implementing the generalized competitive Lotka-Volterra model with demographic noise, a rich dynamics with four qualitatively distinct phases is unfolded. When the overall interspecies competition is weak, the island species recapitulate the mainland species. For higher values of the competition parameter, the system still admits an equilibrium community, but now some of the mainland species are absent on the island. Further increase in competition leads to an intermittent "disordered" phase, where the dynamics is controlled by invadable combinations of species and the turnover rate is governed by the migration. Finally, the strong competition phase is glasslike, dominated by uninvadable states and noise-induced transitions. Our model contains, as a special case, the celebrated neutral island theories of Wilson-MacArthur and Hubbell. Moreover, we show that slight deviations from perfect neutrality may lead to each of the phases, as the Hubbell point appears to be quadracritical.

  2. 21 CFR 170.20 - General principles for evaluating the safety of food additives.

    Science.gov (United States)

    2010-04-01

    ... food additives. 170.20 Section 170.20 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) FOOD ADDITIVES Food Additive Safety § 170.20 General principles for evaluating the safety of food additives. (a) In reaching a...

  3. 21 CFR 570.20 - General principles for evaluating the safety of food additives.

    Science.gov (United States)

    2010-04-01

    ... food additives. 570.20 Section 570.20 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) ANIMAL DRUGS, FEEDS, AND RELATED PRODUCTS FOOD ADDITIVES Food Additive Safety § 570.20 General principles for evaluating the safety of food additives. (a) In reaching a...

  4. Current definition and a generalized federbush model

    International Nuclear Information System (INIS)

    Singh, L.P.S.; Hagen, C.R.

    1978-01-01

    The Federbush model is studied, with particular attention being given to the definition of currents. Inasmuch as there is no a priori restriction of local gauge invariance, the currents in the interacting case can be defined more generally than in Q.E.D. It is found that two arbitrary parameters are thereby introduced into the theory. Lowest order perturbation calculations for the current correlation functions and the Fermion propagators indicate that the theory admits a whole class of solutions dependent upon these parameters with the closed solution of Federbush emerging as a special case. The theory is shown to be locally covariant, and a conserved energy--momentum tensor is displayed. One finds in addition that the generators of gauge transformations for the fields are conserved. Finally it is shown that the general theory yields the Federbush solution if suitable Thirring model type counterterms are added

  5. Generalized concentration addition: a method for examining mixtures containing partial agonists.

    Science.gov (United States)

    Howard, Gregory J; Webster, Thomas F

    2009-08-07

    Environmentally relevant toxic exposures often consist of simultaneous exposure to multiple agents. Methods to predict the expected outcome of such combinations are critical both to risk assessment and to an accurate judgment of whether combinations are synergistic or antagonistic. Concentration addition (CA) has commonly been used to assess the presence of synergy or antagonism in combinations of similarly acting chemicals, and to predict effects of combinations of such agents. CA has the advantage of clear graphical interpretation: Curves of constant joint effect (isoboles) must be negatively sloped straight lines if the mixture is concentration additive. However, CA cannot be directly used to assess combinations that include partial agonists, although such agents are of considerable interest. Here, we propose a natural extension of CA to a functional form that may be applied to mixtures including full agonists and partial agonists. This extended definition, for which we suggest the term "generalized concentration addition," encompasses linear isoboles with slopes of any sign. We apply this approach to the simple example of agents with dose-response relationships described by Hill functions with slope parameter n=1. The resulting isoboles are in all cases linear, with negative, zero and positive slopes. Using simple mechanistic models of ligand-receptor systems, we show that the same isobole pattern and joint effects are generated by modeled combinations of full and partial agonists. Special cases include combinations of two full agonists and a full agonist plus a competitive antagonist.

  6. Just Another Gibbs Additive Modeler: Interfacing JAGS and mgcv

    Directory of Open Access Journals (Sweden)

    Simon N. Wood

    2016-12-01

    Full Text Available The BUGS language offers a very flexible way of specifying complex statistical models for the purposes of Gibbs sampling, while its JAGS variant offers very convenient R integration via the rjags package. However, including smoothers in JAGS models can involve some quite tedious coding, especially for multivariate or adaptive smoothers. Further, if an additive smooth structure is required then some care is needed, in order to centre smooths appropriately, and to find appropriate starting values. R package mgcv implements a wide range of smoothers, all in a manner appropriate for inclusion in JAGS code, and automates centring and other smooth setup tasks. The purpose of this note is to describe an interface between mgcv and JAGS, based around an R function, jagam, which takes a generalized additive model (GAM as specified in mgcv and automatically generates the JAGS model code and data required for inference about the model via Gibbs sampling. Although the auto-generated JAGS code can be run as is, the expectation is that the user would wish to modify it in order to add complex stochastic model components readily specified in JAGS. A simple interface is also provided for visualisation and further inference about the estimated smooth components using standard mgcv functionality. The methods described here will be un-necessarily inefficient if all that is required is fully Bayesian inference about a standard GAM, rather than the full flexibility of JAGS. In that case the BayesX package would be more efficient.

  7. Generalized complex geometry, generalized branes and the Hitchin sigma model

    International Nuclear Information System (INIS)

    Zucchini, Roberto

    2005-01-01

    Hitchin's generalized complex geometry has been shown to be relevant in compactifications of superstring theory with fluxes and is expected to lead to a deeper understanding of mirror symmetry. Gualtieri's notion of generalized complex submanifold seems to be a natural candidate for the description of branes in this context. Recently, we introduced a Batalin-Vilkovisky field theoretic realization of generalized complex geometry, the Hitchin sigma model, extending the well known Poisson sigma model. In this paper, exploiting Gualtieri's formalism, we incorporate branes into the model. A detailed study of the boundary conditions obeyed by the world sheet fields is provided. Finally, it is found that, when branes are present, the classical Batalin-Vilkovisky cohomology contains an extra sector that is related non trivially to a novel cohomology associated with the branes as generalized complex submanifolds. (author)

  8. General introduction to simulation models

    DEFF Research Database (Denmark)

    Hisham Beshara Halasa, Tariq; Boklund, Anette

    2012-01-01

    trials. However, if simulation models would be used, good quality input data must be available. To model FMD, several disease spread models are available. For this project, we chose three simulation model; Davis Animal Disease Spread (DADS), that has been upgraded to DTU-DADS, InterSpread Plus (ISP......Monte Carlo simulation can be defined as a representation of real life systems to gain insight into their functions and to investigate the effects of alternative conditions or actions on the modeled system. Models are a simplification of a system. Most often, it is best to use experiments and field...... trials to investigate the effect of alternative conditions or actions on a specific system. Nonetheless, field trials are expensive and sometimes not possible to conduct, as in case of foot-and-mouth disease (FMD). Instead, simulation models can be a good and cheap substitute for experiments and field...

  9. Generalized latent variable modeling multilevel, longitudinal, and structural equation models

    CERN Document Server

    Skrondal, Anders; Rabe-Hesketh, Sophia

    2004-01-01

    This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.

  10. General Pressurization Model in Simscape

    Science.gov (United States)

    Servin, Mario; Garcia, Vicky

    2010-01-01

    System integration is an essential part of the engineering design process. The Ares I Upper Stage (US) is a complex system which is made up of thousands of components assembled into subsystems including a J2-X engine, liquid hydrogen (LH2) and liquid oxygen (LO2) tanks, avionics, thrust vector control, motors, etc. System integration is the task of connecting together all of the subsystems into one large system. To ensure that all the components will "fit together" as well as safety and, quality, integration analysis is required. Integration analysis verifies that, as an integrated system, the system will behave as designed. Models that represent the actual subsystems are built for more comprehensive analysis. Matlab has been an instrument widely use by engineers to construct mathematical models of systems. Simulink, one of the tools offered by Matlab, provides multi-domain graphical environment to simulate and design time-varying systems. Simulink is a powerful tool to analyze the dynamic behavior of systems over time. Furthermore, Simscape, a tool provided by Simulink, allows users to model physical (such as mechanical, thermal and hydraulic) systems using physical networks. Using Simscape, a model representing an inflow of gas to a pressurized tank was created where the temperature and pressure of the tank are measured over time to show the behavior of the gas. By further incorporation of Simscape into model building, the full potential of this software can be discovered and it hopefully can become a more utilized tool.

  11. Process generalization in conceptual models

    NARCIS (Netherlands)

    Wieringa, Roelf J.

    In conceptual modeling, the universe of discourse (UoD) is divided into classes which have a taxonomic structure. The classes are usually defined in terms of attributes (all objects in a class share attribute names) and possibly of events. For enmple, the class of employees is the set of objects to

  12. Vector models and generalized SYK models

    Energy Technology Data Exchange (ETDEWEB)

    Peng, Cheng [Department of Physics, Brown University,Providence RI 02912 (United States)

    2017-05-23

    We consider the relation between SYK-like models and vector models by studying a toy model where a tensor field is coupled with a vector field. By integrating out the tensor field, the toy model reduces to the Gross-Neveu model in 1 dimension. On the other hand, a certain perturbation can be turned on and the toy model flows to an SYK-like model at low energy. A chaotic-nonchaotic phase transition occurs as the sign of the perturbation is altered. We further study similar models that possess chaos and enhanced reparameterization symmetries.

  13. Testing the generalized partial credit model

    OpenAIRE

    Glas, Cornelis A.W.

    1996-01-01

    The partial credit model (PCM) (G.N. Masters, 1982) can be viewed as a generalization of the Rasch model for dichotomous items to the case of polytomous items. In many cases, the PCM is too restrictive to fit the data. Several generalizations of the PCM have been proposed. In this paper, a generalization of the PCM (GPCM), a further generalization of the one-parameter logistic model, is discussed. The model is defined and the conditional maximum likelihood procedure for the method is describe...

  14. Further Results on Dynamic Additive Hazard Rate Model

    Directory of Open Access Journals (Sweden)

    Zhengcheng Zhang

    2014-01-01

    Full Text Available In the past, the proportional and additive hazard rate models have been investigated in the works. Nanda and Das (2011 introduced and studied the dynamic proportional (reversed hazard rate model. In this paper we study the dynamic additive hazard rate model, and investigate its aging properties for different aging classes. The closure of the model under some stochastic orders has also been investigated. Some examples are also given to illustrate different aging properties and stochastic comparisons of the model.

  15. Actuarial statistics with generalized linear mixed models

    NARCIS (Netherlands)

    Antonio, K.; Beirlant, J.

    2007-01-01

    Over the last decade the use of generalized linear models (GLMs) in actuarial statistics has received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh and Nelder [McCullagh, P., Nelder, J.A., 1989. Generalized linear models. In: Monographs on Statistics

  16. Testing the generalized partial credit model

    NARCIS (Netherlands)

    Glas, Cornelis A.W.

    1996-01-01

    The partial credit model (PCM) (G.N. Masters, 1982) can be viewed as a generalization of the Rasch model for dichotomous items to the case of polytomous items. In many cases, the PCM is too restrictive to fit the data. Several generalizations of the PCM have been proposed. In this paper, a

  17. Bayesian Subset Modeling for High-Dimensional Generalized Linear Models

    KAUST Repository

    Liang, Faming

    2013-06-01

    This article presents a new prior setting for high-dimensional generalized linear models, which leads to a Bayesian subset regression (BSR) with the maximum a posteriori model approximately equivalent to the minimum extended Bayesian information criterion model. The consistency of the resulting posterior is established under mild conditions. Further, a variable screening procedure is proposed based on the marginal inclusion probability, which shares the same properties of sure screening and consistency with the existing sure independence screening (SIS) and iterative sure independence screening (ISIS) procedures. However, since the proposed procedure makes use of joint information from all predictors, it generally outperforms SIS and ISIS in real applications. This article also makes extensive comparisons of BSR with the popular penalized likelihood methods, including Lasso, elastic net, SIS, and ISIS. The numerical results indicate that BSR can generally outperform the penalized likelihood methods. The models selected by BSR tend to be sparser and, more importantly, of higher prediction ability. In addition, the performance of the penalized likelihood methods tends to deteriorate as the number of predictors increases, while this is not significant for BSR. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  18. Micro Data and General Equilibrium Models

    DEFF Research Database (Denmark)

    Browning, Martin; Hansen, Lars Peter; Heckman, James J.

    1999-01-01

    Dynamic general equilibrium models are required to evaluate policies applied at the national level. To use these models to make quantitative forecasts requires knowledge of an extensive array of parameter values for the economy at large. This essay describes the parameters required for different...... economic models, assesses the discordance between the macromodels used in policy evaluation and the microeconomic models used to generate the empirical evidence. For concreteness, we focus on two general equilibrium models: the stochastic growth model extended to include some forms of heterogeneity...

  19. An Additive-Multiplicative Restricted Mean Residual Life Model

    DEFF Research Database (Denmark)

    Mansourvar, Zahra; Martinussen, Torben; Scheike, Thomas H.

    2016-01-01

    mean residual life model to study the association between the restricted mean residual life function and potential regression covariates in the presence of right censoring. This model extends the proportional mean residual life model using an additive model as its covariate dependent baseline....... For the suggested model, some covariate effects are allowed to be time-varying. To estimate the model parameters, martingale estimating equations are developed, and the large sample properties of the resulting estimators are established. In addition, to assess the adequacy of the model, we investigate a goodness...

  20. Generalized requirements and decompositions for the design of test parts for micro additive manufacturing research

    DEFF Research Database (Denmark)

    Thompson, Mary Kathryn; Clemmensen, Line Katrine Harder

    2015-01-01

    The design of experimental test parts to characterize micro additive manufacturing (AM) processes is challenging due to the influence of the manufacturing and metrology processes. This work builds on the lessons learned from a case study in the literature to derive generalized requirements and high...... level decompositions for the design of test parts and the design of experiments to characterize micro additive manufacturing processes. While the test parts and the experiments described are still work in progress, the generic requirements derived from them can serve as a starting point for the design...... of other micro additive manufacturing related studies and their decompositions can help structure future work....

  1. Zinc Addition Effects on General Corrosion of Austenitic Stainless Steels in PWR Primary Conditions

    International Nuclear Information System (INIS)

    Qiao Peipeng; Zhang Lefu; Liu Ruiqin; Jiang Suqing; Zhu Fawen

    2010-01-01

    Zinc addition effects on general corrosion of austenitic stainless steel 316 and 304 were investigated in simulated PWR primary coolant without zinc or with 50 ppb zinc addition at 315 degree C for 500 h. The results show that with the addition of zinc, the corrosion rate of austenitic stainless steel is effectively reduced, the surface oxide film is thinner, the morphology and chemical composition of surface oxide scales are evidently different from those without zinc. There are needle-like corrosion products on the surface of stainless steel 304. (authors)

  2. Process chain modeling and selection in an additive manufacturing context

    DEFF Research Database (Denmark)

    Thompson, Mary Kathryn; Stolfi, Alessandro; Mischkot, Michael

    2016-01-01

    This paper introduces a new two-dimensional approach to modeling manufacturing process chains. This approach is used to consider the role of additive manufacturing technologies in process chains for a part with micro scale features and no internal geometry. It is shown that additive manufacturing...... evolving fields like additive manufacturing....

  3. Additional Research Needs to Support the GENII Biosphere Models

    Energy Technology Data Exchange (ETDEWEB)

    Napier, Bruce A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Snyder, Sandra F. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Arimescu, Carmen [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2013-11-01

    In the course of evaluating the current parameter needs for the GENII Version 2 code (Snyder et al. 2013), areas of possible improvement for both the data and the underlying models have been identified. As the data review was implemented, PNNL staff identified areas where the models can be improved both to accommodate the locally significant pathways identified and also to incorporate newer models. The areas are general data needs for the existing models and improved formulations for the pathway models.

  4. A general consumer-resource population model

    Science.gov (United States)

    Lafferty, Kevin D.; DeLeo, Giulio; Briggs, Cheryl J.; Dobson, Andrew P.; Gross, Thilo; Kuris, Armand M.

    2015-01-01

    Food-web dynamics arise from predator-prey, parasite-host, and herbivore-plant interactions. Models for such interactions include up to three consumer activity states (questing, attacking, consuming) and up to four resource response states (susceptible, exposed, ingested, resistant). Articulating these states into a general model allows for dissecting, comparing, and deriving consumer-resource models. We specify this general model for 11 generic consumer strategies that group mathematically into predators, parasites, and micropredators and then derive conditions for consumer success, including a universal saturating functional response. We further show how to use this framework to create simple models with a common mathematical lineage and transparent assumptions. Underlying assumptions, missing elements, and composite parameters are revealed when classic consumer-resource models are derived from the general model.

  5. A Generalized Random Regret Minimization Model

    NARCIS (Netherlands)

    Chorus, C.G.

    2013-01-01

    This paper presents, discusses and tests a generalized Random Regret Minimization (G-RRM) model. The G-RRM model is created by replacing a fixed constant in the attribute-specific regret functions of the RRM model, by a regret-weight variable. Depending on the value of the regret-weights, the G-RRM

  6. EOP MIT General Circulation Model (MITgcm)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data contains a regional implementation of the Massachusetts Institute of Technology general circulation model (MITgcm) at a 1-km spatial resolution for the...

  7. Generalized Reduced Order Model Generation, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — M4 Engineering proposes to develop a generalized reduced order model generation method. This method will allow for creation of reduced order aeroservoelastic state...

  8. Foundations of linear and generalized linear models

    CERN Document Server

    Agresti, Alan

    2015-01-01

    A valuable overview of the most important ideas and results in statistical analysis Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linear statistical models. The book presents a broad, in-depth overview of the most commonly used statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical model building. The book begins by illustrating the fundamentals of linear models,

  9. On a Generalized Squared Gaussian Diffusion Model for Option Valuation

    Directory of Open Access Journals (Sweden)

    Edeki S.O.

    2017-01-01

    Full Text Available In financial mathematics, option pricing models are vital tools whose usefulness cannot be overemphasized. Modern approaches and modelling of financial derivatives are therefore required in option pricing and valuation settings. In this paper, we derive via the application of Ito lemma, a pricing model referred to as Generalized Squared Gaussian Diffusion Model (GSGDM for option pricing and valuation. Same approach can be considered via Stratonovich stochastic dynamics. We also show that the classical Black-Scholes, and the square root constant elasticity of variance models are special cases of the GSGDM. In addition, general solution of the GSGDM is obtained using modified variational iterative method (MVIM.

  10. Additive Manufacturing and Business Models: Current Knowledge and Missing Perspectives

    Directory of Open Access Journals (Sweden)

    Christina Öberg

    2018-06-01

    Full Text Available Additive manufacturing, that is 3D printing technology, may change the way companies operate their businesses. This article adopts a business model perspective to create an understanding of what we know about these changes. It summarizes current knowledge on additive manufacturing within management and business research, and it discusses future research directions in relation to business models for additive manufacturing. Using the scientific database Web of Science, 116 journal articles were identified. The literature review reveals that most research concerns manufacturing optimization. A more holistic view of the changes that additive manufacturing may bring about for firms is needed, as is more research on changed value propositions, and customer/sales-related issues. The article contributes to previous research by systematically summarizing additive manufacturing research in the business and management literature, and by highlighting areas for further investigation related to the business models of individual firms.

  11. Simple implementation of general dark energy models

    International Nuclear Information System (INIS)

    Bloomfield, Jolyon K.; Pearson, Jonathan A.

    2014-01-01

    We present a formalism for the numerical implementation of general theories of dark energy, combining the computational simplicity of the equation of state for perturbations approach with the generality of the effective field theory approach. An effective fluid description is employed, based on a general action describing single-scalar field models. The formalism is developed from first principles, and constructed keeping the goal of a simple implementation into CAMB in mind. Benefits of this approach include its straightforward implementation, the generality of the underlying theory, the fact that the evolved variables are physical quantities, and that model-independent phenomenological descriptions may be straightforwardly investigated. We hope this formulation will provide a powerful tool for the comparison of theoretical models of dark energy with observational data

  12. Generalization of the quark rearrangement model

    International Nuclear Information System (INIS)

    Fields, T.; Chen, C.K.

    1976-01-01

    An extension and generalization of the quark rearrangement model of baryon annihilation is described which can be applied to all annihilation reactions and which incorporates some of the features of the highly successful quark parton model. Some p anti-p interactions are discussed

  13. Geometrical efficiency in computerized tomography: generalized model

    International Nuclear Information System (INIS)

    Costa, P.R.; Robilotta, C.C.

    1992-01-01

    A simplified model for producing sensitivity and exposure profiles in computerized tomographic system was recently developed allowing the forecast of profiles behaviour in the rotation center of the system. The generalization of this model for some point of the image plane was described, and the geometrical efficiency could be evaluated. (C.G.C.)

  14. Comprehensive European dietary exposure model (CEDEM) for food additives.

    Science.gov (United States)

    Tennant, David R

    2016-05-01

    European methods for assessing dietary exposures to nutrients, additives and other substances in food are limited by the availability of detailed food consumption data for all member states. A proposed comprehensive European dietary exposure model (CEDEM) applies summary data published by the European Food Safety Authority (EFSA) in a deterministic model based on an algorithm from the EFSA intake method for food additives. The proposed approach can predict estimates of food additive exposure provided in previous EFSA scientific opinions that were based on the full European food consumption database.

  15. Additive Intensity Regression Models in Corporate Default Analysis

    DEFF Research Database (Denmark)

    Lando, David; Medhat, Mamdouh; Nielsen, Mads Stenbo

    2013-01-01

    We consider additive intensity (Aalen) models as an alternative to the multiplicative intensity (Cox) models for analyzing the default risk of a sample of rated, nonfinancial U.S. firms. The setting allows for estimating and testing the significance of time-varying effects. We use a variety of mo...

  16. Topics in the generalized vector dominance model

    International Nuclear Information System (INIS)

    Chavin, S.

    1976-01-01

    Two topics are covered in the generalized vector dominance model. In the first topic a model is constructed for dilepton production in hadron-hadron interactions based on the idea of generalized vector-dominance. It is argued that in the high mass region the generalized vector-dominance model and the Drell-Yan parton model are alternative descriptions of the same underlying physics. In the low mass regions the models differ; the vector-dominance approach predicts a greater production of dileptons. It is found that the high mass vector mesons which are the hallmark of the generalized vector-dominance model make little contribution to the large yield of leptons observed in the transverse-momentum range 1 less than p/sub perpendicular/ less than 6 GeV. The recently measured hadronic parameters lead one to believe that detailed fits to the data are possible under the model. The possibility was expected, and illustrated with a simple model the extreme sensitivity of the large-p/sub perpendicular/ lepton yield to the large-transverse-momentum tail of vector-meson production. The second topic is an attempt to explain the mysterious phenomenon of photon shadowing in nuclei utilizing the contribution of the longitudinally polarized photon. It is argued that if the scalar photon anti-shadows, it could compensate for the transverse photon, which is presumed to shadow. It is found in a very simple model that the scalar photon could indeed anti-shadow. The principal feature of the model is a cancellation of amplitudes. The scheme is consistent with scalar photon-nucleon data as well. The idea is tested with two simple GVDM models and finds that the anti-shadowing contribution of the scalar photon is not sufficient to compensate for the contribution of the transverse photon. It is found doubtful that the scalar photon makes a significant contribution to the total photon-nuclear cross section

  17. Generalized Born Models of Macromolecular Solvation Effects

    Science.gov (United States)

    Bashford, Donald; Case, David A.

    2000-10-01

    It would often be useful in computer simulations to use a simple description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation, and approximations to such models that avoid the need to solve the Poisson equation are attractive because of their computational efficiency. Here we give an overview of one such approximation, the generalized Born model, which is simple and fast enough to be used for molecular dynamics simulations of proteins and nucleic acids. We discuss its strengths and weaknesses, both for its fidelity to the underlying continuum model and for its ability to replace explicit consideration of solvent molecules in macromolecular simulations. We focus particularly on versions of the generalized Born model that have a pair-wise analytical form, and therefore fit most naturally into conventional molecular mechanics calculations.

  18. Generalized Reduced Order Modeling of Aeroservoelastic Systems

    Science.gov (United States)

    Gariffo, James Michael

    Transonic aeroelastic and aeroservoelastic (ASE) modeling presents a significant technical and computational challenge. Flow fields with a mixture of subsonic and supersonic flow, as well as moving shock waves, can only be captured through high-fidelity CFD analysis. With modern computing power, it is realtively straightforward to determine the flutter boundary for a single structural configuration at a single flight condition, but problems of larger scope remain quite costly. Some such problems include characterizing a vehicle's flutter boundary over its full flight envelope, optimizing its structural weight subject to aeroelastic constraints, and designing control laws for flutter suppression. For all of these applications, reduced-order models (ROMs) offer substantial computational savings. ROM techniques in general have existed for decades, and the methodology presented in this dissertation builds on successful previous techniques to create a powerful new scheme for modeling aeroelastic systems, and predicting and interpolating their transonic flutter boundaries. In this method, linear ASE state-space models are constructed from modal structural and actuator models coupled to state-space models of the linearized aerodynamic forces through feedback loops. Flutter predictions can be made from these models through simple eigenvalue analysis of their state-transition matrices for an appropriate set of dynamic pressures. Moreover, this analysis returns the frequency and damping trend of every aeroelastic branch. In contrast, determining the critical dynamic pressure by direct time-marching CFD requires a separate run for every dynamic pressure being analyzed simply to obtain the trend for the critical branch. The present ROM methodology also includes a new model interpolation technique that greatly enhances the benefits of these ROMs. This enables predictions of the dynamic behavior of the system for flight conditions where CFD analysis has not been explicitly

  19. Comparison of progressive addition lenses for general purpose and for computer vision: an office field study.

    Science.gov (United States)

    Jaschinski, Wolfgang; König, Mirjam; Mekontso, Tiofil M; Ohlendorf, Arne; Welscher, Monique

    2015-05-01

    Two types of progressive addition lenses (PALs) were compared in an office field study: 1. General purpose PALs with continuous clear vision between infinity and near reading distances and 2. Computer vision PALs with a wider zone of clear vision at the monitor and in near vision but no clear distance vision. Twenty-three presbyopic participants wore each type of lens for two weeks in a double-masked four-week quasi-experimental procedure that included an adaptation phase (Weeks 1 and 2) and a test phase (Weeks 3 and 4). Questionnaires on visual and musculoskeletal conditions as well as preferences regarding the type of lenses were administered. After eight more weeks of free use of the spectacles, the preferences were assessed again. The ergonomic conditions were analysed from photographs. Head inclination when looking at the monitor was significantly lower by 2.3 degrees with the computer vision PALs than with the general purpose PALs. Vision at the monitor was judged significantly better with computer PALs, while distance vision was judged better with general purpose PALs; however, the reported advantage of computer vision PALs differed in extent between participants. Accordingly, 61 per cent of the participants preferred the computer vision PALs, when asked without information about lens design. After full information about lens characteristics and additional eight weeks of free spectacle use, 44 per cent preferred the computer vision PALs. On average, computer vision PALs were rated significantly better with respect to vision at the monitor during the experimental part of the study. In the final forced-choice ratings, approximately half of the participants preferred either the computer vision PAL or the general purpose PAL. Individual factors seem to play a role in this preference and in the rated advantage of computer vision PALs. © 2015 The Authors. Clinical and Experimental Optometry © 2015 Optometry Australia.

  20. The General Analytic Solution of a Functional Equation of Addition Type

    OpenAIRE

    Braden, H. W.; Buchstaber, V. M.

    1995-01-01

    The general analytic solution to the functional equation $$ \\phi_1(x+y)= { { \\biggl|\\matrix{\\phi_2(x)&\\phi_2(y)\\cr\\phi_3(x)&\\phi_3(y)\\cr}\\biggr|} \\over { \\biggl|\\matrix{\\phi_4(x)&\\phi_4(y)\\cr\\phi_5(x)&\\phi_5(y)\\cr}\\biggr|} } $$ is characterised. Up to the action of the symmetry group, this is described in terms of Weierstrass elliptic functions. We illustrate our theory by applying it to the classical addition theorems of the Jacobi elliptic functions and the functional equations $$ \\phi_1(x+...

  1. Crash data modeling with a generalized estimator.

    Science.gov (United States)

    Ye, Zhirui; Xu, Yueru; Lord, Dominique

    2018-05-11

    The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study. This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Review of Shape Deviation Modeling for Additive Manufacturing

    OpenAIRE

    Zhu , Zuowei; Keimasi , Safa; ANWER , Nabil; Mathieu , Luc; Qiao , Lihong

    2016-01-01

    International audience; Additive Manufacturing (AM) is becoming a promising technology capable of building complex customized parts with internal geometries and graded material by stacking up thin individual layers. However, a comprehensive geometric model for Additive Manufacturing is not mature yet. Dimensional and form accuracy and surface finish are still a bottleneck for AM regarding quality control. In this paper, an up-to-date review is drawn on methods and approaches that have been de...

  3. Generalized formal model of Big Data

    OpenAIRE

    Shakhovska, N.; Veres, O.; Hirnyak, M.

    2016-01-01

    This article dwells on the basic characteristic features of the Big Data technologies. It is analyzed the existing definition of the “big data” term. The article proposes and describes the elements of the generalized formal model of big data. It is analyzed the peculiarities of the application of the proposed model components. It is described the fundamental differences between Big Data technology and business analytics. Big Data is supported by the distributed file system Google File System ...

  4. A new General Lorentz Transformation model

    International Nuclear Information System (INIS)

    Novakovic, Branko; Novakovic, Alen; Novakovic, Dario

    2000-01-01

    A new general structure of Lorentz Transformations, in the form of General Lorentz Transformation model (GLT-model), has been derived. This structure includes both Lorentz-Einstein and Galilean Transformations as its particular (special) realizations. Since the free parameters of GLT-model have been identified in a gravitational field, GLT-model can be employed both in Special and General Relativity. Consequently, the possibilities of an unification of Einstein's Special and General Theories of Relativity, as well as an unification of electromagnetic and gravitational fields are opened. If GLT-model is correct then there exist four new observation phenomena (a length and time neutrality, and a length dilation and a time contraction). Besides, the well-known phenomena (a length contraction, and a time dilation) are also the constituents of GLT-model. It means that there is a symmetry in GLT-model, where the center of this symmetry is represented by a length and a time neutrality. A time and a length neutrality in a gravitational field can be realized if the velocity of a moving system is equal to the free fall velocity. A time and a length neutrality include an observation of a particle mass neutrality. A special consideration has been devoted to a correlation between GLT-model and a limitation on particle velocities in order to investigate the possibility of a travel time reduction. It is found out that an observation of a particle speed faster then c=299 792 458 m/s, is possible in a gravitational field, if certain conditions are fulfilled

  5. Generalizations of the noisy-or model

    Czech Academy of Sciences Publication Activity Database

    Vomlel, Jiří

    2015-01-01

    Roč. 51, č. 3 (2015), s. 508-524 ISSN 0023-5954 R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : Bayesian networks * noisy-or model * classification * generalized linear models Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.628, year: 2015 http://library.utia.cas.cz/separaty/2015/MTR/vomlel-0447357.pdf

  6. Adaptive Inference on General Graphical Models

    OpenAIRE

    Acar, Umut A.; Ihler, Alexander T.; Mettu, Ramgopal; Sumer, Ozgur

    2012-01-01

    Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adaptive inference is to take advantage of what is preserved in the model and perform inference more rapidly than from scratch. In this paper, we describe techniques for adaptive inference on general graphs that support marginal computation and updates to the conditional ...

  7. Patient empowerment, an additional characteristic of the European definitions of general practice/family medicine.

    Science.gov (United States)

    Mola, Ernesto

    2013-06-01

    Growing evidence supports the inclusion of patient empowerment as a key ingredient of care for patients with chronic conditions. In recent years, several studies based on patient empowerment, have been carried out in different European countries in the context of general practice and primary care to improve management of chronic diseases. These studies have shown good results of the care model, increasing patient and health professionals' satisfaction, adherence to guidelines and to treatment, and improving clinical outcomes. In 2011, the Wonca European Council included as the twelfth characteristic of the European definitions of general practice/family medicine: 'promote patient empowerment'. The aim of this paper is to clarify the meaning of 'patient empowerment' and to explain why family medicine should be considered the most suitable setting to promote it. The inclusion of patient empowerment as one of the essential characteristics of general practice fills a conceptual gap and clearly suggests to the European health care systems a tested model to face chronic diseases: involving and empowering patients in managing their own conditions to improve health and well-being.

  8. The General Education Collaboration Model: A Model for Successful Mainstreaming.

    Science.gov (United States)

    Simpson, Richard L.; Myles, Brenda Smith

    1990-01-01

    The General Education Collaboration Model is designed to support general educators teaching mainstreamed disabled students, through collaboration with special educators. The model is based on flexible departmentalization, program ownership, identification and development of supportive attitudes, student assessment as a measure of program…

  9. General Equilibrium Models: Improving the Microeconomics Classroom

    Science.gov (United States)

    Nicholson, Walter; Westhoff, Frank

    2009-01-01

    General equilibrium models now play important roles in many fields of economics including tax policy, environmental regulation, international trade, and economic development. The intermediate microeconomics classroom has not kept pace with these trends, however. Microeconomics textbooks primarily focus on the insights that can be drawn from the…

  10. Covariate selection for the semiparametric additive risk model

    DEFF Research Database (Denmark)

    Martinussen, Torben; Scheike, Thomas

    2009-01-01

    This paper considers covariate selection for the additive hazards model. This model is particularly simple to study theoretically and its practical implementation has several major advantages to the similar methodology for the proportional hazards model. One complication compared...... and study their large sample properties for the situation where the number of covariates p is smaller than the number of observations. We also show that the adaptive Lasso has the oracle property. In many practical situations, it is more relevant to tackle the situation with large p compared with the number...... of observations. We do this by studying the properties of the so-called Dantzig selector in the setting of the additive risk model. Specifically, we establish a bound on how close the solution is to a true sparse signal in the case where the number of covariates is large. In a simulation study, we also compare...

  11. Electroacoustics modeling of piezoelectric welders for ultrasonic additive manufacturing processes

    Science.gov (United States)

    Hehr, Adam; Dapino, Marcelo J.

    2016-04-01

    Ultrasonic additive manufacturing (UAM) is a recent 3D metal printing technology which utilizes ultrasonic vibrations from high power piezoelectric transducers to additively weld similar and dissimilar metal foils. CNC machining is used intermittent of welding to create internal channels, embed temperature sensitive components, sensors, and materials, and for net shaping parts. Structural dynamics of the welder and work piece influence the performance of the welder and part quality. To understand the impact of structural dynamics on UAM, a linear time-invariant model is used to relate system shear force and electric current inputs to the system outputs of welder velocity and voltage. Frequency response measurements are combined with in-situ operating measurements of the welder to identify model parameters and to verify model assumptions. The proposed LTI model can enhance process consistency, performance, and guide the development of improved quality monitoring and control strategies.

  12. Projecting UK mortality using Bayesian generalised additive models

    OpenAIRE

    Hilton, Jason; Dodd, Erengul; Forster, Jonathan; Smith, Peter W.F.

    2018-01-01

    Forecasts of mortality provide vital information about future populations, with implications for pension and health-care policy as well as for decisions made by private companies about life insurance and annuity pricing. This paper presents a Bayesian approach to the forecasting of mortality that jointly estimates a Generalised Additive Model (GAM) for mortality for the majority of the age-range and a parametric model for older ages where the data are sparser. The GAM allows smooth components...

  13. The generalized spherical model of ferromagnetic films

    International Nuclear Information System (INIS)

    Costache, G.

    1977-12-01

    The D→ infinity of the D-vectorial model of a ferromagnetic film with free surfaces is exactly solved. The mathematical mechanism responsible for the onset of a phase transition in the system is a generalized sticking phenomenon. It is shown that the temperature at which the sticking appears, the transition temperature of the model is monotonously increasing with increasing the number of layers of the film, contrary to what happens in the spherical model with overall constraint. Certain correlation inequalities of Griffiths type are shown to hold. (author)

  14. Modeling uranium transport in acidic contaminated groundwater with base addition

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Fan [Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Luo, Wensui [ORNL; Parker, Jack C. [University of Tennessee, Knoxville (UTK); Brooks, Scott C [ORNL; Watson, David B [ORNL; Jardine, Philip [University of Tennessee, Knoxville (UTK); Gu, Baohua [ORNL

    2011-01-01

    This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO{sub 3}{sup -}, SO{sub 4}{sup 2-}, U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.

  15. Modeling uranium transport in acidic contaminated groundwater with base addition

    International Nuclear Information System (INIS)

    Zhang Fan; Luo Wensui; Parker, Jack C.; Brooks, Scott C.; Watson, David B.; Jardine, Philip M.; Gu Baohua

    2011-01-01

    This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO 3 - , SO 4 2- , U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.

  16. Modeling uranium transport in acidic contaminated groundwater with base addition

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Fan, E-mail: zhangfan@itpcas.ac.cn [Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, P.O. Box 2871, Beijing, 100085 (China); Luo Wensui [Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 (China); Parker, Jack C. [Institute for a Secure and Sustainable Environment, Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Brooks, Scott C.; Watson, David B. [Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Jardine, Philip M. [Biosystems Engineering and Soil Science Department, University of Tennessee, Knoxville, TN 37996 (United States); Gu Baohua [Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

    2011-06-15

    This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO{sub 3}{sup -}, SO{sub 4}{sup 2-}, U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.

  17. Generalised additive modelling approach to the fermentation process of glutamate.

    Science.gov (United States)

    Liu, Chun-Bo; Li, Yun; Pan, Feng; Shi, Zhong-Ping

    2011-03-01

    In this work, generalised additive models (GAMs) were used for the first time to model the fermentation of glutamate (Glu). It was found that three fermentation parameters fermentation time (T), dissolved oxygen (DO) and oxygen uptake rate (OUR) could capture 97% variance of the production of Glu during the fermentation process through a GAM model calibrated using online data from 15 fermentation experiments. This model was applied to investigate the individual and combined effects of T, DO and OUR on the production of Glu. The conditions to optimize the fermentation process were proposed based on the simulation study from this model. Results suggested that the production of Glu can reach a high level by controlling concentration levels of DO and OUR to the proposed optimization conditions during the fermentation process. The GAM approach therefore provides an alternative way to model and optimize the fermentation process of Glu. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

  18. Single-Index Additive Vector Autoregressive Time Series Models

    KAUST Repository

    LI, YEHUA; GENTON, MARC G.

    2009-01-01

    We study a new class of nonlinear autoregressive models for vector time series, where the current vector depends on single-indexes defined on the past lags and the effects of different lags have an additive form. A sufficient condition is provided

  19. Efficient estimation of an additive quantile regression model

    NARCIS (Netherlands)

    Cheng, Y.; de Gooijer, J.G.; Zerom, D.

    2009-01-01

    In this paper two kernel-based nonparametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a viable alternative to the method of De Gooijer and Zerom (2003). By

  20. Efficient estimation of an additive quantile regression model

    NARCIS (Netherlands)

    Cheng, Y.; de Gooijer, J.G.; Zerom, D.

    2010-01-01

    In this paper two kernel-based nonparametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a viable alternative to the method of De Gooijer and Zerom (2003). By

  1. Efficient estimation of an additive quantile regression model

    NARCIS (Netherlands)

    Cheng, Y.; de Gooijer, J.G.; Zerom, D.

    2011-01-01

    In this paper, two non-parametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a more viable alternative to existing kernel-based approaches. The second estimator

  2. Genomic Model with Correlation Between Additive and Dominance Effects.

    Science.gov (United States)

    Xiang, Tao; Christensen, Ole Fredslund; Vitezica, Zulma Gladis; Legarra, Andres

    2018-05-09

    Dominance genetic effects are rarely included in pedigree-based genetic evaluation. With the availability of single nucleotide polymorphism markers and the development of genomic evaluation, estimates of dominance genetic effects have become feasible using genomic best linear unbiased prediction (GBLUP). Usually, studies involving additive and dominance genetic effects ignore possible relationships between them. It has been often suggested that the magnitude of functional additive and dominance effects at the quantitative trait loci are related, but there is no existing GBLUP-like approach accounting for such correlation. Wellmann and Bennewitz showed two ways of considering directional relationships between additive and dominance effects, which they estimated in a Bayesian framework. However, these relationships cannot be fitted at the level of individuals instead of loci in a mixed model and are not compatible with standard animal or plant breeding software. This comes from a fundamental ambiguity in assigning the reference allele at a given locus. We show that, if there has been selection, assigning the most frequent as the reference allele orients the correlation between functional additive and dominance effects. As a consequence, the most frequent reference allele is expected to have a positive value. We also demonstrate that selection creates negative covariance between genotypic additive and dominance genetic values. For parameter estimation, it is possible to use a combined additive and dominance relationship matrix computed from marker genotypes, and to use standard restricted maximum likelihood (REML) algorithms based on an equivalent model. Through a simulation study, we show that such correlations can easily be estimated by mixed model software and accuracy of prediction for genetic values is slightly improved if such correlations are used in GBLUP. However, a model assuming uncorrelated effects and fitting orthogonal breeding values and dominant

  3. Modelling of additive manufacturing processes: a review and classification

    Science.gov (United States)

    Stavropoulos, Panagiotis; Foteinopoulos, Panagis

    2018-03-01

    Additive manufacturing (AM) is a very promising technology; however, there are a number of open issues related to the different AM processes. The literature on modelling the existing AM processes is reviewed and classified. A categorization of the different AM processes in process groups, according to the process mechanism, has been conducted and the most important issues are stated. Suggestions are made as to which approach is more appropriate according to the key performance indicator desired to be modelled and a discussion is included as to the way that future modelling work can better contribute to improving today's AM process understanding.

  4. A General Model for Estimating Macroevolutionary Landscapes.

    Science.gov (United States)

    Boucher, Florian C; Démery, Vincent; Conti, Elena; Harmon, Luke J; Uyeda, Josef

    2018-03-01

    The evolution of quantitative characters over long timescales is often studied using stochastic diffusion models. The current toolbox available to students of macroevolution is however limited to two main models: Brownian motion and the Ornstein-Uhlenbeck process, plus some of their extensions. Here, we present a very general model for inferring the dynamics of quantitative characters evolving under both random diffusion and deterministic forces of any possible shape and strength, which can accommodate interesting evolutionary scenarios like directional trends, disruptive selection, or macroevolutionary landscapes with multiple peaks. This model is based on a general partial differential equation widely used in statistical mechanics: the Fokker-Planck equation, also known in population genetics as the Kolmogorov forward equation. We thus call the model FPK, for Fokker-Planck-Kolmogorov. We first explain how this model can be used to describe macroevolutionary landscapes over which quantitative traits evolve and, more importantly, we detail how it can be fitted to empirical data. Using simulations, we show that the model has good behavior both in terms of discrimination from alternative models and in terms of parameter inference. We provide R code to fit the model to empirical data using either maximum-likelihood or Bayesian estimation, and illustrate the use of this code with two empirical examples of body mass evolution in mammals. FPK should greatly expand the set of macroevolutionary scenarios that can be studied since it opens the way to estimating macroevolutionary landscapes of any conceivable shape. [Adaptation; bounds; diffusion; FPK model; macroevolution; maximum-likelihood estimation; MCMC methods; phylogenetic comparative data; selection.].

  5. Stability of a Generalized Euler-Lagrange Type Additive Mapping and Homomorphisms in C∗-Algebras

    Directory of Open Access Journals (Sweden)

    Abbas Najati

    2009-01-01

    Full Text Available Let X,Y be Banach modules over a C∗-algebra and let r1,…,rn∈ℝ be given. We prove the generalized Hyers-Ulam stability of the following functional equation in Banach modules over a unital C∗-algebra: ∑j=1nf(−rjxj+∑1≤i≤n,i≠jrixi+2∑i=1nrif(xi=nf(∑i=1nrixi. We show that if ∑i=1nri≠0, ri,rj≠0 for some 1≤iadditive. As an application, we investigate homomorphisms in unital C∗-algebras.

  6. Deposition of additives onto surface of carbon materials by blending method--general conception

    International Nuclear Information System (INIS)

    Przepiorski, Jacek

    2005-01-01

    Carbon fibers loaded with potassium carbonate and with metallic copper were prepared by applying a blending method. Raw isotropic coal pitch was blended with KOH or CuBr 2 and obtained mixtures were subjected to spinning. In this way KOH and copper salt-blended fiber with uniform distribution of potassium and copper were spun. The raw fibers were exposed to stabilization with a mixture of CO 2 and air or air only through heating to 330 deg. C and next to treatment with carbon dioxide or hydrogen at higher temperatures. Electron probe micro-analysis (EPMA) analyses showed presence of potassium carbonate or metallic copper predominantly in peripheral regions of the obtained fibers. Basing on the mechanisms of potassium and copper diffusion over the carbon volume, generalized method for the deposition of additives onto surface of carbon materials is proposed

  7. Single-Index Additive Vector Autoregressive Time Series Models

    KAUST Repository

    LI, YEHUA

    2009-09-01

    We study a new class of nonlinear autoregressive models for vector time series, where the current vector depends on single-indexes defined on the past lags and the effects of different lags have an additive form. A sufficient condition is provided for stationarity of such models. We also study estimation of the proposed model using P-splines, hypothesis testing, asymptotics, selection of the order of the autoregression and of the smoothing parameters and nonlinear forecasting. We perform simulation experiments to evaluate our model in various settings. We illustrate our methodology on a climate data set and show that our model provides more accurate yearly forecasts of the El Niño phenomenon, the unusual warming of water in the Pacific Ocean. © 2009 Board of the Foundation of the Scandinavian Journal of Statistics.

  8. Generalized theory of resonance scattering (GTRS) using the translational addition theorem for spherical wave functions.

    Science.gov (United States)

    Mitri, Farid

    2014-11-01

    The generalized theory of resonance scattering (GTRS) by an elastic spherical target in acoustics is extended to describe the arbitrary scattering of a finite beam using the addition theorem for the spherical wave functions of the first kind under a translation of the coordinate origin. The advantage of the proposed method over the standard discrete spherical harmonics transform previously used in the GTRS formalism is the computation of the off-axial beam-shape coefficients (BSCs) stemming from a closed-form partial-wave series expansion representing the axial BSCs in spherical coordinates. With this general method, the arbitrary acoustical scattering can be evaluated for any particle shape and size, whether the particle is partially or completely illuminated by the incident beam. Numerical examples for the axial and off-axial resonance scattering from an elastic sphere placed arbitrarily in the field of a finite circular piston transducer with uniform vibration are provided. Moreover, the 3-D resonance directivity patterns illustrate the theory and reveal some properties of the scattering. Numerous applications involving the scattering phenomenon in imaging, particle manipulation, and the characterization of multiphase flows can benefit from the present analysis because all physically realizable beams radiate acoustical waves from finite transducers as opposed to waves of infinite extent.

  9. Validation of transport models using additive flux minimization technique

    Energy Technology Data Exchange (ETDEWEB)

    Pankin, A. Y.; Kruger, S. E. [Tech-X Corporation, 5621 Arapahoe Ave., Boulder, Colorado 80303 (United States); Groebner, R. J. [General Atomics, San Diego, California 92121 (United States); Hakim, A. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543-0451 (United States); Kritz, A. H.; Rafiq, T. [Department of Physics, Lehigh University, Bethlehem, Pennsylvania 18015 (United States)

    2013-10-15

    A new additive flux minimization technique is proposed for carrying out the verification and validation (V and V) of anomalous transport models. In this approach, the plasma profiles are computed in time dependent predictive simulations in which an additional effective diffusivity is varied. The goal is to obtain an optimal match between the computed and experimental profile. This new technique has several advantages over traditional V and V methods for transport models in tokamaks and takes advantage of uncertainty quantification methods developed by the applied math community. As a demonstration of its efficiency, the technique is applied to the hypothesis that the paleoclassical density transport dominates in the plasma edge region in DIII-D tokamak discharges. A simplified version of the paleoclassical model that utilizes the Spitzer resistivity for the parallel neoclassical resistivity and neglects the trapped particle effects is tested in this paper. It is shown that a contribution to density transport, in addition to the paleoclassical density transport, is needed in order to describe the experimental profiles. It is found that more additional diffusivity is needed at the top of the H-mode pedestal, and almost no additional diffusivity is needed at the pedestal bottom. The implementation of this V and V technique uses the FACETS::Core transport solver and the DAKOTA toolkit for design optimization and uncertainty quantification. The FACETS::Core solver is used for advancing the plasma density profiles. The DAKOTA toolkit is used for the optimization of plasma profiles and the computation of the additional diffusivity that is required for the predicted density profile to match the experimental profile.

  10. Validation of transport models using additive flux minimization technique

    International Nuclear Information System (INIS)

    Pankin, A. Y.; Kruger, S. E.; Groebner, R. J.; Hakim, A.; Kritz, A. H.; Rafiq, T.

    2013-01-01

    A new additive flux minimization technique is proposed for carrying out the verification and validation (V and V) of anomalous transport models. In this approach, the plasma profiles are computed in time dependent predictive simulations in which an additional effective diffusivity is varied. The goal is to obtain an optimal match between the computed and experimental profile. This new technique has several advantages over traditional V and V methods for transport models in tokamaks and takes advantage of uncertainty quantification methods developed by the applied math community. As a demonstration of its efficiency, the technique is applied to the hypothesis that the paleoclassical density transport dominates in the plasma edge region in DIII-D tokamak discharges. A simplified version of the paleoclassical model that utilizes the Spitzer resistivity for the parallel neoclassical resistivity and neglects the trapped particle effects is tested in this paper. It is shown that a contribution to density transport, in addition to the paleoclassical density transport, is needed in order to describe the experimental profiles. It is found that more additional diffusivity is needed at the top of the H-mode pedestal, and almost no additional diffusivity is needed at the pedestal bottom. The implementation of this V and V technique uses the FACETS::Core transport solver and the DAKOTA toolkit for design optimization and uncertainty quantification. The FACETS::Core solver is used for advancing the plasma density profiles. The DAKOTA toolkit is used for the optimization of plasma profiles and the computation of the additional diffusivity that is required for the predicted density profile to match the experimental profile

  11. General regression and representation model for classification.

    Directory of Open Access Journals (Sweden)

    Jianjun Qian

    Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.

  12. Higher dimensional generalizations of the SYK model

    Energy Technology Data Exchange (ETDEWEB)

    Berkooz, Micha [Department of Particle Physics and Astrophysics, Weizmann Institute of Science,Rehovot 7610001 (Israel); Narayan, Prithvi [International Centre for Theoretical Sciences, Hesaraghatta,Bengaluru North, 560 089 (India); Rozali, Moshe [Department of Physics and Astronomy, University of British Columbia,Vancouver, BC V6T 1Z1 (Canada); Simón, Joan [School of Mathematics and Maxwell Institute for Mathematical Sciences, University of Edinburgh,King’s Buildings, Edinburgh EH9 3FD (United Kingdom)

    2017-01-31

    We discuss a 1+1 dimensional generalization of the Sachdev-Ye-Kitaev model. The model contains N Majorana fermions at each lattice site with a nearest-neighbour hopping term. The SYK random interaction is restricted to low momentum fermions of definite chirality within each lattice site. This gives rise to an ordinary 1+1 field theory above some energy scale and a low energy SYK-like behavior. We exhibit a class of low-pass filters which give rise to a rich variety of hyperscaling behaviour in the IR. We also discuss another set of generalizations which describes probing an SYK system with an external fermion, together with the new scaling behavior they exhibit in the IR.

  13. Modeling the influence of limestone addition on cement hydration

    Directory of Open Access Journals (Sweden)

    Ashraf Ragab Mohamed

    2015-03-01

    Full Text Available This paper addresses the influence of using Portland limestone cement “PLC” on cement hydration by characterization of its microstructure development. The European Standard EN 197-1:2011 and Egyptian specification ESS 4756-1/2009 permit the cement to contain up to 20% ground limestone. The computational tools assist in better understanding the influence of limestone additions on cement hydration and microstructure development to facilitate the acceptance of these more economical and ecological materials. μic model has been developed to enable the modeling of microstructural evolution of cementitious materials. In this research μic model is used to simulate both the influence of limestone as fine filler, providing additional surfaces for the nucleation and growth of hydration products. Limestone powder also reacts relatively slow with hydrating cement to form monocarboaluminate (AFmc phase, similar to the mono-sulfoaluminate (AFm phase formed in ordinary Portland cement. The model results reveal that limestone cement has accelerated cement hydration rate, previous experimental results and computer model “cemhyd3d” are used to validate this model.

  14. A General Business Model for Marine Reserves

    Science.gov (United States)

    Sala, Enric; Costello, Christopher; Dougherty, Dawn; Heal, Geoffrey; Kelleher, Kieran; Murray, Jason H.; Rosenberg, Andrew A.; Sumaila, Rashid

    2013-01-01

    Marine reserves are an effective tool for protecting biodiversity locally, with potential economic benefits including enhancement of local fisheries, increased tourism, and maintenance of ecosystem services. However, fishing communities often fear short-term income losses associated with closures, and thus may oppose marine reserves. Here we review empirical data and develop bioeconomic models to show that the value of marine reserves (enhanced adjacent fishing + tourism) may often exceed the pre-reserve value, and that economic benefits can offset the costs in as little as five years. These results suggest the need for a new business model for creating and managing reserves, which could pay for themselves and turn a profit for stakeholder groups. Our model could be expanded to include ecosystem services and other benefits, and it provides a general framework to estimate costs and benefits of reserves and to develop such business models. PMID:23573192

  15. A proposed general model of information behaviour.

    Directory of Open Access Journals (Sweden)

    2003-01-01

    Full Text Available Presents a critical description of Wilson's (1996 global model of information behaviour and proposes major modification on the basis of research into information behaviour of managers, conducted in Poland. The theoretical analysis and research results suggest that Wilson's model has certain imperfections, both in its conceptual content, and in graphical presentation. The model, for example, cannot be used to describe managers' information behaviour, since managers basically are not the end users of external from organization or computerized information services, and they acquire information mainly through various intermediaries. Therefore, the model cannot be considered as a general model, applicable to every category of information users. The proposed new model encompasses the main concepts of Wilson's model, such as: person-in-context, three categories of intervening variables (individual, social and environmental, activating mechanisms, cyclic character of information behaviours, and the adoption of a multidisciplinary approach to explain them. However, the new model introduces several changes. They include: 1. identification of 'context' with the intervening variables; 2. immersion of the chain of information behaviour in the 'context', to indicate that the context variables influence behaviour at all stages of the process (identification of needs, looking for information, processing and using it; 3. stress is put on the fact that the activating mechanisms also can occur at all stages of the information acquisition process; 4. introduction of two basic strategies of looking for information: personally and/or using various intermediaries.

  16. A general diagnostic model applied to language testing data.

    Science.gov (United States)

    von Davier, Matthias

    2008-11-01

    Probabilistic models with one or more latent variables are designed to report on a corresponding number of skills or cognitive attributes. Multidimensional skill profiles offer additional information beyond what a single test score can provide, if the reported skills can be identified and distinguished reliably. Many recent approaches to skill profile models are limited to dichotomous data and have made use of computationally intensive estimation methods such as Markov chain Monte Carlo, since standard maximum likelihood (ML) estimation techniques were deemed infeasible. This paper presents a general diagnostic model (GDM) that can be estimated with standard ML techniques and applies to polytomous response variables as well as to skills with two or more proficiency levels. The paper uses one member of a larger class of diagnostic models, a compensatory diagnostic model for dichotomous and partial credit data. Many well-known models, such as univariate and multivariate versions of the Rasch model and the two-parameter logistic item response theory model, the generalized partial credit model, as well as a variety of skill profile models, are special cases of this GDM. In addition to an introduction to this model, the paper presents a parameter recovery study using simulated data and an application to real data from the field test for TOEFL Internet-based testing.

  17. The additive hazards model with high-dimensional regressors

    DEFF Research Database (Denmark)

    Martinussen, Torben; Scheike, Thomas

    2009-01-01

    This paper considers estimation and prediction in the Aalen additive hazards model in the case where the covariate vector is high-dimensional such as gene expression measurements. Some form of dimension reduction of the covariate space is needed to obtain useful statistical analyses. We study...... model. A standard PLS algorithm can also be constructed, but it turns out that the resulting predictor can only be related to the original covariates via time-dependent coefficients. The methods are applied to a breast cancer data set with gene expression recordings and to the well known primary biliary...

  18. Genomic breeding value estimation using nonparametric additive regression models

    Directory of Open Access Journals (Sweden)

    Solberg Trygve

    2009-01-01

    Full Text Available Abstract Genomic selection refers to the use of genomewide dense markers for breeding value estimation and subsequently for selection. The main challenge of genomic breeding value estimation is the estimation of many effects from a limited number of observations. Bayesian methods have been proposed to successfully cope with these challenges. As an alternative class of models, non- and semiparametric models were recently introduced. The present study investigated the ability of nonparametric additive regression models to predict genomic breeding values. The genotypes were modelled for each marker or pair of flanking markers (i.e. the predictors separately. The nonparametric functions for the predictors were estimated simultaneously using additive model theory, applying a binomial kernel. The optimal degree of smoothing was determined by bootstrapping. A mutation-drift-balance simulation was carried out. The breeding values of the last generation (genotyped was predicted using data from the next last generation (genotyped and phenotyped. The results show moderate to high accuracies of the predicted breeding values. A determination of predictor specific degree of smoothing increased the accuracy.

  19. Modeling process-structure-property relationships for additive manufacturing

    Science.gov (United States)

    Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Yu, Cheng; Liu, Zeliang; Lian, Yanping; Wolff, Sarah; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

    2018-02-01

    This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the processstructure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a highefficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.

  20. Additive manufacturing for consumer-centric business models

    DEFF Research Database (Denmark)

    Bogers, Marcel; Hadar, Ronen; Bilberg, Arne

    2016-01-01

    Digital fabrication—including additive manufacturing (AM), rapid prototyping and 3D printing—has the potential to revolutionize the way in which products are produced and delivered to the customer. Therefore, it challenges companies to reinvent their business model—describing the logic of creating...... and capturing value. In this paper, we explore the implications that AM technologies have for manufacturing systems in the new business models that they enable. In particular, we consider how a consumer goods manufacturer can organize the operations of a more open business model when moving from a manufacturer......-centric to a consumer-centric value logic. A major shift includes a move from centralized to decentralized supply chains, where consumer goods manufacturers can implement a “hybrid” approach with a focus on localization and accessibility or develop a fully personalized model where the consumer effectively takes over...

  1. Addition and multiplication of beta-expansions in generalized Tribonacci base

    Directory of Open Access Journals (Sweden)

    Petr Ambrož

    2007-05-01

    Full Text Available We study properties of β-numeration systems, where β > 1 is the real root of the polynomial x 3  - mx 2  - x - 1, m ∈ ℕ, m ≥ 1. We consider arithmetic operations on the set of β-integers, i.e., on the set of numbers whose greedy expansion in base β has no fractional part. We show that the number of fractional digits arising under addition of β-integers is at most 5 for m ≥ 3 and 6 for m = 2, whereas under multiplication it is at most 6 for all m ≥ 2. We thus generalize the results known for Tribonacci numeration system, i.e., for m = 1. We summarize the combinatorial properties of infinite words naturally defined by β-integers. We point out the differences between the structure of β-integers in cases m = 1 and m ≥ 2.

  2. Generalized model of the microwave auditory effect

    International Nuclear Information System (INIS)

    Yitzhak, N M; Ruppin, R; Hareuveny, R

    2009-01-01

    A generalized theoretical model for evaluating the amplitudes of the sound waves generated in a spherical head model, which is irradiated by microwave pulses, is developed. The thermoelastic equation of motion is solved for a spherically symmetric heating pattern of arbitrary form. For previously treated heating patterns that are peaked at the sphere centre, the results reduce to those presented before. The generalized model is applied to the case in which the microwave absorption is concentrated near the sphere surface. It is found that, for equal average specific absorption rates, the sound intensity generated by a surface localized heating pattern is comparable to that generated by a heating pattern that is peaked at the centre. The dependence of the induced sound pressure on the shape of the microwave pulse is explored. Another theoretical extension, to the case of repeated pulses, is developed and applied to the interpretation of existing experimental data on the dependence of the human hearing effect threshold on the pulse repetition frequency.

  3. Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

    Science.gov (United States)

    Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar

    2015-01-01

    The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition

  4. Modelling debris flows down general channels

    Directory of Open Access Journals (Sweden)

    S. P. Pudasaini

    2005-01-01

    Full Text Available This paper is an extension of the single-phase cohesionless dry granular avalanche model over curved and twisted channels proposed by Pudasaini and Hutter (2003. It is a generalisation of the Savage and Hutter (1989, 1991 equations based on simple channel topography to a two-phase fluid-solid mixture of debris material. Important terms emerging from the correct treatment of the kinematic and dynamic boundary condition, and the variable basal topography are systematically taken into account. For vanishing fluid contribution and torsion-free channel topography our new model equations exactly degenerate to the previous Savage-Hutter model equations while such a degeneration was not possible by the Iverson and Denlinger (2001 model, which, in fact, also aimed to extend the Savage and Hutter model. The model equations of this paper have been rigorously derived; they include the effects of the curvature and torsion of the topography, generally for arbitrarily curved and twisted channels of variable channel width. The equations are put into a standard conservative form of partial differential equations. From these one can easily infer the importance and influence of the pore-fluid-pressure distribution in debris flow dynamics. The solid-phase is modelled by applying a Coulomb dry friction law whereas the fluid phase is assumed to be an incompressible Newtonian fluid. Input parameters of the equations are the internal and bed friction angles of the solid particles, the viscosity and volume fraction of the fluid, the total mixture density and the pore pressure distribution of the fluid at the bed. Given the bed topography and initial geometry and the initial velocity profile of the debris mixture, the model equations are able to describe the dynamics of the depth profile and bed parallel depth-averaged velocity distribution from the initial position to the final deposit. A shock capturing, total variation diminishing numerical scheme is implemented to

  5. Process Modeling and Validation for Metal Big Area Additive Manufacturing

    Energy Technology Data Exchange (ETDEWEB)

    Simunovic, Srdjan [ORNL; Nycz, Andrzej [ORNL; Noakes, Mark W. [ORNL; Chin, Charlie [Dassault Systemes; Oancea, Victor [Dassault Systemes

    2017-05-01

    Metal Big Area Additive Manufacturing (mBAAM) is a new additive manufacturing (AM) technology based on the metal arc welding. A continuously fed metal wire is melted by an electric arc that forms between the wire and the substrate, and deposited in the form of a bead of molten metal along the predetermined path. Objects are manufactured one layer at a time starting from the base plate. The final properties of the manufactured object are dependent on its geometry and the metal deposition path, in addition to depending on the basic welding process parameters. Computational modeling can be used to accelerate the development of the mBAAM technology as well as a design and optimization tool for the actual manufacturing process. We have developed a finite element method simulation framework for mBAAM using the new features of software ABAQUS. The computational simulation of material deposition with heat transfer is performed first, followed by the structural analysis based on the temperature history for predicting the final deformation and stress state. In this formulation, we assume that two physics phenomena are coupled in only one direction, i.e. the temperatures are driving the deformation and internal stresses, but their feedback on the temperatures is negligible. The experiment instrumentation (measurement types, sensor types, sensor locations, sensor placements, measurement intervals) and the measurements are presented. The temperatures and distortions from the simulations show good correlation with experimental measurements. Ongoing modeling work is also briefly discussed.

  6. A generalized model for compact stars

    Energy Technology Data Exchange (ETDEWEB)

    Aziz, Abdul [Bodai High School (H.S.), Department of Physics, Kolkata, West Bengal (India); Ray, Saibal [Government College of Engineering and Ceramic Technology, Department of Physics, Kolkata, West Bengal (India); Rahaman, Farook [Jadavpur University, Department of Mathematics, Kolkata, West Bengal (India)

    2016-05-15

    By virtue of the maximum entropy principle, we get an Euler-Lagrange equation which is a highly nonlinear differential equation containing the mass function and its derivatives. Solving the equation by a homotopy perturbation method we derive a generalized expression for the mass which is a polynomial function of the radial distance. Using the mass function we find a partially stable configuration and its characteristics. We show that different physical features of the known compact stars, viz. Her X-1, RX J 1856-37, SAX J (SS1), SAX J (SS2), and PSR J 1614-2230, can be explained by the present model. (orig.)

  7. Testing Parametric versus Semiparametric Modelling in Generalized Linear Models

    NARCIS (Netherlands)

    Härdle, W.K.; Mammen, E.; Müller, M.D.

    1996-01-01

    We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known function, b is an unknown parameter vector, and m is an unknown function.The paper introduces a test statistic which allows to decide between a parametric and a semiparametric model: (i) m is linear, i.e.

  8. A Model Fit Statistic for Generalized Partial Credit Model

    Science.gov (United States)

    Liang, Tie; Wells, Craig S.

    2009-01-01

    Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…

  9. The Generalized Quantum Episodic Memory Model.

    Science.gov (United States)

    Trueblood, Jennifer S; Hemmer, Pernille

    2017-11-01

    Recent evidence suggests that experienced events are often mapped to too many episodic states, including those that are logically or experimentally incompatible with one another. For example, episodic over-distribution patterns show that the probability of accepting an item under different mutually exclusive conditions violates the disjunction rule. A related example, called subadditivity, occurs when the probability of accepting an item under mutually exclusive and exhaustive instruction conditions sums to a number >1. Both the over-distribution effect and subadditivity have been widely observed in item and source-memory paradigms. These phenomena are difficult to explain using standard memory frameworks, such as signal-detection theory. A dual-trace model called the over-distribution (OD) model (Brainerd & Reyna, 2008) can explain the episodic over-distribution effect, but not subadditivity. Our goal is to develop a model that can explain both effects. In this paper, we propose the Generalized Quantum Episodic Memory (GQEM) model, which extends the Quantum Episodic Memory (QEM) model developed by Brainerd, Wang, and Reyna (2013). We test GQEM by comparing it to the OD model using data from a novel item-memory experiment and a previously published source-memory experiment (Kellen, Singmann, & Klauer, 2014) examining the over-distribution effect. Using the best-fit parameters from the over-distribution experiments, we conclude by showing that the GQEM model can also account for subadditivity. Overall these results add to a growing body of evidence suggesting that quantum probability theory is a valuable tool in modeling recognition memory. Copyright © 2016 Cognitive Science Society, Inc.

  10. The epistemological status of general circulation models

    Science.gov (United States)

    Loehle, Craig

    2018-03-01

    Forecasts of both likely anthropogenic effects on climate and consequent effects on nature and society are based on large, complex software tools called general circulation models (GCMs). Forecasts generated by GCMs have been used extensively in policy decisions related to climate change. However, the relation between underlying physical theories and results produced by GCMs is unclear. In the case of GCMs, many discretizations and approximations are made, and simulating Earth system processes is far from simple and currently leads to some results with unknown energy balance implications. Statistical testing of GCM forecasts for degree of agreement with data would facilitate assessment of fitness for use. If model results need to be put on an anomaly basis due to model bias, then both visual and quantitative measures of model fit depend strongly on the reference period used for normalization, making testing problematic. Epistemology is here applied to problems of statistical inference during testing, the relationship between the underlying physics and the models, the epistemic meaning of ensemble statistics, problems of spatial and temporal scale, the existence or not of an unforced null for climate fluctuations, the meaning of existing uncertainty estimates, and other issues. Rigorous reasoning entails carefully quantifying levels of uncertainty.

  11. Modeling a Change in Flowrate through Detention or Additional Pavement on the Receiving Stream : Final Report

    Science.gov (United States)

    2017-11-01

    The addition or removal of flow from a stream affects the water surface downstream and possibly upstream. The extent of such effects is generally determined by modeling the receiving stream. Guidance that concisely describes how far up/downstream a h...

  12. Generalized Penner models and multicritical behavior

    International Nuclear Information System (INIS)

    Tan, C.

    1992-01-01

    In this paper, we are interested in the critical behavior of generalized Penner models at t∼-1+μ/N where the topological expansion for the free energy develops logarithmic singularities: Γ∼-(χ 0 μ 2 lnμ+χ 1 lnμ+...). We demonstrate that these criticalities can best be characterized by the fact that the large-N generating function becomes meromorphic with a single pole term of unit residue, F(z)→1/(z-a), where a is the location of the ''sink.'' For a one-band eigenvalue distribution, we identify multicritical potentials; we find that none of these can be associated with the c=1 string compactified at an integral multiple of the self-dual radius. We also give an exact solution to the Gaussian Penner model and explicitly demonstrate that, at criticality, this solution does not correspond to a c=1 string compactified at twice the self-dual radius

  13. Aspects of general linear modelling of migration.

    Science.gov (United States)

    Congdon, P

    1992-01-01

    "This paper investigates the application of general linear modelling principles to analysing migration flows between areas. Particular attention is paid to specifying the form of the regression and error components, and the nature of departures from Poisson randomness. Extensions to take account of spatial and temporal correlation are discussed as well as constrained estimation. The issue of specification bears on the testing of migration theories, and assessing the role migration plays in job and housing markets: the direction and significance of the effects of economic variates on migration depends on the specification of the statistical model. The application is in the context of migration in London and South East England in the 1970s and 1980s." excerpt

  14. On the Use of Generalized Volume Scattering Models for the Improvement of General Polarimetric Model-Based Decomposition

    Directory of Open Access Journals (Sweden)

    Qinghua Xie

    2017-01-01

    Full Text Available Recently, a general polarimetric model-based decomposition framework was proposed by Chen et al., which addresses several well-known limitations in previous decomposition methods and implements a simultaneous full-parameter inversion by using complete polarimetric information. However, it only employs four typical models to characterize the volume scattering component, which limits the parameter inversion performance. To overcome this issue, this paper presents two general polarimetric model-based decomposition methods by incorporating the generalized volume scattering model (GVSM or simplified adaptive volume scattering model, (SAVSM proposed by Antropov et al. and Huang et al., respectively, into the general decomposition framework proposed by Chen et al. By doing so, the final volume coherency matrix structure is selected from a wide range of volume scattering models within a continuous interval according to the data itself without adding unknowns. Moreover, the new approaches rely on one nonlinear optimization stage instead of four as in the previous method proposed by Chen et al. In addition, the parameter inversion procedure adopts the modified algorithm proposed by Xie et al. which leads to higher accuracy and more physically reliable output parameters. A number of Monte Carlo simulations of polarimetric synthetic aperture radar (PolSAR data are carried out and show that the proposed method with GVSM yields an overall improvement in the final accuracy of estimated parameters and outperforms both the version using SAVSM and the original approach. In addition, C-band Radarsat-2 and L-band AIRSAR fully polarimetric images over the San Francisco region are also used for testing purposes. A detailed comparison and analysis of decomposition results over different land-cover types are conducted. According to this study, the use of general decomposition models leads to a more accurate quantitative retrieval of target parameters. However, there

  15. Addition Table of Colours: Additive and Subtractive Mixtures Described Using a Single Reasoning Model

    Science.gov (United States)

    Mota, A. R.; Lopes dos Santos, J. M. B.

    2014-01-01

    Students' misconceptions concerning colour phenomena and the apparent complexity of the underlying concepts--due to the different domains of knowledge involved--make its teaching very difficult. We have developed and tested a teaching device, the addition table of colours (ATC), that encompasses additive and subtractive mixtures in a single…

  16. Kinetics approach to modeling of polymer additive degradation in lubricants

    Institute of Scientific and Technical Information of China (English)

    llyaI.KUDISH; RubenG.AIRAPETYAN; Michael; J.; COVITCH

    2001-01-01

    A kinetics problem for a degrading polymer additive dissolved in a base stock is studied.The polymer degradation may be caused by the combination of such lubricant flow parameters aspressure, elongational strain rate, and temperature as well as lubricant viscosity and the polymercharacteristics (dissociation energy, bead radius, bond length, etc.). A fundamental approach tothe problem of modeling mechanically induced polymer degradation is proposed. The polymerdegradation is modeled on the basis of a kinetic equation for the density of the statistical distribu-tion of polymer molecules as a function of their molecular weight. The integrodifferential kineticequation for polymer degradation is solved numerically. The effects of pressure, elongational strainrate, temperature, and lubricant viscosity on the process of lubricant degradation are considered.The increase of pressure promotes fast degradation while the increase of temperature delaysdegradation. A comparison of a numerically calculated molecular weight distribution with an ex-perimental one obtained in bench tests showed that they are in excellent agreement with eachother.

  17. Generalized Linear Models in Vehicle Insurance

    Directory of Open Access Journals (Sweden)

    Silvie Kafková

    2014-01-01

    Full Text Available Actuaries in insurance companies try to find the best model for an estimation of insurance premium. It depends on many risk factors, e.g. the car characteristics and the profile of the driver. In this paper, an analysis of the portfolio of vehicle insurance data using a generalized linear model (GLM is performed. The main advantage of the approach presented in this article is that the GLMs are not limited by inflexible preconditions. Our aim is to predict the relation of annual claim frequency on given risk factors. Based on a large real-world sample of data from 57 410 vehicles, the present study proposed a classification analysis approach that addresses the selection of predictor variables. The models with different predictor variables are compared by analysis of deviance and Akaike information criterion (AIC. Based on this comparison, the model for the best estimate of annual claim frequency is chosen. All statistical calculations are computed in R environment, which contains stats package with the function for the estimation of parameters of GLM and the function for analysis of deviation.

  18. Nuclear inertia for fission in a generalized cranking model

    International Nuclear Information System (INIS)

    Kunz, J.; Nix, J.R.

    1984-01-01

    A time dependent formalism which is appropriate for β vibrations and fission is developed for a generalized cranking model. The formalism leads to additional terms in the density matrix which affect the nuclear inertia. The case of a harmonic oscillator potential is used to demonstrate the contribution of the pairing gap term on the β vibrational inertia for Pu 240. The inertia remains finite and close to the limiting irrotational value

  19. WATEQ3 geochemical model: thermodynamic data for several additional solids

    International Nuclear Information System (INIS)

    Krupka, K.M.; Jenne, E.A.

    1982-09-01

    Geochemical models such as WATEQ3 can be used to model the concentrations of water-soluble pollutants that may result from the disposal of nuclear waste and retorted oil shale. However, for a model to competently deal with these water-soluble pollutants, an adequate thermodynamic data base must be provided that includes elements identified as important in modeling these pollutants. To this end, several minerals and related solid phases were identified that were absent from the thermodynamic data base of WATEQ3. In this study, the thermodynamic data for the identified solids were compiled and selected from several published tabulations of thermodynamic data. For these solids, an accepted Gibbs free energy of formation, ΔG 0 /sub f,298/, was selected for each solid phase based on the recentness of the tabulated data and on considerations of internal consistency with respect to both the published tabulations and the existing data in WATEQ3. For those solids not included in these published tabulations, Gibbs free energies of formation were calculated from published solubility data (e.g., lepidocrocite), or were estimated (e.g., nontronite) using a free-energy summation method described by Mattigod and Sposito (1978). The accepted or estimated free energies were then combined with internally consistent, ancillary thermodynamic data to calculate equilibrium constants for the hydrolysis reactions of these minerals and related solid phases. Including these values in the WATEQ3 data base increased the competency of this geochemical model in applications associated with the disposal of nuclear waste and retorted oil shale. Additional minerals and related solid phases that need to be added to the solubility submodel will be identified as modeling applications continue in these two programs

  20. A general phenomenological model for work function

    Science.gov (United States)

    Brodie, I.; Chou, S. H.; Yuan, H.

    2014-07-01

    A general phenomenological model is presented for obtaining the zero Kelvin work function of any crystal facet of metals and semiconductors, both clean and covered with a monolayer of electropositive atoms. It utilizes the known physical structure of the crystal and the Fermi energy of the two-dimensional electron gas assumed to form on the surface. A key parameter is the number of electrons donated to the surface electron gas per surface lattice site or adsorbed atom, which is taken to be an integer. Initially this is found by trial and later justified by examining the state of the valence electrons of the relevant atoms. In the case of adsorbed monolayers of electropositive atoms a satisfactory justification could not always be found, particularly for cesium, but a trial value always predicted work functions close to the experimental values. The model can also predict the variation of work function with temperature for clean crystal facets. The model is applied to various crystal faces of tungsten, aluminium, silver, and select metal oxides, and most demonstrate good fits compared to available experimental values.

  1. Structured Additive Regression Models: An R Interface to BayesX

    Directory of Open Access Journals (Sweden)

    Nikolaus Umlauf

    2015-02-01

    Full Text Available Structured additive regression (STAR models provide a flexible framework for model- ing possible nonlinear effects of covariates: They contain the well established frameworks of generalized linear models and generalized additive models as special cases but also allow a wider class of effects, e.g., for geographical or spatio-temporal data, allowing for specification of complex and realistic models. BayesX is standalone software package providing software for fitting general class of STAR models. Based on a comprehensive open-source regression toolbox written in C++, BayesX uses Bayesian inference for estimating STAR models based on Markov chain Monte Carlo simulation techniques, a mixed model representation of STAR models, or stepwise regression techniques combining penalized least squares estimation with model selection. BayesX not only covers models for responses from univariate exponential families, but also models from less-standard regression situations such as models for multi-categorical responses with either ordered or unordered categories, continuous time survival data, or continuous time multi-state models. This paper presents a new fully interactive R interface to BayesX: the R package R2BayesX. With the new package, STAR models can be conveniently specified using Rs formula language (with some extended terms, fitted using the BayesX binary, represented in R with objects of suitable classes, and finally printed/summarized/plotted. This makes BayesX much more accessible to users familiar with R and adds extensive graphics capabilities for visualizing fitted STAR models. Furthermore, R2BayesX complements the already impressive capabilities for semiparametric regression in R by a comprehensive toolbox comprising in particular more complex response types and alternative inferential procedures such as simulation-based Bayesian inference.

  2. Geo-additive modelling of malaria in Burundi

    Directory of Open Access Journals (Sweden)

    Gebhardt Albrecht

    2011-08-01

    Full Text Available Abstract Background Malaria is a major public health issue in Burundi in terms of both morbidity and mortality, with around 2.5 million clinical cases and more than 15,000 deaths each year. It is still the single main cause of mortality in pregnant women and children below five years of age. Because of the severe health and economic burden of malaria, there is still a growing need for methods that will help to understand the influencing factors. Several studies/researches have been done on the subject yielding different results as which factors are most responsible for the increase in malaria transmission. This paper considers the modelling of the dependence of malaria cases on spatial determinants and climatic covariates including rainfall, temperature and humidity in Burundi. Methods The analysis carried out in this work exploits real monthly data collected in the area of Burundi over 12 years (1996-2007. Semi-parametric regression models are used. The spatial analysis is based on a geo-additive model using provinces as the geographic units of study. The spatial effect is split into structured (correlated and unstructured (uncorrelated components. Inference is fully Bayesian and uses Markov chain Monte Carlo techniques. The effects of the continuous covariates are modelled by cubic p-splines with 20 equidistant knots and second order random walk penalty. For the spatially correlated effect, Markov random field prior is chosen. The spatially uncorrelated effects are assumed to be i.i.d. Gaussian. The effects of climatic covariates and the effects of other spatial determinants are estimated simultaneously in a unified regression framework. Results The results obtained from the proposed model suggest that although malaria incidence in a given month is strongly positively associated with the minimum temperature of the previous months, regional patterns of malaria that are related to factors other than climatic variables have been identified

  3. Symplectic models for general insertion devices

    International Nuclear Information System (INIS)

    Wu, Y.; Forest, E.; Robin, D. S.; Nishimura, H.; Wolski, A.; Litvinenko, V. N.

    2001-01-01

    A variety of insertion devices (IDs), wigglers and undulators, linearly or elliptically polarized,are widely used as high brightness radiation sources at the modern light source rings. Long and high-field wigglers have also been proposed as the main source of radiation damping at next generation damping rings. As a result, it becomes increasingly important to understand the impact of IDs on the charged particle dynamics in the storage ring. In this paper, we report our recent development of a general explicit symplectic model for IDs with the paraxial ray approximation. High-order explicit symplectic integrators are developed to study real-world insertion devices with a number of wiggler harmonics and arbitrary polarizations

  4. A generalized model for coincidence counting

    International Nuclear Information System (INIS)

    Lu, Ming-Shih; Teichmann, T.

    1992-01-01

    The aim of this paper is to provide a description of the multiplicative processes associated with coincidence counting techniques, for example in the NDA of plutonium bearing materials. The model elucidates both the physical processes and the underlying mathematical formalism in a relatively simple but comprehensive way. In particular, it includes the effect of absorption by impurities or poisons, as well as that of neutron leakage on a parallel basis to the treatment of induced fission itself. The work thus parallels and generalizes the methods of Boehnel of Hage and Cifarelli, and more recently of Yanjushkin. This paper introduces the concept of a dual probability generating function to account for both the basic physical multiplication phenomena, as well as the detection phenomena. The underlying approach extends the idea of a simple probability generating function, due to De Moivre. The basic mathematical background may be found, for example, in Feller 1966

  5. Teaching general problem-solving skills is not a substitute for, or a viable addition to, teaching mathematics

    NARCIS (Netherlands)

    Sweller, John; Clark, Richard; Kirschner, Paul A.

    2010-01-01

    Sweller, J., Clark, R., & Kirschner, P. A. (2010). Teaching general problem-solving skills is not a substitute for, or a viable addition to, teaching mathematics. Notices of the American Mathematical Society, 57, 1303-1304.

  6. [Critical of the additive model of the randomized controlled trial].

    Science.gov (United States)

    Boussageon, Rémy; Gueyffier, François; Bejan-Angoulvant, Theodora; Felden-Dominiak, Géraldine

    2008-01-01

    Randomized, double-blind, placebo-controlled clinical trials are currently the best way to demonstrate the clinical effectiveness of drugs. Its methodology relies on the method of difference (John Stuart Mill), through which the observed difference between two groups (drug vs placebo) can be attributed to the pharmacological effect of the drug being tested. However, this additive model can be questioned in the event of statistical interactions between the pharmacological and the placebo effects. Evidence in different domains has shown that the placebo effect can influence the effect of the active principle. This article evaluates the methodological, clinical and epistemological consequences of this phenomenon. Topics treated include extrapolating results, accounting for heterogeneous results, demonstrating the existence of several factors in the placebo effect, the necessity to take these factors into account for given symptoms or pathologies, as well as the problem of the "specific" effect.

  7. Generalized transport model for phase transition with memory

    International Nuclear Information System (INIS)

    Chen, Chi; Ciucci, Francesco

    2013-01-01

    A general model for phenomenological transport in phase transition is derived, which extends Jäckle and Frisch model of phase transition with memory and the Cahn–Hilliard model. In addition to including interfacial energy to account for the presence of interfaces, we introduce viscosity and relaxation contributions, which result from incorporating memory effect into the driving potential. Our simulation results show that even without interfacial energy term, the viscous term can lead to transient diffuse interfaces. From the phase transition induced hysteresis, we discover different energy dissipation mechanism for the interfacial energy and the viscosity effect. In addition, by combining viscosity and interfacial energy, we find that if the former dominates, then the concentration difference across the phase boundary is reduced; conversely, if the interfacial energy is greater then this difference is enlarged.

  8. Dynamical reduction models with general gaussian noises

    International Nuclear Information System (INIS)

    Bassi, Angelo; Ghirardi, GianCarlo

    2002-02-01

    We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the statevector, white noise stochastic processes with non white ones. We prove that such a modification can be consistently performed without altering the most interesting features of the previous models. One of the reasons to discuss this matter derives from the desire of being allowed to deal with physical stochastic fields, such as the gravitational one, which cannot give rise to white noises. From our point of view the most relevant motivation for the approach we propose here derives from the fact that in relativistic models the occurrence of white noises is the main responsible for the appearance of untractable divergences. Therefore, one can hope that resorting to non white noises one can overcome such a difficulty. We investigate stochastic equations with non white noises, we discuss their reduction properties and their physical implications. Our analysis has a precise interest not only for the above mentioned subject but also for the general study of dissipative systems and decoherence. (author)

  9. Dynamical reduction models with general Gaussian noises

    International Nuclear Information System (INIS)

    Bassi, Angelo; Ghirardi, GianCarlo

    2002-01-01

    We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the state vector, white-noise stochastic processes with nonwhite ones. We prove that such a modification can be consistently performed without altering the most interesting features of the previous models. One of the reasons to discuss this matter derives from the desire of being allowed to deal with physical stochastic fields, such as the gravitational one, which cannot give rise to white noises. From our point of view, the most relevant motivation for the approach we propose here derives from the fact that in relativistic models intractable divergences appear as a consequence of the white nature of the noises. Therefore, one can hope that resorting to nonwhite noises, one can overcome such a difficulty. We investigate stochastic equations with nonwhite noises, we discuss their reduction properties and their physical implications. Our analysis has a precise interest not only for the above-mentioned subject but also for the general study of dissipative systems and decoherence

  10. MODEL OF BRAZILIAN URBANIZATION: GENERAL NOTES

    Directory of Open Access Journals (Sweden)

    Leandro da Silva Guimarães

    2016-07-01

    Full Text Available The full text format seeks to analyze the social inequality in Brazil through the spatial process of that inequality in this sense it analyzes, scratching the edges of what is known of the Brazilian urbanization model and how this same model produced gentrification cities and exclusive. So search the text discuss the country’s urban exclusion through consolidation of what is conventionally called peripheral areas, or more generally, of peripheries. The text on screen is the result of research carried out at the Federal Fluminense University in Masters level. In this study, we tried to understand the genesis of an urban housing development located in São Gonçalo, Rio de Janeiro called Jardim Catarina. Understand what the problem space partner who originated it. In this sense, his analysis becomes consubstantial to understand the social and spatial inequalities in Brazil, as well as the role of the state as planning manager socio-spatial planning and principal agent in the solution of such problems. It is expected that with the realization of a study of greater amounts, from which this article is just a micro work can contribute subsidies that contribute to the arrangement and crystallization of public policies that give account of social inequalities and serve to leverage a country more fair and equitable cities.

  11. Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

    Directory of Open Access Journals (Sweden)

    Juliana Petrini

    2012-12-01

    Full Text Available The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567, yearling weight (n=58,124, and scrotal circumference (n=20,371 of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.

  12. Evaluating the double Poisson generalized linear model.

    Science.gov (United States)

    Zou, Yaotian; Geedipally, Srinivas Reddy; Lord, Dominique

    2013-10-01

    The objectives of this study are to: (1) examine the applicability of the double Poisson (DP) generalized linear model (GLM) for analyzing motor vehicle crash data characterized by over- and under-dispersion and (2) compare the performance of the DP GLM with the Conway-Maxwell-Poisson (COM-Poisson) GLM in terms of goodness-of-fit and theoretical soundness. The DP distribution has seldom been investigated and applied since its first introduction two decades ago. The hurdle for applying the DP is related to its normalizing constant (or multiplicative constant) which is not available in closed form. This study proposed a new method to approximate the normalizing constant of the DP with high accuracy and reliability. The DP GLM and COM-Poisson GLM were developed using two observed over-dispersed datasets and one observed under-dispersed dataset. The modeling results indicate that the DP GLM with its normalizing constant approximated by the new method can handle crash data characterized by over- and under-dispersion. Its performance is comparable to the COM-Poisson GLM in terms of goodness-of-fit (GOF), although COM-Poisson GLM provides a slightly better fit. For the over-dispersed data, the DP GLM performs similar to the NB GLM. Considering the fact that the DP GLM can be easily estimated with inexpensive computation and that it is simpler to interpret coefficients, it offers a flexible and efficient alternative for researchers to model count data. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. A Note on the Identifiability of Generalized Linear Mixed Models

    DEFF Research Database (Denmark)

    Labouriau, Rodrigo

    2014-01-01

    I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable. The proof is based on the assumptions of generalized linear mixed models on the first and second order moments and some general mild regularity...... conditions, and, therefore, is extensible to quasi-likelihood based generalized linear models. In particular, binomial and Poisson mixed models with dispersion parameter are identifiable when equipped with the standard parametrization...

  14. Versatility of cooperative transcriptional activation: a thermodynamical modeling analysis for greater-than-additive and less-than-additive effects.

    Directory of Open Access Journals (Sweden)

    Till D Frank

    Full Text Available We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive

  15. 76 FR 59247 - Environmental Impact Considerations, Food Additives, and Generally Recognized As Safe Substances...

    Science.gov (United States)

    2011-09-26

    ... agent in the manufacture of silica.'' PART 178--INDIRECT FOOD ADDITIVES: ADJUVANTS, PRODUCTION AIDS, AND... pale orange or pinkish white powder. * * * * * * * * 0 21. Section 184.1845 is amended by revising the...

  16. Constraints on Generality (COG): A Proposed Addition to All Empirical Papers.

    Science.gov (United States)

    Simons, Daniel J; Shoda, Yuichi; Lindsay, D Stephen

    2017-11-01

    Psychological scientists draw inferences about populations based on samples-of people, situations, and stimuli-from those populations. Yet, few papers identify their target populations, and even fewer justify how or why the tested samples are representative of broader populations. A cumulative science depends on accurately characterizing the generality of findings, but current publishing standards do not require authors to constrain their inferences, leaving readers to assume the broadest possible generalizations. We propose that the discussion section of all primary research articles specify Constraints on Generality (i.e., a "COG" statement) that identify and justify target populations for the reported findings. Explicitly defining the target populations will help other researchers to sample from the same populations when conducting a direct replication, and it could encourage follow-up studies that test the boundary conditions of the original finding. Universal adoption of COG statements would change publishing incentives to favor a more cumulative science.

  17. Modeling of Cementitious Representative Volume Element with Additives

    Science.gov (United States)

    Shahzamanian, M. M.; Basirun, W. J.

    CEMHYD3D has been employed to simulate the representative volume element (RVE) of cementitious systems (Type I cement) containing fly ash (Class F) through a voxel-based finite element analysis (FEA) approach. Three-dimensional microstructures composed of voxels are generated for a heterogeneous cementitious material consisting of various constituent phases. The primary focus is to simulate a cementitious RVE containing fly ash and to present the homogenized macromechanical properties obtained from its analysis. Simple kinematic uniform boundary conditions as well as periodic boundary conditions were imposed on the RVE to obtain the principal and shear moduli. Our current work considers the effect of fly ash percentage on the elastic properties based on the mass and volume replacements. RVEs with lengths of 50, 100 and 200μm at different degrees of hydration are generated, and the elastic properties are modeled and simulated. In general, the elastic properties of a cementitious RVE with fly ash replacement for cement based on mass and volume differ from each other. Moreover, the finite element (FE) mesh density effect is studied. Results indicate that mechanical properties decrease with increasing mesh density.

  18. 42 CFR 412.87 - Additional payment for new medical services and technologies: General provisions.

    Science.gov (United States)

    2010-10-01

    ... payment for new medical services and technologies: General provisions. (a) Basis. Sections 412.87 and 412... establish a mechanism to recognize the costs of new medical services and technologies under the hospital... that are new medical services and technologies, if the following conditions are met: (1) A new medical...

  19. Cosmological models in the generalized Einstein action

    International Nuclear Information System (INIS)

    Arbab, A.I.

    2007-12-01

    We have studied the evolution of the Universe in the generalized Einstein action of the form R + β R 2 , where R is the scalar curvature and β = const. We have found exact cosmological solutions that predict the present cosmic acceleration. These models predict an inflationary de-Sitter era occurring in the early Universe. The cosmological constant (Λ) is found to decay with the Hubble constant (H) as, Λ ∝ H 4 . In this scenario the cosmological constant varies quadratically with the energy density (ρ), i.e., Λ ∝ ρ 2 . Such a variation is found to describe a two-component cosmic fluid in the Universe. One of the components accelerated the Universe in the early era, and the other in the present era. The scale factor of the Universe varies as a ∼ t n = 1/2 in the radiation era. The cosmological constant vanishes when n = 4/3 and n =1/2. We have found that the inclusion of the term R 2 mimics a cosmic matter that could substitute the ordinary matter. (author)

  20. A generalized model for homogenized reflectors

    International Nuclear Information System (INIS)

    Pogosbekyan, Leonid; Kim, Yeong Il; Kim, Young Jin; Joo, Hyung Kook

    1996-01-01

    A new concept of equivalent homogenization is proposed. The concept employs new set of homogenized parameters: homogenized cross sections (XS) and interface matrix (IM), which relates partial currents at the cell interfaces. The idea of interface matrix generalizes the idea of discontinuity factors (DFs), proposed and developed by K. Koebke and K. Smith. The method of K. Smith can be simulated within framework of new method, while the new method approximates hetero-geneous cell better in case of the steep flux gradients at the cell interfaces. The attractive shapes of new concept are:improved accuracy, simplicity of incorporation in the existing codes, equal numerical expenses in comparison to the K. Smith's approach. The new concept is useful for: (a) explicit reflector/baffle simulation; (b)control blades simulation; (c) mixed UO 2 /MOX core simulation. The offered model has been incorporated in the finite difference code and in the nodal code PANBOX. The numerical results show good accuracy of core calculations and insensitivity of homogenized parameters with respect to in-core conditions

  1. Dynamic generalized linear models for monitoring endemic diseases

    DEFF Research Database (Denmark)

    Lopes Antunes, Ana Carolina; Jensen, Dan; Hisham Beshara Halasa, Tariq

    2016-01-01

    The objective was to use a Dynamic Generalized Linear Model (DGLM) based on abinomial distribution with a linear trend, for monitoring the PRRS (Porcine Reproductive and Respiratory Syndrome sero-prevalence in Danish swine herds. The DGLM was described and its performance for monitoring control...... and eradication programmes based on changes in PRRS sero-prevalence was explored. Results showed a declining trend in PRRS sero-prevalence between 2007 and 2014 suggesting that Danish herds are slowly eradicating PRRS. The simulation study demonstrated the flexibility of DGLMs in adapting to changes intrends...... in sero-prevalence. Based on this, it was possible to detect variations in the growth model component. This study is a proof-of-concept, demonstrating the use of DGLMs for monitoring endemic diseases. In addition, the principles stated might be useful in general research on monitoring and surveillance...

  2. Climatology of the HOPE-G global ocean general circulation model - Sea ice general circulation model

    Energy Technology Data Exchange (ETDEWEB)

    Legutke, S. [Deutsches Klimarechenzentrum (DKRZ), Hamburg (Germany); Maier-Reimer, E. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany)

    1999-12-01

    The HOPE-G global ocean general circulation model (OGCM) climatology, obtained in a long-term forced integration is described. HOPE-G is a primitive-equation z-level ocean model which contains a dynamic-thermodynamic sea-ice model. It is formulated on a 2.8 grid with increased resolution in low latitudes in order to better resolve equatorial dynamics. The vertical resolution is 20 layers. The purpose of the integration was both to investigate the models ability to reproduce the observed general circulation of the world ocean and to obtain an initial state for coupled atmosphere - ocean - sea-ice climate simulations. The model was driven with daily mean data of a 15-year integration of the atmosphere general circulation model ECHAM4, the atmospheric component in later coupled runs. Thereby, a maximum of the flux variability that is expected to appear in coupled simulations is included already in the ocean spin-up experiment described here. The model was run for more than 2000 years until a quasi-steady state was achieved. It reproduces the major current systems and the main features of the so-called conveyor belt circulation. The observed distribution of water masses is reproduced reasonably well, although with a saline bias in the intermediate water masses and a warm bias in the deep and bottom water of the Atlantic and Indian Oceans. The model underestimates the meridional transport of heat in the Atlantic Ocean. The simulated heat transport in the other basins, though, is in good agreement with observations. (orig.)

  3. Remarks on the additional symmetries and W-constraints in the generalized KdV hierarchy

    International Nuclear Information System (INIS)

    Panda, S.; Roy, S.

    1992-07-01

    Additional symmetries of the p-reduced KP hierarchy are generated by the Lax operator L and another operator M, satisfying res(M n L m+n/p ) = 0 for 1 ≤n≤p - 1 and m ≥ -1 with the condition that γL/γt kp = 0,k = 1,2,.... We show explicitly that the generators of these additional symmetries satisfy a closed and consistent W-algebra only when we impose the extra condition that γM/γt tk = 0. (author). 32 refs

  4. Application of Improved Radiation Modeling to General Circulation Models

    Energy Technology Data Exchange (ETDEWEB)

    Michael J Iacono

    2011-04-07

    This research has accomplished its primary objectives of developing accurate and efficient radiation codes, validating them with measurements and higher resolution models, and providing these advancements to the global modeling community to enhance the treatment of cloud and radiative processes in weather and climate prediction models. A critical component of this research has been the development of the longwave and shortwave broadband radiative transfer code for general circulation model (GCM) applications, RRTMG, which is based on the single-column reference code, RRTM, also developed at AER. RRTMG is a rigorously tested radiation model that retains a considerable level of accuracy relative to higher resolution models and measurements despite the performance enhancements that have made it possible to apply this radiation code successfully to global dynamical models. This model includes the radiative effects of all significant atmospheric gases, and it treats the absorption and scattering from liquid and ice clouds and aerosols. RRTMG also includes a statistical technique for representing small-scale cloud variability, such as cloud fraction and the vertical overlap of clouds, which has been shown to improve cloud radiative forcing in global models. This development approach has provided a direct link from observations to the enhanced radiative transfer provided by RRTMG for application to GCMs. Recent comparison of existing climate model radiation codes with high resolution models has documented the improved radiative forcing capability provided by RRTMG, especially at the surface, relative to other GCM radiation models. Due to its high accuracy, its connection to observations, and its computational efficiency, RRTMG has been implemented operationally in many national and international dynamical models to provide validated radiative transfer for improving weather forecasts and enhancing the prediction of global climate change.

  5. Thurstonian models for sensory discrimination tests as generalized linear models

    DEFF Research Database (Denmark)

    Brockhoff, Per B.; Christensen, Rune Haubo Bojesen

    2010-01-01

    as a so-called generalized linear model. The underlying sensory difference 6 becomes directly a parameter of the statistical model and the estimate d' and it's standard error becomes the "usual" output of the statistical analysis. The d' for the monadic A-NOT A method is shown to appear as a standard......Sensory discrimination tests such as the triangle, duo-trio, 2-AFC and 3-AFC tests produce binary data and the Thurstonian decision rule links the underlying sensory difference 6 to the observed number of correct responses. In this paper it is shown how each of these four situations can be viewed...

  6. Between and beyond additivity and non-additivity : the statistical modelling of genotype by environment interaction in plant breeding

    OpenAIRE

    Eeuwijk, van, F.A.

    1996-01-01

    In plant breeding it is a common observation to see genotypes react differently to environmental changes. This phenomenon is called genotype by environment interaction. Many statistical approaches for analysing genotype by environment interaction rely heavily on the analysis of variance model. Genotype by environment interaction is then taken to be equivalent to non-additivity. This thesis criticizes the analysis of variance approach. Modelling genotype by environment interaction by non-addit...

  7. Multivariate statistical modelling based on generalized linear models

    CERN Document Server

    Fahrmeir, Ludwig

    1994-01-01

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

  8. A generalized multivariate regression model for modelling ocean wave heights

    Science.gov (United States)

    Wang, X. L.; Feng, Y.; Swail, V. R.

    2012-04-01

    In this study, a generalized multivariate linear regression model is developed to represent the relationship between 6-hourly ocean significant wave heights (Hs) and the corresponding 6-hourly mean sea level pressure (MSLP) fields. The model is calibrated using the ERA-Interim reanalysis of Hs and MSLP fields for 1981-2000, and is validated using the ERA-Interim reanalysis for 2001-2010 and ERA40 reanalysis of Hs and MSLP for 1958-2001. The performance of the fitted model is evaluated in terms of Pierce skill score, frequency bias index, and correlation skill score. Being not normally distributed, wave heights are subjected to a data adaptive Box-Cox transformation before being used in the model fitting. Also, since 6-hourly data are being modelled, lag-1 autocorrelation must be and is accounted for. The models with and without Box-Cox transformation, and with and without accounting for autocorrelation, are inter-compared in terms of their prediction skills. The fitted MSLP-Hs relationship is then used to reconstruct historical wave height climate from the 6-hourly MSLP fields taken from the Twentieth Century Reanalysis (20CR, Compo et al. 2011), and to project possible future wave height climates using CMIP5 model simulations of MSLP fields. The reconstructed and projected wave heights, both seasonal means and maxima, are subject to a trend analysis that allows for non-linear (polynomial) trends.

  9. The ECHAM3 atmospheric general circulation model

    International Nuclear Information System (INIS)

    1993-09-01

    The ECHAM model has been developed from the ECMWF model (cycle 31, November 1988). It contains several changes, mostly in the parameterization, in order to adjust the model for climate simulations. The technical details of the ECHAM operational model are described. (orig./KW)

  10. The Michigan Titan Thermospheric General Circulation Model (TTGCM)

    Science.gov (United States)

    Bell, J. M.; Bougher, S. W.; de Lahaye, V.; Waite, J. H.

    2005-12-01

    The Cassini flybys of Titan since late October, 2004 have provided data critical to better understanding its chemical and thermal structures. With this in mind, a 3-D TGCM of Titan's atmosphere from 600km to the exobase (~1450km) has been developed. This paper presents the first results from the partially operational code. Currently, the TTGCM includes static background chemistry (Lebonnois et al 2001, Vervack et al 2004) coupled with thermal conduction routines. The thermosphere remains dominated by solar EUV forcing and HCN rotational cooling, which is calculated by a full line-by-line radiative transfer routine along the lines of Yelle (1991) and Mueller-Wodarg (2000, 2002). In addition, an approximate treatment of magnetospheric heating is explored. This paper illustrates the model's capabilities as well as some initial results from the Titan Thermospheric General Circulation model that will be compared with both the Cassini INMS data and the model of Mueller-Wodarg (2000,2002).

  11. Three General Theoretical Models in Sociology: An Articulated ?(Disunity?

    Directory of Open Access Journals (Sweden)

    Thaís García-Pereiro

    2015-01-01

    Full Text Available After merely a brief, comparative reconstruction of the three most general theoretical models underlying contemporary Sociology (atomic, systemic, and fluid it becomes necessary to review the question about the unity or plurality of Sociology, which is the main objective of this paper. To do so, the basic terms of the question are firstly updated by following the hegemonic trends in current studies of science. Secondly the convergences and divergences among the three models discussed are shown. Following some additional discussion, the conclusion is reached that contemporary Sociology is not unitary, and need not be so. It is plural, but its plurality is limited and articulated by those very models. It may therefore be portrayed as integrated and commensurable, to the extent that a partial and unstable (disunity may be said to exist in Sociology, which is not too far off from what happens in the natural sciences.

  12. INFORMATION MODEL OF A GENERAL PRACTITIONER

    Directory of Open Access Journals (Sweden)

    S. M. Zlepko

    2016-06-01

    Full Text Available In the paper the authors developed information model family doctor shows its innovation and functionality. The proposed model meets the requirements of the current job description and criteria World Organization of Family Doctors.

  13. Generalization of Random Intercept Multilevel Models

    Directory of Open Access Journals (Sweden)

    Rehan Ahmad Khan

    2013-10-01

    Full Text Available The concept of random intercept models in a multilevel model developed by Goldstein (1986 has been extended for k-levels. The random variation in intercepts at individual level is marginally split into components by incorporating higher levels of hierarchy in the single level model. So, one can control the random variation in intercepts by incorporating the higher levels in the model.

  14. generalized constitutive model for stabilized quick clay

    African Journals Online (AJOL)

    QUICK CLAY. PANCRAS MUGISHAGWE BUJULU AND GUSTAV GRIMSTAD. ABSTRACT. An experimentally-based two yield surface constitutive model for cemented quick clay has been ... Clay Model, the Koiter Rule and two Mapping Rules. .... models, where a mobilization formulation is used, this is independent of q.

  15. Reshocks, rarefactions, and the generalized Layzer model for hydrodynamic instabilities

    International Nuclear Information System (INIS)

    Mikaelian, K.O.

    2008-01-01

    We report numerical simulations and analytic modeling of shock tube experiments on Rayleigh-Taylor and Richtmyer-Meshkov instabilities. We examine single interfaces of the type A/B where the incident shock is initiated in A and the transmitted shock proceeds into B. Examples are He/air and air/He. In addition, we study finite-thickness or double-interface A/B/A configurations like air/SF 6 /air gas-curtain experiments. We first consider conventional shock tubes that have a 'fixed' boundary: A solid endwall which reflects the transmitted shock and reshocks the interface(s). Then we focus on new experiments with a 'free' boundary--a membrane disrupted mechanically or by the transmitted shock, sending back a rarefaction towards the interface(s). Complex acceleration histories are achieved, relevant for Inertial Confinement Fusion implosions. We compare our simulation results with a generalized Layzer model for two fluids with time-dependent densities, and derive a new freeze-out condition whereby accelerating and compressive forces cancel each other out. Except for the recently reported failures of the Layzer model, the generalized Layzer model and hydrocode simulations for reshocks and rarefactions agree well with each other, and remain to be verified experimentally

  16. Reshocks, rarefactions, and the generalized Layzer model for hydrodynamic instabilities

    Energy Technology Data Exchange (ETDEWEB)

    Mikaelian, K O

    2008-06-10

    We report numerical simulations and analytic modeling of shock tube experiments on Rayleigh-Taylor and Richtmyer-Meshkov instabilities. We examine single interfaces of the type A/B where the incident shock is initiated in A and the transmitted shock proceeds into B. Examples are He/air and air/He. In addition, we study finite-thickness or double-interface A/B/A configurations like air/SF{sub 6}/air gas-curtain experiments. We first consider conventional shock tubes that have a 'fixed' boundary: A solid endwall which reflects the transmitted shock and reshocks the interface(s). Then we focus on new experiments with a 'free' boundary--a membrane disrupted mechanically or by the transmitted shock, sending back a rarefaction towards the interface(s). Complex acceleration histories are achieved, relevant for Inertial Confinement Fusion implosions. We compare our simulation results with a generalized Layzer model for two fluids with time-dependent densities, and derive a new freeze-out condition whereby accelerating and compressive forces cancel each other out. Except for the recently reported failures of the Layzer model, the generalized Layzer model and hydrocode simulations for reshocks and rarefactions agree well with each other, and remain to be verified experimentally.

  17. A Generalized Deduction of the Ideal-Solution Model

    Science.gov (United States)

    Leo, Teresa J.; Perez-del-Notario, Pedro; Raso, Miguel A.

    2006-01-01

    A new general procedure for deriving the Gibbs energy of mixing is developed through general thermodynamic considerations, and the ideal-solution model is obtained as a special particular case of the general one. The deduction of the Gibbs energy of mixing for the ideal-solution model is a rational one and viewed suitable for advanced students who…

  18. Stratospheric General Circulation with Chemistry Model (SGCCM)

    Science.gov (United States)

    Rood, Richard B.; Douglass, Anne R.; Geller, Marvin A.; Kaye, Jack A.; Nielsen, J. Eric; Rosenfield, Joan E.; Stolarski, Richard S.

    1990-01-01

    In the past two years constituent transport and chemistry experiments have been performed using both simple single constituent models and more complex reservoir species models. Winds for these experiments have been taken from the data assimilation effort, Stratospheric Data Analysis System (STRATAN).

  19. Development of a generalized integral jet model

    DEFF Research Database (Denmark)

    Duijm, Nijs Jan; Kessler, A.; Markert, Frank

    2017-01-01

    Integral type models to describe stationary plumes and jets in cross-flows (wind) have been developed since about 1970. These models are widely used for risk analysis, to describe the consequences of many different scenarios. Alternatively, CFD codes are being applied, but computational requireme......Integral type models to describe stationary plumes and jets in cross-flows (wind) have been developed since about 1970. These models are widely used for risk analysis, to describe the consequences of many different scenarios. Alternatively, CFD codes are being applied, but computational...... requirements still limit the number of scenarios that can be dealt with using CFD only. The integral models, however, are not suited to handle transient releases, such as releases from pressurized equipment, where the initially high release rate decreases rapidly with time. Further, on gas ignition, a second...... model is needed to describe the rapid combustion of the flammable part of the plume (flash fire) and a third model has to be applied for the remaining jet fire. The objective of this paper is to describe the first steps of the development of an integral-type model describing the transient development...

  20. Generalized coupling in the Kuramoto model

    DEFF Research Database (Denmark)

    Filatrella, G.; Pedersen, Niels Falsig; Wiesenfeld, K.

    2007-01-01

    We propose a modification of the Kuramoto model to account for the effective change in the coupling constant among the oscillators, as suggested by some experiments on Josephson junction, laser arrays, and mechanical systems, where the active elements are turned on one by one. The resulting model...... with the behavior of Josephson junctions coupled via a cavity....

  1. Smooth generalized linear models for aggregated data

    OpenAIRE

    Ayma Anza, Diego Armando

    2016-01-01

    Mención Internacional en el título de doctor Aggregated data commonly appear in areas such as epidemiology, demography, and public health. Generally, the aggregation process is done to protect the privacy of patients, to facilitate compact presentation, or to make it comparable with other coarser datasets. However, this process may hinder the visualization of the underlying distribution that follows the data. Also, it prohibits the direct analysis of relationships between ag...

  2. Primary circuit iodine model addition to IMPAIR-3

    Energy Technology Data Exchange (ETDEWEB)

    Osetek, D J; Louie, D L.Y. [Los Alamos Technical Associates, Inc., Albuquerque, NM (United States); Guntay, S; Cripps, R [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

    1996-12-01

    As part of a continuing effort to provide the U.S. Department of Energy (DOE) Advanced Reactor Severe Accident Program (ARSAP) with complete iodine analysis capability, a task was undertaken to expand the modeling of IMPAIR-3, an iodine chemistry code. The expanded code will enable the DOE to include detailed iodine behavior in the assessment of severe accident source terms used in the licensing of U.S. Advanced Light Water Reactors (ALWRs). IMPAIR-3 was developed at the Paul Scherrer Institute (PSI), Switzerland, and has been used by ARSAP for the past two years to analyze containment iodine chemistry for ALWR source term analyses. IMPAIR-3 is primarily a containment code but the iodine chemistry inside the primary circuit (the Reactor Coolant System or RCS) may influence the iodine species released into the the containment; therefore, a RCS iodine chemistry model must be implemented in IMPAIR-3 to ensure thorough source term analysis. The ARSAP source term team and the PSI IMPAIR-3 developers are working together to accomplish this task. This cooperation is divided into two phases. Phase I, taking place in 1996, involves developing a stand-alone RCS iodine chemistry program called IMPRCS (IMPAIR -Reactor Coolant System). This program models a number of the chemical and physical processes of iodine that are thought to be important at conditions of high temperature and pressure in the RCS. In Phase II, which is tentatively scheduled for 1997, IMPRCS will be implemented as a subroutine in IMPAIR-3. To ensure an efficient calculation, an interface/tracking system will be developed to control the use of the RCS model from the containment model. These two models will be interfaced in such a way that once the iodine is released from the RCS, it will no longer be tracked by the RCS model but will be tracked by the containment model. All RCS thermal-hydraulic parameters will be provided by other codes. (author) figs., tabs., refs.

  3. General informatics teaching with B-Learning teaching model

    Directory of Open Access Journals (Sweden)

    Nguyen The Dung

    2018-03-01

    Full Text Available Blended learning (B-learning, a combination of face-to-face teaching and E-learning-supported-teaching in an online course, and Information and Communication Technology (ICT tools have been studied in recent years. In addition, the use of this teaching model is effective in teaching and learning conditions in which some certain subjects are appropriate for the specific teaching context. As it has been a matter of concern of the universities in Vietnam today, deep studies related to this topic is crucial to be conducted. In this article, the process of developing online courses and organizing teaching for the General Informatics subject for first-year students at the Hue University of Education with B-learning teaching model will be presented. The combination of 60% face-to-face and 40% online learning.

  4. Universality in generalized models of inflation

    Energy Technology Data Exchange (ETDEWEB)

    Binétruy, P.; Pieroni, M. [AstroParticule et Cosmologie, Université Paris Diderot, CNRS, CEA, Observatoire de Paris, Sorbonne Paris Cité, 10, rue Alice Domon et Léonie Duquet, F-75205 Paris Cedex 13 (France); Mabillard, J., E-mail: pierre.binetruy@apc.univ-paris7.fr, E-mail: joel.mabillard@ed.ac.uk, E-mail: mauro.pieroni@apc.in2p3.fr [School of Physics and Astronomy, University of Edinburgh, Edinburgh, EH9 3JZ (United Kingdom)

    2017-03-01

    We discuss the cosmological evolution of a scalar field with non standard kinetic term in terms of a Renormalization Group Equation (RGE). In this framework inflation corresponds to the slow evolution in a neighborhood of a fixed point and universality classes for inflationary models naturally arise. Using some examples we show the application of the formalism. The predicted values for the speed of sound c {sub s} {sup 2} and for the amount of non-Gaussianities produced in these models are discussed. In particular, we show that it is possible to introduce models with c {sub s} {sup 2} ≠ 1 that can be in agreement with present cosmological observations.

  5. General circulation model study of atmospheric carbon monoxide

    International Nuclear Information System (INIS)

    Pinto, J.P.; Yung, Y.L.; Rind, D.; Russell, G.L.; Lerner, J.A.; Hansen, J.E.; Hameed, S.

    1983-01-01

    The carbon monoxide cycle is studied by incorporating the known and hypothetical sources and sinks in a tracer model that uses the winds generated by a general circulation model. Photochemical production and loss terms, which depend on OH radical concentrations, are calculated in an interactive fashion. The computed global distribution and seasonal variations of CO are compared with observations to obtain constraints on the distribution and magnitude of the sources and sinks of CO, and on the tropospheric abundance of OH. The simplest model that accounts for available observations requires a low latitude plant source of about 1.3 x 10 15 g yr -1 , in addition to sources from incomplete combustion of fossil fuels and oxidation of methane. The globally averaged OH concentration calculated in the model is 7 x 10 5 cm -3 . Models that calculate globally averaged OH concentrations much lower than our nominal value are not consistent with the observed variability of CO. Such models are also inconsistent with measurements of CO isotopic abundances, which imply the existence of plant sources

  6. Generalized Path Analysis and Generalized Simultaneous Equations Model for Recursive Systems with Responses of Mixed Types

    Science.gov (United States)

    Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang

    2006-01-01

    This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…

  7. Newton's constant from a minimal length: additional models

    International Nuclear Information System (INIS)

    Sahlmann, Hanno

    2011-01-01

    We follow arguments of Verlinde (2010 arXiv:1001.0785 [hep-th]) and Klinkhamer (2010 arXiv:1006.2094 [hep-th]), and construct two models of the microscopic theory of a holographic screen that allow for the thermodynamical derivation of Newton's law, with Newton's constant expressed in terms of a minimal length scale l contained in the area spectrum of the microscopic theory. One of the models is loosely related to the quantum structure of surfaces and isolated horizons in loop quantum gravity. Our investigation shows that the conclusions reached by Klinkhamer regarding the new length scale l seem to be generic in all their qualitative aspects.

  8. Moment based model predictive control for systems with additive uncertainty

    NARCIS (Netherlands)

    Saltik, M.B.; Ozkan, L.; Weiland, S.; Ludlage, J.H.A.

    2017-01-01

    In this paper, we present a model predictive control (MPC) strategy based on the moments of the state variables and the cost functional. The statistical properties of the state predictions are calculated through the open loop iteration of dynamics and used in the formulation of MPC cost function. We

  9. Double generalized linear compound poisson models to insurance claims data

    DEFF Research Database (Denmark)

    Andersen, Daniel Arnfeldt; Bonat, Wagner Hugo

    2017-01-01

    This paper describes the specification, estimation and comparison of double generalized linear compound Poisson models based on the likelihood paradigm. The models are motivated by insurance applications, where the distribution of the response variable is composed by a degenerate distribution...... implementation and illustrate the application of double generalized linear compound Poisson models using a data set about car insurances....

  10. The Five-Factor Model: General Overview

    Directory of Open Access Journals (Sweden)

    A A Vorobyeva

    2011-12-01

    Full Text Available The article describes the five-factor model (FFM, giving an overview of its history, basic dimensions, cross-cultural research conducted on the model and highlights some practical studies based on the FFM, including the studies on job performance, leader performance and daily social interactions. An overview of the recent five-factor theory is also provided. According to the theory, the five factors are encoded in human genes, therefore it is almost impossible to change the basic factors themselves, but a person's behavior might be changed due to characteristic adaptations which do not alter personality dimensions, only a person's behavior.

  11. Technical Work Plan for: Additional Multiscale Thermohydrologic Modeling

    International Nuclear Information System (INIS)

    B. Kirstein

    2006-01-01

    The primary objective of Revision 04 of the MSTHM report is to provide TSPA with revised repository-wide MSTHM analyses that incorporate updated percolation flux distributions, revised hydrologic properties, updated IEDs, and information pertaining to the emplacement of transport, aging, and disposal (TAD) canisters. The updated design information is primarily related to the incorporation of TAD canisters, but also includes updates related to superseded IEDs describing emplacement drift cross-sectional geometry and layout. The intended use of the results of Revision 04 of the MSTHM report, as described in this TWP, is to predict the evolution of TH conditions (temperature, relative humidity, liquid-phase saturation, and liquid-phase flux) at specified locations within emplacement drifts and in the adjoining near-field host rock along all emplacement drifts throughout the repository. This information directly supports the TSPA for the nominal and seismic scenarios. The revised repository-wide analyses are required to incorporate updated parameters and design information and to extend those analyses out to 1,000,000 years. Note that the previous MSTHM analyses reported in Revision 03 of Multiscale Thermohydrologic Model (BSC 2005 [DIRS 173944]) only extend out to 20,000 years. The updated parameters are the percolation flux distributions, including incorporation of post-10,000-year distributions, and updated calibrated hydrologic property values for the host-rock units. The applied calibrated hydrologic properties will be an updated version of those available in Calibrated Properties Model (BSC 2004 [DIRS 169857]). These updated properties will be documented in an Appendix of Revision 03 of UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]). The updated calibrated properties are applied because they represent the latest available information. The reasonableness of applying the updated calibrated' properties to the prediction of near-fieldin-drift TH conditions

  12. Esperanto: A Unique Model for General Linguistics.

    Science.gov (United States)

    Dulichenko, Aleksandr D.

    1988-01-01

    Esperanto presents a unique model for linguistic research by allowing the study of language development from project to fully functioning language. Esperanto provides insight into the growth of polysemy and redundancy, as well as into language universals and the phenomenon of social control. (Author/CB)

  13. Thermal modelling of extrusion based additive manufacturing of composite materials

    DEFF Research Database (Denmark)

    Jensen, Mathias Laustsen; Sonne, Mads Rostgaard; Hattel, Jesper Henri

    One of the hottest topics regarding manufacturing these years is additive manufacturing (AM). AM is a young branch of manufacturing techniques, which by nature is disruptive due to its completely different manufacturing approach, wherein material is added instead of removed. By adding material...... layer by layer, mould and customised tooling requirements from the conventional manufacturing are reduced or removed, which leads to increased customisation options and enables new part complexities without increasing the manufacturing cost. AM hence enables customised small volume productions...... of composite parts not feasible by conventional manufacturing techniques. This sets up new requirements to the part verification and validation, while conventional destructive tests become too expensive. This initial study aims to investigate alternative options to this destructive testing by increasing...

  14. Computable general equilibrium model fiscal year 2013 capability development report

    Energy Technology Data Exchange (ETDEWEB)

    Edwards, Brian Keith [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rivera, Michael Kelly [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Boero, Riccardo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-17

    This report documents progress made on continued developments of the National Infrastructure Simulation and Analysis Center (NISAC) Computable General Equilibrium Model (NCGEM), developed in fiscal year 2012. In fiscal year 2013, NISAC the treatment of the labor market and tests performed with the model to examine the properties of the solutions computed by the model. To examine these, developers conducted a series of 20 simulations for 20 U.S. States. Each of these simulations compared an economic baseline simulation with an alternative simulation that assumed a 20-percent reduction in overall factor productivity in the manufacturing industries of each State. Differences in the simulation results between the baseline and alternative simulations capture the economic impact of the reduction in factor productivity. While not every State is affected in precisely the same way, the reduction in manufacturing industry productivity negatively affects the manufacturing industries in each State to an extent proportional to the reduction in overall factor productivity. Moreover, overall economic activity decreases when manufacturing sector productivity is reduced. Developers ran two additional simulations: (1) a version of the model for the State of Michigan, with manufacturing divided into two sub-industries (automobile and other vehicle manufacturing as one sub-industry and the rest of manufacturing as the other subindustry); and (2) a version of the model for the United States, divided into 30 industries. NISAC conducted these simulations to illustrate the flexibility of industry definitions in NCGEM and to examine the simulation properties of in more detail.

  15. Multiple phase transitions in the generalized Curie-Weiss model

    International Nuclear Information System (INIS)

    Eisele, T.; Ellis, R.S.

    1988-01-01

    The generalized Curie-Weiss model is an extension of the classical Curie-Weiss model in which the quadratic interaction function of the mean spin value is replaced by a more general interaction function. It is shown that the generalized Curie-Weiss model can have a sequence of phase transitions at different critical temperatures. Both first-order and second-order phase transitions can occur, and explicit criteria for the two types are given. Three examples of generalized Curie-Weiss models are worked out in detail, including one example with infinitely many phase transitions. A number of results are derived using large-deviation techniques

  16. On A General Frame For Macroeconomic Modelling

    Directory of Open Access Journals (Sweden)

    Emil DINGA

    2012-03-01

    Full Text Available The purpose of the research project was to identify the methodological bases for the aggregate description of the Romanian national economy, both logically and in terms of the sources of empirical data for modelling. The specific objectives of the project were: a description of the economic markets in correlation with the logic description of the economic behaviours; b determination of the sectoral blocks of the Romanian economy, on the basis of the homogeneity of the economic; activity and behaviour; c association of the sectoral blocks to the national accounts, so as to ensure the sources of empirical data for the calibration and utilisation of the model; d association of the sectoral blocks to the economic markets; e association of the national accounts with the economic markets; f identification of the classes of interactions between the determined sectoral blocks.

  17. Generalized Mathai-Quillen Topological Sigma Models

    OpenAIRE

    Llatas, Pablo M.

    1995-01-01

    A simple field theoretical approach to Mathai-Quillen topological field theories of maps $X: M_I \\to M_T$ from an internal space to a target space is presented. As an example of applications of our formalism we compute by applying our formulas the action and Q-variations of the fields of two well known topological systems: Topological Quantum Mechanics and type-A topological Sigma Model.

  18. Reduced Order Modeling in General Relativity

    Science.gov (United States)

    Tiglio, Manuel

    2014-03-01

    Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).

  19. General Methods for Evolutionary Quantitative Genetic Inference from Generalized Mixed Models.

    Science.gov (United States)

    de Villemereuil, Pierre; Schielzeth, Holger; Nakagawa, Shinichi; Morrissey, Michael

    2016-11-01

    Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have inherently nonnormal distributions. The generalized linear mixed model (GLMM) framework has become a widely used tool for estimating quantitative genetic parameters for nonnormal traits. However, whereas GLMMs provide inference on a statistically convenient latent scale, it is often desirable to express quantitative genetic parameters on the scale upon which traits are measured. The parameters of fitted GLMMs, despite being on a latent scale, fully determine all quantities of potential interest on the scale on which traits are expressed. We provide expressions for deriving each of such quantities, including population means, phenotypic (co)variances, variance components including additive genetic (co)variances, and parameters such as heritability. We demonstrate that fixed effects have a strong impact on those parameters and show how to deal with this by averaging or integrating over fixed effects. The expressions require integration of quantities determined by the link function, over distributions of latent values. In general cases, the required integrals must be solved numerically, but efficient methods are available and we provide an implementation in an R package, QGglmm. We show that known formulas for quantities such as heritability of traits with binomial and Poisson distributions are special cases of our expressions. Additionally, we show how fitted GLMM can be incorporated into existing methods for predicting evolutionary trajectories. We demonstrate the accuracy of the resulting method for evolutionary prediction by simulation and apply our approach to data from a wild pedigreed vertebrate population. Copyright © 2016 de Villemereuil et al.

  20. Models and materials for generalized Kitaev magnetism

    Science.gov (United States)

    Winter, Stephen M.; Tsirlin, Alexander A.; Daghofer, Maria; van den Brink, Jeroen; Singh, Yogesh; Gegenwart, Philipp; Valentí, Roser

    2017-12-01

    The exactly solvable Kitaev model on the honeycomb lattice has recently received enormous attention linked to the hope of achieving novel spin-liquid states with fractionalized Majorana-like excitations. In this review, we analyze the mechanism proposed by Jackeli and Khaliullin to identify Kitaev materials based on spin-orbital dependent bond interactions and provide a comprehensive overview of its implications in real materials. We set the focus on experimental results and current theoretical understanding of planar honeycomb systems (Na2IrO3, α-Li2IrO3, and α-RuCl3), three-dimensional Kitaev materials (β- and γ-Li2IrO3), and other potential candidates, completing the review with the list of open questions awaiting new insights.

  1. Modeling electrokinetics in ionic liquids: General

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Chao [Physical and Computational Science Directorate, Pacific Northwest National Laboratory, Richland WA USA; Bao, Jie [Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland WA USA; Pan, Wenxiao [Department of Mechanical Engineering, University of Wisconsin-Madison, Madison WI USA; Sun, Xin [Physical and Computational Science Directorate, Pacific Northwest National Laboratory, Richland WA USA

    2017-04-07

    Using direct numerical simulations we provide a thorough study on the electrokinetics of ionic liquids. In particular, the modfied Poisson-Nernst-Planck (MPNP) equations are solved to capture the crowding and overscreening effects that are the characteristics of an ionic liquid. For modeling electrokinetic flows in an ionic liquid, the MPNP equations are coupled with the Navier-Stokes equations to study the coupling of ion transport, hydrodynamics, and electrostatic forces. Specifically, we consider the ion transport between two parallel plates, charging dynamics in a 2D straight-walled pore, electro-osmotic ow in a nano-channel, electroconvective instability on a plane ion-selective surface, and electroconvective ow on a curved ion-selective surface. We discuss how the crowding and overscreening effects and their interplay affect the electrokinetic behaviors of ionic liquids in these application problems.

  2. The DART general equilibrium model: A technical description

    OpenAIRE

    Springer, Katrin

    1998-01-01

    This paper provides a technical description of the Dynamic Applied Regional Trade (DART) General Equilibrium Model. The DART model is a recursive dynamic, multi-region, multi-sector computable general equilibrium model. All regions are fully specified and linked by bilateral trade flows. The DART model can be used to project economic activities, energy use and trade flows for each of the specified regions to simulate various trade policy as well as environmental policy scenarios, and to analy...

  3. Using 3D Printing (Additive Manufacturing) to Produce Low-Cost Simulation Models for Medical Training.

    Science.gov (United States)

    Lichtenberger, John P; Tatum, Peter S; Gada, Satyen; Wyn, Mark; Ho, Vincent B; Liacouras, Peter

    2018-03-01

    This work describes customized, task-specific simulation models derived from 3D printing in clinical settings and medical professional training programs. Simulation models/task trainers have an array of purposes and desired achievements for the trainee, defining that these are the first step in the production process. After this purpose is defined, computer-aided design and 3D printing (additive manufacturing) are used to create a customized anatomical model. Simulation models then undergo initial in-house testing by medical specialists followed by a larger scale beta testing. Feedback is acquired, via surveys, to validate effectiveness and to guide or determine if any future modifications and/or improvements are necessary. Numerous custom simulation models have been successfully completed with resulting task trainers designed for procedures, including removal of ocular foreign bodies, ultrasound-guided joint injections, nerve block injections, and various suturing and reconstruction procedures. These task trainers have been frequently utilized in the delivery of simulation-based training with increasing demand. 3D printing has been integral to the production of limited-quantity, low-cost simulation models across a variety of medical specialties. In general, production cost is a small fraction of a commercial, generic simulation model, if available. These simulation and training models are customized to the educational need and serve an integral role in the education of our military health professionals.

  4. Model for Assembly Line Re-Balancing Considering Additional Capacity and Outsourcing to Face Demand Fluctuations

    Science.gov (United States)

    Samadhi, TMAA; Sumihartati, Atin

    2016-02-01

    The most critical stage in a garment industry is sewing process, because generally, it consists of a number of operations and a large number of sewing machines for each operation. Therefore, it requires a balancing method that can assign task to work station with balance workloads. Many studies on assembly line balancing assume a new assembly line, but in reality, due to demand fluctuation and demand increased a re-balancing is needed. To cope with those fluctuating demand changes, additional capacity can be carried out by investing in spare sewing machine and paying for sewing service through outsourcing. This study develops an assembly line balancing (ALB) model on existing line to cope with fluctuating demand change. Capacity redesign is decided if the fluctuation demand exceeds the available capacity through a combination of making investment on new machines and outsourcing while considering for minimizing the cost of idle capacity in the future. The objective of the model is to minimize the total cost of the line assembly that consists of operating costs, machine cost, adding capacity cost, losses cost due to idle capacity and outsourcing costs. The model develop is based on an integer programming model. The model is tested for a set of data of one year demand with the existing number of sewing machines of 41 units. The result shows that additional maximum capacity up to 76 units of machine required when there is an increase of 60% of the average demand, at the equal cost parameters..

  5. A QCD Model Using Generalized Yang-Mills Theory

    International Nuclear Information System (INIS)

    Wang Dianfu; Song Heshan; Kou Lina

    2007-01-01

    Generalized Yang-Mills theory has a covariant derivative, which contains both vector and scalar gauge bosons. Based on this theory, we construct a strong interaction model by using the group U(4). By using this U(4) generalized Yang-Mills model, we also obtain a gauge potential solution, which can be used to explain the asymptotic behavior and color confinement.

  6. Modeling of non-additive mixture properties using the Online CHEmical database and Modeling environment (OCHEM

    Directory of Open Access Journals (Sweden)

    Oprisiu Ioana

    2013-01-01

    Full Text Available Abstract The Online Chemical Modeling Environment (OCHEM, http://ochem.eu is a web-based platform that provides tools for automation of typical steps necessary to create a predictive QSAR/QSPR model. The platform consists of two major subsystems: a database of experimental measurements and a modeling framework. So far, OCHEM has been limited to the processing of individual compounds. In this work, we extended OCHEM with a new ability to store and model properties of binary non-additive mixtures. The developed system is publicly accessible, meaning that any user on the Web can store new data for binary mixtures and develop models to predict their non-additive properties. The database already contains almost 10,000 data points for the density, bubble point, and azeotropic behavior of binary mixtures. For these data, we developed models for both qualitative (azeotrope/zeotrope and quantitative endpoints (density and bubble points using different learning methods and specially developed descriptors for mixtures. The prediction performance of the models was similar to or more accurate than results reported in previous studies. Thus, we have developed and made publicly available a powerful system for modeling mixtures of chemical compounds on the Web.

  7. Diabatic models with transferrable parameters for generalized chemical reactions

    International Nuclear Information System (INIS)

    Reimers, Jeffrey R; McKemmish, Laura K; McKenzie, Ross H; Hush, Noel S

    2017-01-01

    Diabatic models applied to adiabatic electron-transfer theory yield many equations involving just a few parameters that connect ground-state geometries and vibration frequencies to excited-state transition energies and vibration frequencies to the rate constants for electron-transfer reactions, utilizing properties of the conical-intersection seam linking the ground and excited states through the Pseudo Jahn-Teller effect. We review how such simplicity in basic understanding can also be obtained for general chemical reactions. The key feature that must be recognized is that electron-transfer (or hole transfer) processes typically involve one electron (hole) moving between two orbitals, whereas general reactions typically involve two electrons or even four electrons for processes in aromatic molecules. Each additional moving electron leads to new high-energy but interrelated conical-intersection seams that distort the shape of the critical lowest-energy seam. Recognizing this feature shows how conical-intersection descriptors can be transferred between systems, and how general chemical reactions can be compared using the same set of simple parameters. Mathematical relationships are presented depicting how different conical-intersection seams relate to each other, showing that complex problems can be reduced into an effective interaction between the ground-state and a critical excited state to provide the first semi-quantitative implementation of Shaik’s “twin state” concept. Applications are made (i) demonstrating why the chemistry of the first-row elements is qualitatively so different to that of the second and later rows, (ii) deducing the bond-length alternation in hypothetical cyclohexatriene from the observed UV spectroscopy of benzene, (iii) demonstrating that commonly used procedures for modelling surface hopping based on inclusion of only the first-derivative correction to the Born-Oppenheimer approximation are valid in no region of the chemical

  8. A generalized model via random walks for information filtering

    International Nuclear Information System (INIS)

    Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

    2016-01-01

    There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

  9. A generalized model via random walks for information filtering

    Energy Technology Data Exchange (ETDEWEB)

    Ren, Zhuo-Ming, E-mail: zhuomingren@gmail.com [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Kong, Yixiu [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Shang, Ming-Sheng, E-mail: msshang@cigit.ac.cn [Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Zhang, Yi-Cheng [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland)

    2016-08-06

    There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

  10. Can ligand addition to soil enhance Cd phytoextraction? A mechanistic model study.

    Science.gov (United States)

    Lin, Zhongbing; Schneider, André; Nguyen, Christophe; Sterckeman, Thibault

    2014-11-01

    Phytoextraction is a potential method for cleaning Cd-polluted soils. Ligand addition to soil is expected to enhance Cd phytoextraction. However, experimental results show that this addition has contradictory effects on plant Cd uptake. A mechanistic model simulating the reaction kinetics (adsorption on solid phase, complexation in solution), transport (convection, diffusion) and root absorption (symplastic, apoplastic) of Cd and its complexes in soil was developed. This was used to calculate plant Cd uptake with and without ligand addition in a great number of combinations of soil, ligand and plant characteristics, varying the parameters within defined domains. Ligand addition generally strongly reduced hydrated Cd (Cd(2+)) concentration in soil solution through Cd complexation. Dissociation of Cd complex ([Formula: see text]) could not compensate for this reduction, which greatly lowered Cd(2+) symplastic uptake by roots. The apoplastic uptake of [Formula: see text] was not sufficient to compensate for the decrease in symplastic uptake. This explained why in the majority of the cases, ligand addition resulted in the reduction of the simulated Cd phytoextraction. A few results showed an enhanced phytoextraction in very particular conditions (strong plant transpiration with high apoplastic Cd uptake capacity), but this enhancement was very limited, making chelant-enhanced phytoextraction poorly efficient for Cd.

  11. Aspects of Additional Psychiatric Disorders in Severe Depression/Melancholia: A Comparison between Suicides and Controls and General Pattern

    Directory of Open Access Journals (Sweden)

    Ulrika Heu

    2018-06-01

    Full Text Available Objective: Additional and comorbid diagnoses are common among suicide victims with major depressive disorder (MDD and have been shown to increase the suicide risk. The aim of the present study was first, to investigate whether patients with severe depression/melancholia who had died by suicide showed more additional psychiatric disorders than a matched control group. Second, general rates of comorbid and additional diagnoses in the total group of patients were estimated and compared with literature on MDD. Method: A blind record evaluation was performed on 100 suicide victims with severe depression/melancholia (MDD with melancholic and/or psychotic features: MDD-M/P and matched controls admitted to the Department of Psychiatry, Lund, Sweden between 1956 and 1969 and monitored to 2010. Diagnoses in addition to severe depression were noted. Results: Less than half of both the suicides and controls had just one psychiatric disorder (47% in the suicide and 46% in the control group. The average number of diagnoses was 1.80 and 1.82, respectively. Additional diagnoses were not related to an increased suicide risk. Anxiety was the most common diagnosis. Occurrence of suspected schizophrenia/schizotypal or additional obsessive-compulsive symptoms were more common than expected, but alcohol use disorders did not appear very frequent. Conclusions: The known increased risk of suicide in MDD with comorbid/additional diagnoses does not seem to apply to persons with MDD-M/P (major depressive disorder-depression/Melancholia. Some diagnoses, such as schizophrenia/schizotypal disorders, were more frequent than expected, which is discussed, and a genetic overlap with MDD-M/P is proposed.

  12. Modeling of space environment impact on nanostructured materials. General principles

    Science.gov (United States)

    Voronina, Ekaterina; Novikov, Lev

    2016-07-01

    In accordance with the resolution of ISO TC20/SC14 WG4/WG6 joint meeting, Technical Specification (TS) 'Modeling of space environment impact on nanostructured materials. General principles' which describes computer simulation methods of space environment impact on nanostructured materials is being prepared. Nanomaterials surpass traditional materials for space applications in many aspects due to their unique properties associated with nanoscale size of their constituents. This superiority in mechanical, thermal, electrical and optical properties will evidently inspire a wide range of applications in the next generation spacecraft intended for the long-term (~15-20 years) operation in near-Earth orbits and the automatic and manned interplanetary missions. Currently, ISO activity on developing standards concerning different issues of nanomaterials manufacturing and applications is high enough. Most such standards are related to production and characterization of nanostructures, however there is no ISO documents concerning nanomaterials behavior in different environmental conditions, including the space environment. The given TS deals with the peculiarities of the space environment impact on nanostructured materials (i.e. materials with structured objects which size in at least one dimension lies within 1-100 nm). The basic purpose of the document is the general description of the methodology of applying computer simulation methods which relate to different space and time scale to modeling processes occurring in nanostructured materials under the space environment impact. This document will emphasize the necessity of applying multiscale simulation approach and present the recommendations for the choice of the most appropriate methods (or a group of methods) for computer modeling of various processes that can occur in nanostructured materials under the influence of different space environment components. In addition, TS includes the description of possible

  13. The effects of the addition of a pediatric surgery fellow on the operative experience of the general surgery resident.

    Science.gov (United States)

    Raines, Alexander; Garwe, Tabitha; Adeseye, Ademola; Ruiz-Elizalde, Alejandro; Churchill, Warren; Tuggle, David; Mantor, Cameron; Lees, Jason

    2015-06-01

    Adding fellows to surgical departments with residency programs can affect resident education. Our specific aim was to evaluate the effect of adding a pediatric surgery (PS) fellow on the number of index PS cases logged by the general surgery (GS) residents. At a single institution with both PS and GS programs, we examined the number of logged cases for the fellows and residents over 10 years [5 years before (Time 1) and 5 years after (Time 2) the addition of a PS fellow]. Additionally, the procedure related relative value units (RVUs) recorded by the faculty were evaluated. The fellows averaged 752 and 703 cases during Times 1 and 2, respectively, decreasing by 49 (P = 0.2303). The residents averaged 172 and 161 cases annually during Time 1 and Time 2, respectively, decreasing by 11 (P = 0.7340). The total number of procedure related RVUs was 4627 and 6000 during Times 1 and 2, respectively. The number of cases logged by the PS fellows and GS residents decreased after the addition of a PS fellow; however, the decrease was not significant. Programs can reasonably add an additional PS fellow, but care should be taken especially in programs that are otherwise static in size.

  14. Reliability assessment of competing risks with generalized mixed shock models

    International Nuclear Information System (INIS)

    Rafiee, Koosha; Feng, Qianmei; Coit, David W.

    2017-01-01

    This paper investigates reliability modeling for systems subject to dependent competing risks considering the impact from a new generalized mixed shock model. Two dependent competing risks are soft failure due to a degradation process, and hard failure due to random shocks. The shock process contains fatal shocks that can cause hard failure instantaneously, and nonfatal shocks that impact the system in three different ways: 1) damaging the unit by immediately increasing the degradation level, 2) speeding up the deterioration by accelerating the degradation rate, and 3) weakening the unit strength by reducing the hard failure threshold. While the first impact from nonfatal shocks comes from each individual shock, the other two impacts are realized when the condition for a new generalized mixed shock model is satisfied. Unlike most existing mixed shock models that consider a combination of two shock patterns, our new generalized mixed shock model includes three classic shock patterns. According to the proposed generalized mixed shock model, the degradation rate and the hard failure threshold can simultaneously shift multiple times, whenever the condition for one of these three shock patterns is satisfied. An example using micro-electro-mechanical systems devices illustrates the effectiveness of the proposed approach with sensitivity analysis. - Highlights: • A rich reliability model for systems subject to dependent failures is proposed. • The degradation rate and the hard failure threshold can shift simultaneously. • The shift is triggered by a new generalized mixed shock model. • The shift can occur multiple times under the generalized mixed shock model.

  15. Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

    Science.gov (United States)

    DeCarlo, Lawrence T

    2003-02-01

    The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

  16. A general description of additive and nonadditive elements of sperm competitiveness and their relation to male fertilization success.

    Science.gov (United States)

    Engqvist, Leif

    2013-05-01

    A complete understanding of male reproductive success, and thus sexual selection, often requires an insight into male success in sperm competition. Genuine conclusions on male sperm competitiveness can only be made in real competitive situations. However, statistical analyses of sperm competitiveness from fertilization success data have been shown to be problematic. Here, I first outline a comprehensive general description of the different additive and nonadditive elements relevant for the outcome of sperm competition staged between two males. Based on this description, I will highlight two main problems that are frequently encountered in experiments aiming at estimating sperm competitiveness. First, I focus on potential problems when using standardized competitors versus random mating trials, because trials with standardized competitors do not allow generalization if male-male interactions are important. Second, I illustrate the necessity to analyze data on the logit scale rather than on raw proportions, because only the logit scale allows a clean separation of additive and nonadditive effects (i.e., male × male and female × male interactions). © 2012 The Author(s). Evolution © 2012 The Society for the Study of Evolution.

  17. Learning general phonological rules from distributional information: a computational model.

    Science.gov (United States)

    Calamaro, Shira; Jarosz, Gaja

    2015-04-01

    Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony (Peperkamp, Le Calvez, Nadal, & Dupoux, 2006). This paper extends the model to account for learning of a broader set of phonological alternations and the formalization of these alternations as general rules. In Experiment 1, we apply the original model to new data in Dutch and demonstrate its limitations in learning nonallophonic rules. In Experiment 2, we extend the model to allow it to learn general rules for alternations that apply to a class of segments. In Experiment 3, the model is further extended to allow for generalization by context; we argue that this generalization must be constrained by linguistic principles. Copyright © 2014 Cognitive Science Society, Inc.

  18. General Friction Model Extended by the Effect of Strain Hardening

    DEFF Research Database (Denmark)

    Nielsen, Chris V.; Martins, Paulo A.F.; Bay, Niels

    2016-01-01

    An extension to the general friction model proposed by Wanheim and Bay [1] to include the effect of strain hardening is proposed. The friction model relates the friction stress to the fraction of real contact area by a friction factor under steady state sliding. The original model for the real...... contact area as function of the normalized contact pressure is based on slip-line analysis and hence on the assumption of rigid-ideally plastic material behavior. In the present work, a general finite element model is established to, firstly, reproduce the original model under the assumption of rigid...

  19. Kalman Filter for Generalized 2-D Roesser Models

    Institute of Scientific and Technical Information of China (English)

    SHENG Mei; ZOU Yun

    2007-01-01

    The design problem of the state filter for the generalized stochastic 2-D Roesser models, which appears when both the state and measurement are simultaneously subjected to the interference from white noise, is discussed. The wellknown Kalman filter design is extended to the generalized 2-D Roesser models. Based on the method of "scanning line by line", the filtering problem of generalized 2-D Roesser models with mode-energy reconstruction is solved. The formula of the optimal filtering, which minimizes the variance of the estimation error of the state vectors, is derived. The validity of the designed filter is verified by the calculation steps and the examples are introduced.

  20. Generalized Linear Models with Applications in Engineering and the Sciences

    CERN Document Server

    Myers, Raymond H; Vining, G Geoffrey; Robinson, Timothy J

    2012-01-01

    Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities."-Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Ma

  1. Topsoil organic carbon content of Europe, a new map based on a generalised additive model

    Science.gov (United States)

    de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

    2014-05-01

    There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average

  2. Critical Comments on the General Model of Instructional Communication

    Science.gov (United States)

    Walton, Justin D.

    2014-01-01

    This essay presents a critical commentary on McCroskey et al.'s (2004) general model of instructional communication. In particular, five points are examined which make explicit and problematize the meta-theoretical assumptions of the model. Comments call attention to the limitations of the model and argue for a broader approach to…

  3. Membrane models and generalized Z2 gauge theories

    International Nuclear Information System (INIS)

    Lowe, M.J.; Wallace, D.J.

    1980-01-01

    We consider models of (d-n)-dimensional membranes fluctuating in a d-dimensional space under the action of surface tension. We investigate the renormalization properties of these models perturbatively and in 1/n expansion. The potential relationships of these models to generalized Z 2 gauge theories are indicated. (orig.)

  4. A Duality Result for the Generalized Erlang Risk Model

    Directory of Open Access Journals (Sweden)

    Lanpeng Ji

    2014-11-01

    Full Text Available In this article, we consider the generalized Erlang risk model and its dual model. By using a conditional measure-preserving correspondence between the two models, we derive an identity for two interesting conditional probabilities. Applications to the discounted joint density of the surplus prior to ruin and the deficit at ruin are also discussed.

  5. A Generalized Partial Credit Model: Application of an EM Algorithm.

    Science.gov (United States)

    Muraki, Eiji

    1992-01-01

    The partial credit model with a varying slope parameter is developed and called the generalized partial credit model (GPCM). Analysis results for simulated data by this and other polytomous item-response models demonstrate that the rating formulation of the GPCM is adaptable to the analysis of polytomous item responses. (SLD)

  6. Linear and Generalized Linear Mixed Models and Their Applications

    CERN Document Server

    Jiang, Jiming

    2007-01-01

    This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested

  7. Vacuum Expectation Value Profiles of the Bulk Scalar Field in the Generalized Randall-Sundrum Model

    International Nuclear Information System (INIS)

    Moazzen, M.; Tofighi, A.; Farokhtabar, A.

    2015-01-01

    In the generalized Randall-Sundrum warped brane-world model the cosmological constant induced on the visible brane can be positive or negative. In this paper we investigate profiles of vacuum expectation value of the bulk scalar field under general Dirichlet and Neumann boundary conditions in the generalized warped brane-world model. We show that the VEV profiles generally depend on the value of the brane cosmological constant. We find that the VEV profiles of the bulk scalar field for a visible brane with negative cosmological constant and positive tension are quite distinct from those of Randall-Sundrum model. In addition we show that the VEV profiles for a visible brane with large positive cosmological constant are also different from those of the Randall-Sundrum model. We also verify that Goldberger and Wise mechanism can work under nonzero Dirichlet boundary conditions in the generalized Randall-Sundrum model.

  8. a Proposal for Generalization of 3d Models

    Science.gov (United States)

    Uyar, A.; Ulugtekin, N. N.

    2017-11-01

    In recent years, 3D models have been created of many cities around the world. Most of the 3D city models have been introduced as completely graphic or geometric models, and the semantic and topographic aspects of the models have been neglected. In order to use 3D city models beyond the task, a generalization is necessary. CityGML is an open data model and XML-based format for the storage and exchange of virtual 3D city models. Level of Details (LoD) which is an important concept for 3D modelling, can be defined as outlined degree or prior representation of real-world objects. The paper aim is first describes some requirements of 3D model generalization, then presents problems and approaches that have been developed in recent years. In conclude the paper will be a summary and outlook on problems and future work.

  9. General classical solutions in the noncommutative CPN-1 model

    International Nuclear Information System (INIS)

    Foda, O.; Jack, I.; Jones, D.R.T.

    2002-01-01

    We give an explicit construction of general classical solutions for the noncommutative CP N-1 model in two dimensions, showing that they correspond to integer values for the action and topological charge. We also give explicit solutions for the Dirac equation in the background of these general solutions and show that the index theorem is satisfied

  10. Parameter Estimation for a Computable General Equilibrium Model

    DEFF Research Database (Denmark)

    Arndt, Channing; Robinson, Sherman; Tarp, Finn

    2002-01-01

    We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of non-linear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...

  11. Parameter Estimation for a Computable General Equilibrium Model

    DEFF Research Database (Denmark)

    Arndt, Channing; Robinson, Sherman; Tarp, Finn

    We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (CGE) models. The approach applies information theory to estimating a system of nonlinear simultaneous equations. It has a number of advantages. First, it imposes all general equilibrium constraints...

  12. Dividend taxation in an infinite-horizon general equilibrium model

    OpenAIRE

    Pham, Ngoc-Sang

    2017-01-01

    We consider an infinite-horizon general equilibrium model with heterogeneous agents and financial market imperfections. We investigate the role of dividend taxation on economic growth and asset price. The optimal dividend taxation is also studied.

  13. Two point function for a simple general relativistic quantum model

    OpenAIRE

    Colosi, Daniele

    2007-01-01

    We study the quantum theory of a simple general relativistic quantum model of two coupled harmonic oscillators and compute the two-point function following a proposal first introduced in the context of loop quantum gravity.

  14. Generalized model for Memristor-based Wien family oscillators

    KAUST Repository

    Talukdar, Abdul Hafiz Ibne; Radwan, Ahmed G.; Salama, Khaled N.

    2012-01-01

    In this paper, we report the unconventional characteristics of Memristor in Wien oscillators. Generalized mathematical models are developed to analyze four members of the Wien family using Memristors. Sustained oscillation is reported for all types

  15. The DINA model as a constrained general diagnostic model: Two variants of a model equivalency.

    Science.gov (United States)

    von Davier, Matthias

    2014-02-01

    The 'deterministic-input noisy-AND' (DINA) model is one of the more frequently applied diagnostic classification models for binary observed responses and binary latent variables. The purpose of this paper is to show that the model is equivalent to a special case of a more general compensatory family of diagnostic models. Two equivalencies are presented. Both project the original DINA skill space and design Q-matrix using mappings into a transformed skill space as well as a transformed Q-matrix space. Both variants of the equivalency produce a compensatory model that is mathematically equivalent to the (conjunctive) DINA model. This equivalency holds for all DINA models with any type of Q-matrix, not only for trivial (simple-structure) cases. The two versions of the equivalency presented in this paper are not implied by the recently suggested log-linear cognitive diagnosis model or the generalized DINA approach. The equivalencies presented here exist independent of these recently derived models since they solely require a linear - compensatory - general diagnostic model without any skill interaction terms. Whenever it can be shown that one model can be viewed as a special case of another more general one, conclusions derived from any particular model-based estimates are drawn into question. It is widely known that multidimensional models can often be specified in multiple ways while the model-based probabilities of observed variables stay the same. This paper goes beyond this type of equivalency by showing that a conjunctive diagnostic classification model can be expressed as a constrained special case of a general compensatory diagnostic modelling framework. © 2013 The British Psychological Society.

  16. A Generalized QMRA Beta-Poisson Dose-Response Model.

    Science.gov (United States)

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

    2016-10-01

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

  17. Specific and General Human Capital in an Endogenous Growth Model

    OpenAIRE

    Evangelia Vourvachaki; Vahagn Jerbashian; : Sergey Slobodyan

    2014-01-01

    In this article, we define specific (general) human capital in terms of the occupations whose use is spread in a limited (wide) set of industries. We analyze the growth impact of an economy's composition of specific and general human capital, in a model where education and research and development are costly and complementary activities. The model suggests that a declining share of specific human capital, as observed in the Czech Republic, can be associated with a lower rate of long-term grow...

  18. Dynamical CP violation of the generalized Yang-Mills model

    International Nuclear Information System (INIS)

    Wang Dianfu; Chang Xiaojing; Sun Xiaoyu

    2011-01-01

    Starting from the generalized Yang-Mills model which contains, besides the vector part V μ , also a scalar part S and a pseudoscalar part P . It is shown, in terms of the Nambu-Jona-Lasinio (NJL) mechanism, that CP violation can be realized dynamically. The combination of the generalized Yang-Mills model and the NJL mechanism provides a new way to explain CP violation. (authors)

  19. Validation analysis of probabilistic models of dietary exposure to food additives.

    Science.gov (United States)

    Gilsenan, M B; Thompson, R L; Lambe, J; Gibney, M J

    2003-10-01

    The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above 'true' additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (2(3)) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above 'true' intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty.

  20. Modelling time course gene expression data with finite mixtures of linear additive models.

    Science.gov (United States)

    Grün, Bettina; Scharl, Theresa; Leisch, Friedrich

    2012-01-15

    A model class of finite mixtures of linear additive models is presented. The component-specific parameters in the regression models are estimated using regularized likelihood methods. The advantages of the regularization are that (i) the pre-specified maximum degrees of freedom for the splines is less crucial than for unregularized estimation and that (ii) for each component individually a suitable degree of freedom is selected in an automatic way. The performance is evaluated in a simulation study with artificial data as well as on a yeast cell cycle dataset of gene expression levels over time. The latest release version of the R package flexmix is available from CRAN (http://cran.r-project.org/).

  1. A general model for membrane-based separation processes

    DEFF Research Database (Denmark)

    Soni, Vipasha; Abildskov, Jens; Jonsson, Gunnar Eigil

    2009-01-01

    behaviour will play an important role. In this paper, modelling of membrane-based processes for separation of gas and liquid mixtures are considered. Two general models, one for membrane-based liquid separation processes (with phase change) and another for membrane-based gas separation are presented....... The separation processes covered are: membrane-based gas separation processes, pervaporation and various types of membrane distillation processes. The specific model for each type of membrane-based process is generated from the two general models by applying the specific system descriptions and the corresponding...

  2. Generalized continua as models for classical and advanced materials

    CERN Document Server

    Forest, Samuel

    2016-01-01

    This volume is devoted to an actual topic which is the focus world-wide of various research groups. It contains contributions describing the material behavior on different scales, new existence and uniqueness theorems, the formulation of constitutive equations for advanced materials. The main emphasis of the contributions is directed on the following items - Modelling and simulation of natural and artificial materials with significant microstructure, - Generalized continua as a result of multi-scale models, - Multi-field actions on materials resulting in generalized material models, - Theories including higher gradients, and - Comparison with discrete modelling approaches.

  3. Pricing Participating Products under a Generalized Jump-Diffusion Model

    Directory of Open Access Journals (Sweden)

    Tak Kuen Siu

    2008-01-01

    Full Text Available We propose a model for valuing participating life insurance products under a generalized jump-diffusion model with a Markov-switching compensator. It also nests a number of important and popular models in finance, including the classes of jump-diffusion models and Markovian regime-switching models. The Esscher transform is employed to determine an equivalent martingale measure. Simulation experiments are conducted to illustrate the practical implementation of the model and to highlight some features that can be obtained from our model.

  4. International Competition and Inequality: A Generalized Ricardian Model

    OpenAIRE

    Adolfo Figueroa

    2014-01-01

    Why does the gap in real wage rates persist between the First World and the Third World after so many years of increasing globalization? The standard neoclassical trade model predicts that real wage rates will be equalized with international trade, whereas the standard Ricardian trade model does not. Facts are thus consistent with the Ricardian model. However, this model leaves undetermined income distribution. The objective of this paper is to fill this gap by developing a generalized Ricard...

  5. Adaptation of a general circulation model to ocean dynamics

    Science.gov (United States)

    Turner, R. E.; Rees, T. H.; Woodbury, G. E.

    1976-01-01

    A primitive-variable general circulation model of the ocean was formulated in which fast external gravity waves are suppressed with rigid-lid surface constraint pressires which also provide a means for simulating the effects of large-scale free-surface topography. The surface pressure method is simpler to apply than the conventional stream function models, and the resulting model can be applied to both global ocean and limited region situations. Strengths and weaknesses of the model are also presented.

  6. Regional disaster impact analysis: comparing Input-Output and Computable General Equilibrium models

    NARCIS (Netherlands)

    Koks, E.E.; Carrera, L.; Jonkeren, O.; Aerts, J.C.J.H.; Husby, T.G.; Thissen, M.; Standardi, G.; Mysiak, J.

    2016-01-01

    A variety of models have been applied to assess the economic losses of disasters, of which the most common ones are input-output (IO) and computable general equilibrium (CGE) models. In addition, an increasing number of scholars have developed hybrid approaches: one that combines both or either of

  7. A generalized statistical model for the size distribution of wealth

    International Nuclear Information System (INIS)

    Clementi, F; Gallegati, M; Kaniadakis, G

    2012-01-01

    In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature. (paper)

  8. A generalized statistical model for the size distribution of wealth

    Science.gov (United States)

    Clementi, F.; Gallegati, M.; Kaniadakis, G.

    2012-12-01

    In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature.

  9. Worst case prediction of additives migration from polystyrene for food safety purposes: a model update.

    Science.gov (United States)

    Martínez-López, Brais; Gontard, Nathalie; Peyron, Stéphane

    2018-03-01

    A reliable prediction of migration levels of plastic additives into food requires a robust estimation of diffusivity. Predictive modelling of diffusivity as recommended by the EU commission is carried out using a semi-empirical equation that relies on two polymer-dependent parameters. These parameters were determined for the polymers most used by packaging industry (LLDPE, HDPE, PP, PET, PS, HIPS) from the diffusivity data available at that time. In the specific case of general purpose polystyrene, the diffusivity data published since then shows that the use of the equation with the original parameters results in systematic underestimation of diffusivity. The goal of this study was therefore, to propose an update of the aforementioned parameters for PS on the basis of up to date diffusivity data, so the equation can be used for a reasoned overestimation of diffusivity.

  10. Robot-based additive manufacturing for flexible die-modelling in incremental sheet forming

    Science.gov (United States)

    Rieger, Michael; Störkle, Denis Daniel; Thyssen, Lars; Kuhlenkötter, Bernd

    2017-10-01

    The paper describes the application concept of additive manufactured dies to support the robot-based incremental sheet metal forming process (`Roboforming') for the production of sheet metal components in small batch sizes. Compared to the dieless kinematic-based generation of a shape by means of two cooperating industrial robots, the supporting robot models a die on the back of the metal sheet by using the robot-based fused layer manufacturing process (FLM). This tool chain is software-defined and preserves the high geometrical form flexibility of Roboforming while flexibly generating support structures adapted to the final part's geometry. Test series serve to confirm the feasibility of the concept by investigating the process challenges of the adhesion to the sheet surface and the general stability as well as the influence on the geometric accuracy compared to the well-known forming strategies.

  11. Transport methods: general. 3. An Additive Angular-Dependent Re-balance Acceleration Method for Neutron Transport Equations

    International Nuclear Information System (INIS)

    Cho, Nam Zin; Park, Chang Je

    2001-01-01

    An additive angular-dependent re-balance (AADR) factor acceleration method is described to accelerate the source iteration of discrete ordinates transport calculation. The formulation of the AADR method follows that of the angular-dependent re-balance (ADR) method in that the re-balance factor is defined only on the cell interface and in that the low-order equation is derived by integrating the transport equation (high-order equation) over angular subspaces. But, the re-balance factor is applied additively. While the AADR method is similar to the boundary projection acceleration and the alpha-weighted linear acceleration, it is more general and does have distinct features. The method is easily extendible to DP N and low-order S N re-balancing, and it does not require consistent discretizations between the high- and low-order equations as in diffusion synthetic acceleration. We find by Fourier analysis and numerical results that the AADR method with a chosen form of weighting functions is unconditionally stable and very effective. There also exists an optimal weighting parameter that leads to the smallest spectral radius. The AADR acceleration method described in this paper is simple to implement, unconditionally stable, and very effective. It uses a physically based weighting function with an optimal parameter, leading to the best spectral radius of ρ<0.1865, compared to ρ<0.2247 of DSA. The application of the AADR acceleration method with the LMB scheme on a test problem shows encouraging results

  12. Generalized entropy formalism and a new holographic dark energy model

    Science.gov (United States)

    Sayahian Jahromi, A.; Moosavi, S. A.; Moradpour, H.; Morais Graça, J. P.; Lobo, I. P.; Salako, I. G.; Jawad, A.

    2018-05-01

    Recently, the Rényi and Tsallis generalized entropies have extensively been used in order to study various cosmological and gravitational setups. Here, using a special type of generalized entropy, a generalization of both the Rényi and Tsallis entropy, together with holographic principle, we build a new model for holographic dark energy. Thereinafter, considering a flat FRW universe, filled by a pressureless component and the new obtained dark energy model, the evolution of cosmos has been investigated showing satisfactory results and behavior. In our model, the Hubble horizon plays the role of IR cutoff, and there is no mutual interaction between the cosmos components. Our results indicate that the generalized entropy formalism may open a new window to become more familiar with the nature of spacetime and its properties.

  13. A generalized model via random walks for information filtering

    Science.gov (United States)

    Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

    2016-08-01

    There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation.

  14. 78 FR 12271 - Wireline Competition Bureau Seeks Additional Comment In Connect America Cost Model Virtual Workshop

    Science.gov (United States)

    2013-02-22

    ... Competition Bureau seeks public input on additional questions relating to modeling voice capability and Annual... the model. 4. The Bureau now seeks public input on additional questions relating to modeling voice... with fewer than 25 employees, pursuant to the Small Business Paperwork Relief Act of 2002, Public Law...

  15. Additive model for thermal comfort generated by matrix experiment using orthogonal array

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, Reuy-Lung [Department of Occupational Safety and Health, China Medical University, 91 Huseh-shin Road, Taichung 404 (China); Lin, Tzu-Ping [Department of Leisure Planning, National Formosa University, 64 Wen-hua Road, Huwei, Yunlin 632 (China); Liang, Han-Hsi [Department of Architecture, National United University, No. 1, Lien Da, Kung-Ching Li, Miaoli 360 (China); Yang, Kuan-Hsiug; Yeh, Tsung-Chyn [Department of Mechanical and Electro-Mechanical Engineering, National Sun Yet-Sen University, No. 91, Lien-hai Road, Kaohsiung (China)

    2009-08-15

    In addition to ensuring the thermal comfort of occupants, monitoring and controlling indoor thermal environments can reduce the energy consumed by air conditioning systems. This study develops an additive model for predicting thermal comfort with rapid and simple arithmetic calculations. The advantage of the additive model is its comprehensibility to administrators of air conditioning systems, who are unfamiliar with the PMV-PPD model but want to adjust an indoor environment to save energy without generating complaints of discomfort from occupants. In order to generate the additive model, a laboratory chamber experiment based on matrix experiment using orthogonal array, was performed. By applying the analysis of variance on observed thermal sensation votes and percentage of dissatisfaction, the factor effects of environmental variables that account for the additive model were determined. Additionally, the applicability of the PMV-PPD model in hot and humid climates is discussed in this study, based on experimental results. (author)

  16. Merons in a generally covariant model with Gursey term

    International Nuclear Information System (INIS)

    Akdeniz, K.G.; Smailagic, A.

    1982-10-01

    We study meron solutions of the generally covariant and Weyl invariant fermionic model with Gursey term. We find that, due to the presence of this term, merons can exist even without the cosmological constant. This is a new feature compared to previously studied models. (author)

  17. Simulation modelling in agriculture: General considerations. | R.I. ...

    African Journals Online (AJOL)

    A computer simulation model is a detailed working hypothesis about a given system. The computer does all the necessary arithmetic when the hypothesis is invoked to predict the future behaviour of the simulated system under given conditions.A general pragmatic approach to model building is discussed; techniques are ...

  18. Response of an ocean general circulation model to wind and ...

    Indian Academy of Sciences (India)

    The stretched-coordinate ocean general circulation model has been designed to study the observed variability due to wind and thermodynamic forcings. The model domain extends from 60°N to 60°S and cyclically continuous in the longitudinal direction. The horizontal resolution is 5° × 5° and 9 discrete vertical levels.

  19. General Separations Area (GSA) Groundwater Flow Model Update: Hydrostratigraphic Data

    Energy Technology Data Exchange (ETDEWEB)

    Bagwell, L. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Bennett, P. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Flach, G. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-02-21

    This document describes the assembly, selection, and interpretation of hydrostratigraphic data for input to an updated groundwater flow model for the General Separations Area (GSA; Figure 1) at the Department of Energy’s (DOE) Savannah River Site (SRS). This report is one of several discrete but interrelated tasks that support development of an updated groundwater model (Bagwell and Flach, 2016).

  20. Simplicial models for trace spaces II: General higher dimensional automata

    DEFF Research Database (Denmark)

    Raussen, Martin

    of directed paths with given end points in a pre-cubical complex as the nerve of a particular category. The paper generalizes the results from Raussen [19, 18] in which we had to assume that the HDA in question arises from a semaphore model. In particular, important for applications, it allows for models...

  1. Generalized algebra-valued models of set theory

    NARCIS (Netherlands)

    Löwe, B.; Tarafder, S.

    2015-01-01

    We generalize the construction of lattice-valued models of set theory due to Takeuti, Titani, Kozawa and Ozawa to a wider class of algebras and show that this yields a model of a paraconsistent logic that validates all axioms of the negation-free fragment of Zermelo-Fraenkel set theory.

  2. Efficient probabilistic model checking on general purpose graphic processors

    NARCIS (Netherlands)

    Bosnacki, D.; Edelkamp, S.; Sulewski, D.; Pasareanu, C.S.

    2009-01-01

    We present algorithms for parallel probabilistic model checking on general purpose graphic processing units (GPGPUs). For this purpose we exploit the fact that some of the basic algorithms for probabilistic model checking rely on matrix vector multiplication. Since this kind of linear algebraic

  3. Stability analysis for a general age-dependent vaccination model

    International Nuclear Information System (INIS)

    El Doma, M.

    1995-05-01

    An SIR epidemic model of a general age-dependent vaccination model is investigated when the fertility, mortality and removal rates depends on age. We give threshold criteria of the existence of equilibriums and perform stability analysis. Furthermore a critical vaccination coverage that is sufficient to eradicate the disease is determined. (author). 12 refs

  4. A General Polygon-based Deformable Model for Object Recognition

    DEFF Research Database (Denmark)

    Jensen, Rune Fisker; Carstensen, Jens Michael

    1999-01-01

    We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic distr...

  5. A General Microscopic Traffic Model Yielding Dissipative Shocks

    DEFF Research Database (Denmark)

    Gaididei, Yuri Borisovich; Caputo, Jean Guy; Christiansen, Peter Leth

    2018-01-01

    We consider a general microscopic traffic model with a delay. An algebraic traffic function reduces the equation to the Aw-Rascle microscopic model while a sigmoid function gives the standard “follow the leader”. For zero delay we prove that the homogeneous solution is globally stable...

  6. Nature of dynamical suppressions in the generalized Veneziano model

    International Nuclear Information System (INIS)

    Odorico, R.

    1976-05-01

    It is shown by explicit numerical calculations that of a class of coupling suppressions existing in the generalized Veneziano model, which have been recently used to interpret the psi data and other related phenomena, only a part can be attributed to the exponential growth with energy of the number of levels in the model. The remaining suppressions have a more direct dual origin

  7. Bayesian Subset Modeling for High-Dimensional Generalized Linear Models

    KAUST Repository

    Liang, Faming; Song, Qifan; Yu, Kai

    2013-01-01

    criterion model. The consistency of the resulting posterior is established under mild conditions. Further, a variable screening procedure is proposed based on the marginal inclusion probability, which shares the same properties of sure screening

  8. Infrared problems in two-dimensional generalized σ-models

    International Nuclear Information System (INIS)

    Curci, G.; Paffuti, G.

    1989-01-01

    We study the correlations of the energy-momentum tensor for classically conformally invariant generalized σ-models in the Wilson operator-product-expansion approach. We find that these correlations are, in general, infrared divergent. The absence of infrared divergences is obtained, as one can expect, for σ-models on a group manifold or for σ-models with a string-like interpretation. Moreover, the infrared divergences spoil the naive scaling arguments used by Zamolodchikov in the demonstration of the C-theorem. (orig.)

  9. Calibration and validation of a general infiltration model

    Science.gov (United States)

    Mishra, Surendra Kumar; Ranjan Kumar, Shashi; Singh, Vijay P.

    1999-08-01

    A general infiltration model proposed by Singh and Yu (1990) was calibrated and validated using a split sampling approach for 191 sets of infiltration data observed in the states of Minnesota and Georgia in the USA. Of the five model parameters, fc (the final infiltration rate), So (the available storage space) and exponent n were found to be more predictable than the other two parameters: m (exponent) and a (proportionality factor). A critical examination of the general model revealed that it is related to the Soil Conservation Service (1956) curve number (SCS-CN) method and its parameter So is equivalent to the potential maximum retention of the SCS-CN method and is, in turn, found to be a function of soil sorptivity and hydraulic conductivity. The general model was found to describe infiltration rate with time varying curve number.

  10. Partially Observed Mixtures of IRT Models: An Extension of the Generalized Partial-Credit Model

    Science.gov (United States)

    Von Davier, Matthias; Yamamoto, Kentaro

    2004-01-01

    The generalized partial-credit model (GPCM) is used frequently in educational testing and in large-scale assessments for analyzing polytomous data. Special cases of the generalized partial-credit model are the partial-credit model--or Rasch model for ordinal data--and the two parameter logistic (2PL) model. This article extends the GPCM to the…

  11. Multiple High-Fidelity Modeling Tools for Metal Additive Manufacturing Process Development, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Despite the rapid commercialization of additive manufacturing technology such as selective laser melting, SLM, there are gaps in process modeling and material...

  12. Multiple High-Fidelity Modeling Tools for Metal Additive Manufacturing Process Development, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Despite the rapid commercialization of additive manufacturing technology such as selective laser melting, SLM, there are gaps in process modeling and material...

  13. 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

  14. Generalized Tavis-Cummings models and quantum networks

    Science.gov (United States)

    Gorokhov, A. V.

    2018-04-01

    The properties of quantum networks based on generalized Tavis-Cummings models are theoretically investigated. We have calculated the information transfer success rate from one node to another in a simple model of a quantum network realized with two-level atoms placed in the cavities and interacting with an external laser field and cavity photons. The method of dynamical group of the Hamiltonian and technique of corresponding coherent states were used for investigation of the temporal dynamics of the two nodes model.

  15. The cointegrated vector autoregressive model with general deterministic terms

    DEFF Research Database (Denmark)

    Johansen, Søren; Nielsen, Morten Ørregaard

    2017-01-01

    In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model X(t)=Z(t) Y(t), where Z(t) belongs to a large class...... of deterministic regressors and Y(t) is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended...... model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are X 2 -distributed....

  16. The cointegrated vector autoregressive model with general deterministic terms

    DEFF Research Database (Denmark)

    Johansen, Søren; Nielsen, Morten Ørregaard

    In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model X(t)= Z(t) + Y(t), where Z(t) belongs to a large class...... of deterministic regressors and Y(t) is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended...... model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are khi squared distributed....

  17. Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models

    Directory of Open Access Journals (Sweden)

    Shelton Peiris

    2017-12-01

    Full Text Available This paper considers a flexible class of time series models generated by Gegenbauer polynomials incorporating the long memory in stochastic volatility (SV components in order to develop the General Long Memory SV (GLMSV model. We examine the corresponding statistical properties of this model, discuss the spectral likelihood estimation and investigate the finite sample properties via Monte Carlo experiments. We provide empirical evidence by applying the GLMSV model to three exchange rate return series and conjecture that the results of out-of-sample forecasts adequately confirm the use of GLMSV model in certain financial applications.

  18. Generalized heat-transport equations: parabolic and hyperbolic models

    Science.gov (United States)

    Rogolino, Patrizia; Kovács, Robert; Ván, Peter; Cimmelli, Vito Antonio

    2018-03-01

    We derive two different generalized heat-transport equations: the most general one, of the first order in time and second order in space, encompasses some well-known heat equations and describes the hyperbolic regime in the absence of nonlocal effects. Another, less general, of the second order in time and fourth order in space, is able to describe hyperbolic heat conduction also in the presence of nonlocal effects. We investigate the thermodynamic compatibility of both models by applying some generalizations of the classical Liu and Coleman-Noll procedures. In both cases, constitutive equations for the entropy and for the entropy flux are obtained. For the second model, we consider a heat-transport equation which includes nonlocal terms and study the resulting set of balance laws, proving that the corresponding thermal perturbations propagate with finite speed.

  19. Generalized semi-Markovian dividend discount model: risk and return

    OpenAIRE

    D'Amico, Guglielmo

    2016-01-01

    The article presents a general discrete time dividend valuation model when the dividend growth rate is a general continuous variable. The main assumption is that the dividend growth rate follows a discrete time semi-Markov chain with measurable space. The paper furnishes sufficient conditions that assure finiteness of fundamental prices and risks and new equations that describe the first and second order price-dividend ratios. Approximation methods to solve equations are provided and some new...

  20. Additive Manufacturing Modeling and Simulation A Literature Review for Electron Beam Free Form Fabrication

    Science.gov (United States)

    Seufzer, William J.

    2014-01-01

    Additive manufacturing is coming into industrial use and has several desirable attributes. Control of the deposition remains a complex challenge, and so this literature review was initiated to capture current modeling efforts in the field of additive manufacturing. This paper summarizes about 10 years of modeling and simulation related to both welding and additive manufacturing. The goals were to learn who is doing what in modeling and simulation, to summarize various approaches taken to create models, and to identify research gaps. Later sections in the report summarize implications for closed-loop-control of the process, implications for local research efforts, and implications for local modeling efforts.

  1. Practical likelihood analysis for spatial generalized linear mixed models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Ribeiro, Paulo Justiniano

    2016-01-01

    We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...

  2. Modeling the brain morphology distribution in the general aging population

    Science.gov (United States)

    Huizinga, W.; Poot, D. H. J.; Roshchupkin, G.; Bron, E. E.; Ikram, M. A.; Vernooij, M. W.; Rueckert, D.; Niessen, W. J.; Klein, S.

    2016-03-01

    Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.

  3. Explicit prediction of ice clouds in general circulation models

    Science.gov (United States)

    Kohler, Martin

    1999-11-01

    Although clouds play extremely important roles in the radiation budget and hydrological cycle of the Earth, there are large quantitative uncertainties in our understanding of their generation, maintenance and decay mechanisms, representing major obstacles in the development of reliable prognostic cloud water schemes for General Circulation Models (GCMs). Recognizing their relative neglect in the past, both observationally and theoretically, this work places special focus on ice clouds. A recent version of the UCLA - University of Utah Cloud Resolving Model (CRM) that includes interactive radiation is used to perform idealized experiments to study ice cloud maintenance and decay mechanisms under various conditions in term of: (1) background static stability, (2) background relative humidity, (3) rate of cloud ice addition over a fixed initial time-period and (4) radiation: daytime, nighttime and no-radiation. Radiation is found to have major effects on the life-time of layer-clouds. Optically thick ice clouds decay significantly slower than expected from pure microphysical crystal fall-out (taucld = 0.9--1.4 h as opposed to no-motion taumicro = 0.5--0.7 h). This is explained by the upward turbulent fluxes of water induced by IR destabilization, which partially balance the downward transport of water by snowfall. Solar radiation further slows the ice-water decay by destruction of the inversion above cloud-top and the resulting upward transport of water. Optically thin ice clouds, on the other hand, may exhibit even longer life-times (>1 day) in the presence of radiational cooling. The resulting saturation mixing ratio reduction provides for a constant cloud ice source. These CRM results are used to develop a prognostic cloud water scheme for the UCLA-GCM. The framework is based on the bulk water phase model of Ose (1993). The model predicts cloud liquid water and cloud ice separately, and which is extended to split the ice phase into suspended cloud ice (predicted

  4. Hierarchical random additive process and logarithmic scaling of generalized high order, two-point correlations in turbulent boundary layer flow

    Science.gov (United States)

    Yang, X. I. A.; Marusic, I.; Meneveau, C.

    2016-06-01

    Townsend [Townsend, The Structure of Turbulent Shear Flow (Cambridge University Press, Cambridge, UK, 1976)] hypothesized that the logarithmic region in high-Reynolds-number wall-bounded flows consists of space-filling, self-similar attached eddies. Invoking this hypothesis, we express streamwise velocity fluctuations in the inertial layer in high-Reynolds-number wall-bounded flows as a hierarchical random additive process (HRAP): uz+=∑i=1Nzai . Here u is the streamwise velocity fluctuation, + indicates normalization in wall units, z is the wall normal distance, and ai's are independently, identically distributed random additives, each of which is associated with an attached eddy in the wall-attached hierarchy. The number of random additives is Nz˜ln(δ /z ) where δ is the boundary layer thickness and ln is natural log. Due to its simplified structure, such a process leads to predictions of the scaling behaviors for various turbulence statistics in the logarithmic layer. Besides reproducing known logarithmic scaling of moments, structure functions, and correlation function [" close="]3/2 uz(x ) uz(x +r ) >, new logarithmic laws in two-point statistics such as uz4(x ) > 1 /2, 1/3, etc. can be derived using the HRAP formalism. Supporting empirical evidence for the logarithmic scaling in such statistics is found from the Melbourne High Reynolds Number Boundary Layer Wind Tunnel measurements. We also show that, at high Reynolds numbers, the above mentioned new logarithmic laws can be derived by assuming the arrival of an attached eddy at a generic point in the flow field to be a Poisson process [Woodcock and Marusic, Phys. Fluids 27, 015104 (2015), 10.1063/1.4905301]. Taken together, the results provide new evidence supporting the essential ingredients of the attached eddy hypothesis to describe streamwise velocity fluctuations of large, momentum transporting eddies in wall-bounded turbulence, while observed deviations suggest the need for further extensions of the

  5. A model for additive transport in metal halide lamps containing mercury and dysprosium tri-iodide

    NARCIS (Netherlands)

    Beks, M.L.; Haverlag, M.; Mullen, van der J.J.A.M.

    2008-01-01

    The distribution of additives in a metal halide lamp is examined through numerical modelling. A model for a lamp containing sodium iodide additives has been modified to study a discharge containing dysprosium tri-iodide salts. To study the complex chemistry the method of Gibbs minimization is used

  6. Generalized memory associativity in a network model for the neuroses

    Science.gov (United States)

    Wedemann, Roseli S.; Donangelo, Raul; de Carvalho, Luís A. V.

    2009-03-01

    We review concepts introduced in earlier work, where a neural network mechanism describes some mental processes in neurotic pathology and psychoanalytic working-through, as associative memory functioning, according to the findings of Freud. We developed a complex network model, where modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's idea that consciousness is related to symbolic and linguistic memory activity in the brain. We have introduced a generalization of the Boltzmann machine to model memory associativity. Model behavior is illustrated with simulations and some of its properties are analyzed with methods from statistical mechanics.

  7. Automation of electroweak NLO corrections in general models

    Energy Technology Data Exchange (ETDEWEB)

    Lang, Jean-Nicolas [Universitaet Wuerzburg (Germany)

    2016-07-01

    I discuss the automation of generation of scattering amplitudes in general quantum field theories at next-to-leading order in perturbation theory. The work is based on Recola, a highly efficient one-loop amplitude generator for the Standard Model, which I have extended so that it can deal with general quantum field theories. Internally, Recola computes off-shell currents and for new models new rules for off-shell currents emerge which are derived from the Feynman rules. My work relies on the UFO format which can be obtained by a suited model builder, e.g. FeynRules. I have developed tools to derive the necessary counterterm structures and to perform the renormalization within Recola in an automated way. I describe the procedure using the example of the two-Higgs-doublet model.

  8. Seasonal predictability of Kiremt rainfall in coupled general circulation models

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

    2017-11-01

    The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

  9. Interacting holographic dark energy models: a general approach

    Science.gov (United States)

    Som, S.; Sil, A.

    2014-08-01

    Dark energy models inspired by the cosmological holographic principle are studied in homogeneous isotropic spacetime with a general choice for the dark energy density . Special choices of the parameters enable us to obtain three different holographic models, including the holographic Ricci dark energy (RDE) model. Effect of interaction between dark matter and dark energy on the dynamics of those models are investigated for different popular forms of interaction. It is found that crossing of phantom divide can be avoided in RDE models for β>0.5 irrespective of the presence of interaction. A choice of α=1 and β=2/3 leads to a varying Λ-like model introducing an IR cutoff length Λ -1/2. It is concluded that among the popular choices an interaction of the form Q∝ Hρ m suits the best in avoiding the coincidence problem in this model.

  10. a Model Study of Small-Scale World Map Generalization

    Science.gov (United States)

    Cheng, Y.; Yin, Y.; Li, C. M.; Wu, W.; Guo, P. P.; Ma, X. L.; Hu, F. M.

    2018-04-01

    With the globalization and rapid development every filed is taking an increasing interest in physical geography and human economics. There is a surging demand for small scale world map in large formats all over the world. Further study of automated mapping technology, especially the realization of small scale production on a large scale global map, is the key of the cartographic field need to solve. In light of this, this paper adopts the improved model (with the map and data separated) in the field of the mapmaking generalization, which can separate geographic data from mapping data from maps, mainly including cross-platform symbols and automatic map-making knowledge engine. With respect to the cross-platform symbol library, the symbol and the physical symbol in the geographic information are configured at all scale levels. With respect to automatic map-making knowledge engine consists 97 types, 1086 subtypes, 21845 basic algorithm and over 2500 relevant functional modules.In order to evaluate the accuracy and visual effect of our model towards topographic maps and thematic maps, we take the world map generalization in small scale as an example. After mapping generalization process, combining and simplifying the scattered islands make the map more explicit at 1 : 2.1 billion scale, and the map features more complete and accurate. Not only it enhance the map generalization of various scales significantly, but achieve the integration among map-makings of various scales, suggesting that this model provide a reference in cartographic generalization for various scales.

  11. On complicated continuum models in general relativity theory

    International Nuclear Information System (INIS)

    Tsypkin, A.G.

    1987-01-01

    A set of Euler's equations is obtained in the framework of the general relativity theory from the variational equation in the supposition that lagrangian of the material depends on additional (in comparison with classical theories) thermodynamic parameters and taking into account possible irreversible processes. Momentum equations for continuous medium of a thermodynamic closed set are shown to be the consequence of field equations. The problem about the type of energy-momentum material tensor in the presence of derivatives from additional thermodynamic parameters in the number of lagrangian arguments is considered

  12. Study of the properties of general relativistic Kink model (GRK)

    International Nuclear Information System (INIS)

    Oliveira, L.C.S. de.

    1980-01-01

    The stability of the general relativistic Kink model (GRK) is studied. It is shown that the model is stable at least against radial perturbations. Furthermore, the Dirac field in the background of the geometry generated by the GRK is studied. It is verified that the GRK localizes the Dirac field, around the region of largest curvature. The physical interpretation of this system (the Dirac field in the GRK background) is discussed. (Author) [pt

  13. Optimisation of a parallel ocean general circulation model

    OpenAIRE

    M. I. Beare; D. P. Stevens

    1997-01-01

    International audience; This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by...

  14. A general graphical user interface for automatic reliability modeling

    Science.gov (United States)

    Liceaga, Carlos A.; Siewiorek, Daniel P.

    1991-01-01

    Reported here is a general Graphical User Interface (GUI) for automatic reliability modeling of Processor Memory Switch (PMS) structures using a Markov model. This GUI is based on a hierarchy of windows. One window has graphical editing capabilities for specifying the system's communication structure, hierarchy, reconfiguration capabilities, and requirements. Other windows have field texts, popup menus, and buttons for specifying parameters and selecting actions. An example application of the GUI is given.

  15. Optimal Designs for the Generalized Partial Credit Model

    OpenAIRE

    Bürkner, Paul-Christian; Schwabe, Rainer; Holling, Heinz

    2018-01-01

    Analyzing ordinal data becomes increasingly important in psychology, especially in the context of item response theory. The generalized partial credit model (GPCM) is probably the most widely used ordinal model and finds application in many large scale educational assessment studies such as PISA. In the present paper, optimal test designs are investigated for estimating persons' abilities with the GPCM for calibrated tests when item parameters are known from previous studies. We will derive t...

  16. Nonlinear feedback in a six-dimensional Lorenz model: impact of an additional heating term

    Science.gov (United States)

    Shen, B.-W.

    2015-12-01

    In this study, a six-dimensional Lorenz model (6DLM) is derived, based on a recent study using a five-dimensional (5-D) Lorenz model (LM), in order to examine the impact of an additional mode and its accompanying heating term on solution stability. The new mode added to improve the representation of the streamfunction is referred to as a secondary streamfunction mode, while the two additional modes, which appear in both the 6DLM and 5DLM but not in the original LM, are referred to as secondary temperature modes. Two energy conservation relationships of the 6DLM are first derived in the dissipationless limit. The impact of three additional modes on solution stability is examined by comparing numerical solutions and ensemble Lyapunov exponents of the 6DLM and 5DLM as well as the original LM. For the onset of chaos, the critical value of the normalized Rayleigh number (rc) is determined to be 41.1. The critical value is larger than that in the 3DLM (rc ~ 24.74), but slightly smaller than the one in the 5DLM (rc ~ 42.9). A stability analysis and numerical experiments obtained using generalized LMs, with or without simplifications, suggest the following: (1) negative nonlinear feedback in association with the secondary temperature modes, as first identified using the 5DLM, plays a dominant role in providing feedback for improving the solution's stability of the 6DLM, (2) the additional heating term in association with the secondary streamfunction mode may destabilize the solution, and (3) overall feedback due to the secondary streamfunction mode is much smaller than the feedback due to the secondary temperature modes; therefore, the critical Rayleigh number of the 6DLM is comparable to that of the 5DLM. The 5DLM and 6DLM collectively suggest different roles for small-scale processes (i.e., stabilization vs. destabilization), consistent with the following statement by Lorenz (1972): "If the flap of a butterfly's wings can be instrumental in generating a tornado, it can

  17. Anisotropic cosmological models and generalized scalar tensor theory

    Indian Academy of Sciences (India)

    Abstract. In this paper generalized scalar tensor theory has been considered in the background of anisotropic cosmological models, namely, axially symmetric Bianchi-I, Bianchi-III and Kortowski–. Sachs space-time. For bulk viscous fluid, both exponential and power-law solutions have been stud- ied and some assumptions ...

  18. Anisotropic cosmological models and generalized scalar tensor theory

    Indian Academy of Sciences (India)

    In this paper generalized scalar tensor theory has been considered in the background of anisotropic cosmological models, namely, axially symmetric Bianchi-I, Bianchi-III and Kortowski–Sachs space-time. For bulk viscous fluid, both exponential and power-law solutions have been studied and some assumptions among the ...

  19. A general circulation model (GCM) parameterization of Pinatubo aerosols

    Energy Technology Data Exchange (ETDEWEB)

    Lacis, A.A.; Carlson, B.E.; Mishchenko, M.I. [NASA Goddard Institute for Space Studies, New York, NY (United States)

    1996-04-01

    The June 1991 volcanic eruption of Mt. Pinatubo is the largest and best documented global climate forcing experiment in recorded history. The time development and geographical dispersion of the aerosol has been closely monitored and sampled. Based on preliminary estimates of the Pinatubo aerosol loading, general circulation model predictions of the impact on global climate have been made.

  20. Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models

    Science.gov (United States)

    Wagler, Amy E.

    2014-01-01

    Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…

  1. Penalized Estimation in Large-Scale Generalized Linear Array Models

    DEFF Research Database (Denmark)

    Lund, Adam; Vincent, Martin; Hansen, Niels Richard

    2017-01-01

    Large-scale generalized linear array models (GLAMs) can be challenging to fit. Computation and storage of its tensor product design matrix can be impossible due to time and memory constraints, and previously considered design matrix free algorithms do not scale well with the dimension...

  2. An applied general equilibrium model for Dutch agribusiness policy analysis

    NARCIS (Netherlands)

    Peerlings, J.

    1993-01-01

    The purpose of this thesis was to develop a basic static applied general equilibrium (AGE) model to analyse the effects of agricultural policy changes on Dutch agribusiness. In particular the effects on inter-industry transactions, factor demand, income, and trade are of

  3. Transmittivity and wavefunctions in one-dimensional generalized Aubry models

    International Nuclear Information System (INIS)

    Basu, C.; Mookerjee, A.; Sen, A.K.; Thakur, P.K.

    1990-07-01

    We use the vector recursion method of Haydock to obtain the transmittance of a class of generalized Aubry models in one-dimension. We also study the phase change of the wavefunctions as they travel through the chain and also the behaviour of the conductance with changes in size. (author). 10 refs, 9 figs

  4. On the general procedure for modelling complex ecological systems

    International Nuclear Information System (INIS)

    He Shanyu.

    1987-12-01

    In this paper, the principle of a general procedure for modelling complex ecological systems, i.e. the Adaptive Superposition Procedure (ASP) is shortly stated. The result of application of ASP in a national project for ecological regionalization is also described. (author). 3 refs

  5. A generalized development model for testing GPS user equipment

    Science.gov (United States)

    Hemesath, N.

    1978-01-01

    The generalized development model (GDM) program, which was intended to establish how well GPS user equipment can perform under a combination of jamming and dynamics, is described. The systems design and the characteristics of the GDM are discussed. The performance aspects of the GDM are listed and the application of the GDM to civil aviation is examined.

  6. Selected translated abstracts of Russian-language climate-change publications. 4: General circulation models

    Energy Technology Data Exchange (ETDEWEB)

    Burtis, M.D. [comp.] [Oak Ridge National Lab., TN (United States). Carbon Dioxide Information Analysis Center; Razuvaev, V.N.; Sivachok, S.G. [All-Russian Research Inst. of Hydrometeorological Information--World Data Center, Obninsk (Russian Federation)

    1996-10-01

    This report presents English-translated abstracts of important Russian-language literature concerning general circulation models as they relate to climate change. Into addition to the bibliographic citations and abstracts translated into English, this report presents the original citations and abstracts in Russian. Author and title indexes are included to assist the reader in locating abstracts of particular interest.

  7. Strategies for Controlling Item Exposure in Computerized Adaptive Testing with the Generalized Partial Credit Model

    Science.gov (United States)

    Davis, Laurie Laughlin

    2004-01-01

    Choosing a strategy for controlling item exposure has become an integral part of test development for computerized adaptive testing (CAT). This study investigated the performance of six procedures for controlling item exposure in a series of simulated CATs under the generalized partial credit model. In addition to a no-exposure control baseline…

  8. A General Model for Testing Mediation and Moderation Effects

    Science.gov (United States)

    MacKinnon, David P.

    2010-01-01

    This paper describes methods for testing mediation and moderation effects in a dataset, both together and separately. Investigations of this kind are especially valuable in prevention research to obtain information on the process by which a program achieves its effects and whether the program is effective for subgroups of individuals. A general model that simultaneously estimates mediation and moderation effects is presented, and the utility of combining the effects into a single model is described. Possible effects of interest in the model are explained, as are statistical methods to assess these effects. The methods are further illustrated in a hypothetical prevention program example. PMID:19003535

  9. Generalized Jaynes-Cummings model as a quantum search algorithm

    International Nuclear Information System (INIS)

    Romanelli, A.

    2009-01-01

    We propose a continuous time quantum search algorithm using a generalization of the Jaynes-Cummings model. In this model the states of the atom are the elements among which the algorithm realizes the search, exciting resonances between the initial and the searched states. This algorithm behaves like Grover's algorithm; the optimal search time is proportional to the square root of the size of the search set and the probability to find the searched state oscillates periodically in time. In this frame, it is possible to reinterpret the usual Jaynes-Cummings model as a trivial case of the quantum search algorithm.

  10. Generalized Roe's numerical scheme for a two-fluid model

    International Nuclear Information System (INIS)

    Toumi, I.; Raymond, P.

    1993-01-01

    This paper is devoted to a mathematical and numerical study of a six equation two-fluid model. We will prove that the model is strictly hyperbolic due to the inclusion of the virtual mass force term in the phasic momentum equations. The two-fluid model is naturally written under a nonconservative form. To solve the nonlinear Riemann problem for this nonconservative hyperbolic system, a generalized Roe's approximate Riemann solver, is used, based on a linearization of the nonconservative terms. A Godunov type numerical scheme is built, using this approximate Riemann solver. 10 refs., 5 figs,

  11. Zeros of the partition function for some generalized Ising models

    International Nuclear Information System (INIS)

    Dunlop, F.

    1981-01-01

    The author considers generalized Ising Models with two and four body interactions in a complex external field h such that Re h>=mod(Im h) + C, where C is an explicit function of the interaction parameters. The partition function Z(h) is then shown to satisfy mod(Z(h))>=Z(c), so that the pressure is analytic in h inside the given region. The method is applied to specific examples: the gauge invariant Ising Model, and the Widom Rowlinson model on the lattice. (Auth.)

  12. A Graphical User Interface to Generalized Linear Models in MATLAB

    Directory of Open Access Journals (Sweden)

    Peter Dunn

    1999-07-01

    Full Text Available Generalized linear models unite a wide variety of statistical models in a common theoretical framework. This paper discusses GLMLAB-software that enables such models to be fitted in the popular mathematical package MATLAB. It provides a graphical user interface to the powerful MATLAB computational engine to produce a program that is easy to use but with many features, including offsets, prior weights and user-defined distributions and link functions. MATLAB's graphical capacities are also utilized in providing a number of simple residual diagnostic plots.

  13. A General Accelerated Degradation Model Based on the Wiener Process.

    Science.gov (United States)

    Liu, Le; Li, Xiaoyang; Sun, Fuqiang; Wang, Ning

    2016-12-06

    Accelerated degradation testing (ADT) is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses.

  14. Generalized Landau-Lifshitz models on the interval

    International Nuclear Information System (INIS)

    Doikou, Anastasia; Karaiskos, Nikos

    2011-01-01

    We study the classical generalized gl n Landau-Lifshitz (L-L) model with special boundary conditions that preserve integrability. We explicitly derive the first non-trivial local integral of motion, which corresponds to the boundary Hamiltonian for the sl 2 L-L model. Novel expressions of the modified Lax pairs associated to the integrals of motion are also extracted. The relevant equations of motion with the corresponding boundary conditions are determined. Dynamical integrable boundary conditions are also examined within this spirit. Then the generalized isotropic and anisotropic gl n Landau-Lifshitz models are considered, and novel expressions of the boundary Hamiltonians and the relevant equations of motion and boundary conditions are derived.

  15. Materials Testing and Cost Modeling for Composite Parts Through Additive Manufacturing

    Science.gov (United States)

    2016-04-30

    FDM include plastic jet printing (PJP), fused filament modeling ( FFM ), and fused filament fabrication (FFF). FFF was coined by the RepRap project to...additive manufacturing processes? • Fused deposition modeling (FDM) trademarked by Stratasys • Fused filament modeling ( FFM ) and fused filament

  16. Considering the Epistemic Uncertainties of the Variogram Model in Locating Additional Exploratory Drillholes

    Directory of Open Access Journals (Sweden)

    Saeed Soltani

    2015-06-01

    Full Text Available To enhance the certainty of the grade block model, it is necessary to increase the number of exploratory drillholes and collect more data from the deposit. The inputs of the process of locating these additional drillholes include the variogram model parameters, locations of the samples taken from the initial drillholes, and the geological block model. The uncertainties of these inputs will lead to uncertainties in the optimal locations of additional drillholes. Meanwhile, the locations of the initial data are crisp, but the variogram model parameters and the geological model have uncertainties due to the limitation of the number of initial data. In this paper, effort has been made to consider the effects of variogram uncertainties on the optimal location of additional drillholes using the fuzzy kriging and solve the locating problem with the genetic algorithm (GA optimization method.A bauxite deposit case study has shown the efficiency of the proposed model.

  17. A generalized conditional heteroscedastic model for temperature downscaling

    Science.gov (United States)

    Modarres, R.; Ouarda, T. B. M. J.

    2014-11-01

    This study describes a method for deriving the time varying second order moment, or heteroscedasticity, of local daily temperature and its association to large Coupled Canadian General Circulation Models predictors. This is carried out by applying a multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) approach to construct the conditional variance-covariance structure between General Circulation Models (GCMs) predictors and maximum and minimum temperature time series during 1980-2000. Two MGARCH specifications namely diagonal VECH and dynamic conditional correlation (DCC) are applied and 25 GCM predictors were selected for a bivariate temperature heteroscedastic modeling. It is observed that the conditional covariance between predictors and temperature is not very strong and mostly depends on the interaction between the random process governing temporal variation of predictors and predictants. The DCC model reveals a time varying conditional correlation between GCM predictors and temperature time series. No remarkable increasing or decreasing change is observed for correlation coefficients between GCM predictors and observed temperature during 1980-2000 while weak winter-summer seasonality is clear for both conditional covariance and correlation. Furthermore, the stationarity and nonlinearity Kwiatkowski-Phillips-Schmidt-Shin (KPSS) and Brock-Dechert-Scheinkman (BDS) tests showed that GCM predictors, temperature and their conditional correlation time series are nonlinear but stationary during 1980-2000 according to BDS and KPSS test results. However, the degree of nonlinearity of temperature time series is higher than most of the GCM predictors.

  18. Generalized Modeling of the Human Lower Limb Assembly

    Science.gov (United States)

    Cofaru, Ioana; Huzu, Iulia

    2014-11-01

    The main reason for creating a generalized assembly of the main bones of the lower human member is to create the premises of realizing a biomechanic assisted study which could be used for the study of the high range of varieties of pathologies that exist at this level. Starting from 3D CAD models of the main bones of the lower human member, which were realized in previous researches, in this study a generalized assembly system was developed, system in which are highlighted both the situation of an healthy subject and the situation of the situation of a subject affected by axial deviations. In order to achieve these purpose reference systems were created, systems that are in accordance with the mechanical axes and the anatomic axes of the lower member, which were later generally assembled in a manner that provides an easy customization option

  19. Regression analysis of mixed recurrent-event and panel-count data with additive rate models.

    Science.gov (United States)

    Zhu, Liang; Zhao, Hui; Sun, Jianguo; Leisenring, Wendy; Robison, Leslie L

    2015-03-01

    Event-history studies of recurrent events are often conducted in fields such as demography, epidemiology, medicine, and social sciences (Cook and Lawless, 2007, The Statistical Analysis of Recurrent Events. New York: Springer-Verlag; Zhao et al., 2011, Test 20, 1-42). For such analysis, two types of data have been extensively investigated: recurrent-event data and panel-count data. However, in practice, one may face a third type of data, mixed recurrent-event and panel-count data or mixed event-history data. Such data occur if some study subjects are monitored or observed continuously and thus provide recurrent-event data, while the others are observed only at discrete times and hence give only panel-count data. A more general situation is that each subject is observed continuously over certain time periods but only at discrete times over other time periods. There exists little literature on the analysis of such mixed data except that published by Zhu et al. (2013, Statistics in Medicine 32, 1954-1963). In this article, we consider the regression analysis of mixed data using the additive rate model and develop some estimating equation-based approaches to estimate the regression parameters of interest. Both finite sample and asymptotic properties of the resulting estimators are established, and the numerical studies suggest that the proposed methodology works well for practical situations. The approach is applied to a Childhood Cancer Survivor Study that motivated this study. © 2014, The International Biometric Society.

  20. Attractive Hubbard model with disorder and the generalized Anderson theorem

    International Nuclear Information System (INIS)

    Kuchinskii, E. Z.; Kuleeva, N. A.; Sadovskii, M. V.

    2015-01-01

    Using the generalized DMFT+Σ approach, we study the influence of disorder on single-particle properties of the normal phase and the superconducting transition temperature in the attractive Hubbard model. A wide range of attractive potentials U is studied, from the weak coupling region, where both the instability of the normal phase and superconductivity are well described by the BCS model, to the strong-coupling region, where the superconducting transition is due to Bose-Einstein condensation (BEC) of compact Cooper pairs, formed at temperatures much higher than the superconducting transition temperature. We study two typical models of the conduction band with semi-elliptic and flat densities of states, respectively appropriate for three-dimensional and two-dimensional systems. For the semi-elliptic density of states, the disorder influence on all single-particle properties (e.g., density of states) is universal for an arbitrary strength of electronic correlations and disorder and is due to only the general disorder widening of the conduction band. In the case of a flat density of states, universality is absent in the general case, but still the disorder influence is mainly due to band widening, and the universal behavior is restored for large enough disorder. Using the combination of DMFT+Σ and Nozieres-Schmitt-Rink approximations, we study the disorder influence on the superconducting transition temperature T c for a range of characteristic values of U and disorder, including the BCS-BEC crossover region and the limit of strong-coupling. Disorder can either suppress T c (in the weak-coupling region) or significantly increase T c (in the strong-coupling region). However, in all cases, the generalized Anderson theorem is valid and all changes of the superconducting critical temperature are essentially due to only the general disorder widening of the conduction band

  1. Effect of Hydrogen Addition on Methane HCCI Engine Ignition Timing and Emissions Using a Multi-zone Model

    Science.gov (United States)

    Wang, Zi-han; Wang, Chun-mei; Tang, Hua-xin; Zuo, Cheng-ji; Xu, Hong-ming

    2009-06-01

    Ignition timing control is of great importance in homogeneous charge compression ignition engines. The effect of hydrogen addition on methane combustion was investigated using a CHEMKIN multi-zone model. Results show that hydrogen addition advances ignition timing and enhances peak pressure and temperature. A brief analysis of chemical kinetics of methane blending hydrogen is also performed in order to investigate the scope of its application, and the analysis suggests that OH radical plays an important role in the oxidation. Hydrogen addition increases NOx while decreasing HC and CO emissions. Exhaust gas recirculation (EGR) also advances ignition timing; however, its effects on emissions are generally the opposite. By adjusting the hydrogen addition and EGR rate, the ignition timing can be regulated with a low emission level. Investigation into zones suggests that NOx is mostly formed in core zones while HC and CO mostly originate in the crevice and the quench layer.

  2. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina

    2012-08-03

    We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

  3. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.

    2012-01-01

    We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

  4. Comparison of nonstationary generalized logistic models based on Monte Carlo simulation

    Directory of Open Access Journals (Sweden)

    S. Kim

    2015-06-01

    Full Text Available Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstationarity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.

  5. Treatment of cloud radiative effects in general circulation models

    Energy Technology Data Exchange (ETDEWEB)

    Wang, W.C.; Dudek, M.P.; Liang, X.Z.; Ding, M. [State Univ. of New York, Albany, NY (United States)] [and others

    1996-04-01

    We participate in the Atmospheric Radiation Measurement (ARM) program with two objectives: (1) to improve the general circulation model (GCM) cloud/radiation treatment with a focus on cloud verticle overlapping and layer cloud optical properties, and (2) to study the effects of cloud/radiation-climate interaction on GCM climate simulations. This report summarizes the project progress since the Fourth ARM Science Team meeting February 28-March 4, 1994, in Charleston, South Carolina.

  6. A General Model for Repeated Audit Controls Using Monotone Subsampling

    OpenAIRE

    Raats, V.M.; van der Genugten, B.B.; Moors, J.J.A.

    2002-01-01

    In categorical repeated audit controls, fallible auditors classify sample elements in order to estimate the population fraction of elements in certain categories.To take possible misclassifications into account, subsequent checks are performed with a decreasing number of observations.In this paper a model is presented for a general repeated audit control system, where k subsequent auditors classify elements into r categories.Two different sub-sampling procedures will be discussed, named 'stra...

  7. Electromagnetic axial anomaly in a generalized linear sigma model

    Science.gov (United States)

    Fariborz, Amir H.; Jora, Renata

    2017-06-01

    We construct the electromagnetic anomaly effective term for a generalized linear sigma model with two chiral nonets, one with a quark-antiquark structure, the other one with a four-quark content. We compute in the leading order of this framework the decays into two photons of six pseudoscalars: π0(137 ), π0(1300 ), η (547 ), η (958 ), η (1295 ) and η (1760 ). Our results agree well with the available experimental data.

  8. Generalized isothermal models with strange equation of state

    Indian Academy of Sciences (India)

    intention to study the Einstein–Maxwell system with a linear equation of state with ... It is our intention to model the interior of a dense realistic star with a general ... The definition m(r) = 1. 2. ∫ r. 0 ω2ρ(ω)dω. (14) represents the mass contained within a radius r which is a useful physical quantity. The mass function (14) has ...

  9. Generalized Calogero-Sutherland systems from many-matrix models

    International Nuclear Information System (INIS)

    Polychronakos, Alexios P.

    1999-01-01

    We construct generalizations of the Calogero-Sutherland-Moser system by appropriately reducing a model involving many unitary matrices. The resulting systems consist of particles on the circle with internal degrees of freedom, coupled through modifications of the inverse-square potential. The coupling involves SU(M) non-invariant (anti) ferromagnetic interactions of the internal degrees of freedom. The systems are shown to be integrable and the spectrum and wavefunctions of the quantum version are derived

  10. Generalized Bogoliubov Polariton Model: An Application to Stock Exchange Market

    International Nuclear Information System (INIS)

    Anh, Chu Thuy; Anh, Truong Thi Ngoc; Lan, Nguyen Tri; Viet, Nguyen Ai

    2016-01-01

    A generalized Bogoliubov method for investigation non-simple and complex systems was developed. We take two branch polariton Hamiltonian model in second quantization representation and replace the energies of quasi-particles by two distribution functions of research objects. Application to stock exchange market was taken as an example, where the changing the form of return distribution functions from Boltzmann-like to Gaussian-like was studied. (paper)

  11. Structural dynamic analysis with generalized damping models analysis

    CERN Document Server

    Adhikari , Sondipon

    2013-01-01

    Since Lord Rayleigh introduced the idea of viscous damping in his classic work ""The Theory of Sound"" in 1877, it has become standard practice to use this approach in dynamics, covering a wide range of applications from aerospace to civil engineering. However, in the majority of practical cases this approach is adopted more for mathematical convenience than for modeling the physics of vibration damping. Over the past decade, extensive research has been undertaken on more general ""non-viscous"" damping models and vibration of non-viscously damped systems. This book, along with a related book

  12. A generalization of the bond fluctuation model to viscoelastic environments

    International Nuclear Information System (INIS)

    Fritsch, Christian C

    2014-01-01

    A lattice-based simulation method for polymer diffusion in a viscoelastic medium is presented. This method combines the eight-site bond fluctuation model with an algorithm for the simulation of fractional Brownian motion on the lattice. The method applies to unentangled self-avoiding chains and is probed for anomalous diffusion exponents α between 0.7 and 1.0. The simulation results are in very good agreement with the predictions of the generalized Rouse model of a self-avoiding chain polymer in a viscoelastic medium. (paper)

  13. Optimisation of a parallel ocean general circulation model

    Science.gov (United States)

    Beare, M. I.; Stevens, D. P.

    1997-10-01

    This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

  14. Energy spectra of odd nuclei in the generalized model

    Directory of Open Access Journals (Sweden)

    I. O. Korzh

    2015-04-01

    Full Text Available Based on the generalized nuclear model, energy spectra of the odd nuclei of such elements as 25Mg, 41K, and 65Cu are determined, and the structure of wave functions of these nuclei in the excited and normal states is studied. High quality in determining the energy spectra is possible due to the accurate calculations of all elements of the energy matrix. It is demonstrated that the structure of the wave functions so determined provides the possibility to more accurately select the nuclear model and the method for calculating the nucleon cross-sections of the inelastic scattering of nucleons by odd nuclei.

  15. Generalized model for Memristor-based Wien family oscillators

    KAUST Repository

    Talukdar, Abdul Hafiz Ibne

    2012-07-23

    In this paper, we report the unconventional characteristics of Memristor in Wien oscillators. Generalized mathematical models are developed to analyze four members of the Wien family using Memristors. Sustained oscillation is reported for all types though oscillating resistance and time dependent poles are present. We have also proposed an analytical model to estimate the desired amplitude of oscillation before the oscillation starts. These Memristor-based oscillation results, presented for the first time, are in good agreement with simulation results. © 2011 Elsevier Ltd.

  16. General dosimetry model for internal contamination with radioisotopes

    International Nuclear Information System (INIS)

    Nino, L.

    1989-01-01

    Radiation dose by inner contamination with radioisotopes is not measured directly but evaluated by the application of mathematical models of fixation and elimination, taken into account biological activity of each organ with respect to the incorporated material. Models proposed by ICRP for the respiratory and gastrointestinal tracts (30) seems that they should not be applied independently because of the evident correlation between them. In this paper both models are integrated in a more general one with neither modification nor limitation of the starting models. It has been applied to some patients in the Instituto Nacional de Cancerologia, who received some I-131 dose via oral and results are quite similar to dose experimentally obtained via urine spectrograms. Based on this results the method was formalized and applied to professional exposed personnel of the medical staff at the same Institute; due to high doses found in some of the urine samples, probable I-131 air contamination could be supposed

  17. Working covariance model selection for generalized estimating equations.

    Science.gov (United States)

    Carey, Vincent J; Wang, You-Gan

    2011-11-20

    We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. Copyright © 2011 John Wiley & Sons, Ltd.

  18. Pharmaceutical industry and trade liberalization using computable general equilibrium model.

    Science.gov (United States)

    Barouni, M; Ghaderi, H; Banouei, Aa

    2012-01-01

    Computable general equilibrium models are known as a powerful instrument in economic analyses and widely have been used in order to evaluate trade liberalization effects. The purpose of this study was to provide the impacts of trade openness on pharmaceutical industry using CGE model. Using a computable general equilibrium model in this study, the effects of decrease in tariffs as a symbol of trade liberalization on key variables of Iranian pharmaceutical products were studied. Simulation was performed via two scenarios in this study. The first scenario was the effect of decrease in tariffs of pharmaceutical products as 10, 30, 50, and 100 on key drug variables, and the second was the effect of decrease in other sectors except pharmaceutical products on vital and economic variables of pharmaceutical products. The required data were obtained and the model parameters were calibrated according to the social accounting matrix of Iran in 2006. The results associated with simulation demonstrated that the first scenario has increased import, export, drug supply to markets and household consumption, while import, export, supply of product to market, and household consumption of pharmaceutical products would averagely decrease in the second scenario. Ultimately, society welfare would improve in all scenarios. We presents and synthesizes the CGE model which could be used to analyze trade liberalization policy issue in developing countries (like Iran), and thus provides information that policymakers can use to improve the pharmacy economics.

  19. Border Collision Bifurcations in a Generalized Model of Population Dynamics

    Directory of Open Access Journals (Sweden)

    Lilia M. Ladino

    2016-01-01

    Full Text Available We analyze the dynamics of a generalized discrete time population model of a two-stage species with recruitment and capture. This generalization, which is inspired by other approaches and real data that one can find in literature, consists in considering no restriction for the value of the two key parameters appearing in the model, that is, the natural death rate and the mortality rate due to fishing activity. In the more general case the feasibility of the system has been preserved by posing opportune formulas for the piecewise map defining the model. The resulting two-dimensional nonlinear map is not smooth, though continuous, as its definition changes as any border is crossed in the phase plane. Hence, techniques from the mathematical theory of piecewise smooth dynamical systems must be applied to show that, due to the existence of borders, abrupt changes in the dynamic behavior of population sizes and multistability emerge. The main novelty of the present contribution with respect to the previous ones is that, while using real data, richer dynamics are produced, such as fluctuations and multistability. Such new evidences are of great interest in biology since new strategies to preserve the survival of the species can be suggested.

  20. Dynamical generalization of a solvable family of two-electron model atoms with general interparticle repulsion

    International Nuclear Information System (INIS)

    Niehaus, T A; Suhai, S; March, N H

    2008-01-01

    Holas, Howard and March (2003 Phys. Lett. A 310 451) have obtained analytic solutions for ground-state properties of a whole family of two-electron spin-compensated harmonically confined model atoms whose different members are characterized by a specific interparticle potential energy u(r 12 ). Here, we make a start on the dynamic generalization of the harmonic external potential, the motivation being the serious criticism levelled recently against the foundations of time-dependent density-functional theory (e.g., Schirmer and Dreuw 2007 Phys. Rev. A 75 022513). In this context, we derive a simplified expression for the time-dependent electron density for arbitrary interparticle interaction, which is fully determined by a one-dimensional non-interacting Hamiltonian. Moreover, a closed solution for the momentum space density in the Moshinsky model is obtained

  1. The chaos and control of a food chain model supplying additional food to top-predator

    International Nuclear Information System (INIS)

    Sahoo, Banshidhar; Poria, Swarup

    2014-01-01

    Highlights: • We propose a chaotic food chain model supplying additional food to top-predator. • Local and global stability conditions are derived in presence of additional food. • Chaos is controlled only by increasing quantity of additional food. • System enters into periodic region and depicts Hopf bifurcations supplying additional food. • This an application of non-chemical methods for controlling chaos. -- Abstract: The control and management of chaotic population is one of the main objectives for constructing mathematical model in ecology today. In this paper, we apply a technique of controlling chaotic predator–prey population dynamics by supplying additional food to top-predator. We formulate a three species predator–prey model supplying additional food to top-predator. Existence conditions and local stability criteria of equilibrium points are determined analytically. Persistence conditions for the system are derived. Global stability conditions of interior equilibrium point is calculated. Theoretical results are verified through numerical simulations. Phase diagram is presented for various quality and quantity of additional food. One parameter bifurcation analysis is done with respect to quality and quantity of additional food separately keeping one of them fixed. Using MATCONT package, we derive the bifurcation scenarios when both the parameters quality and quantity of additional food vary together. We predict the existence of Hopf point (H), limit point (LP) and branch point (BP) in the model for suitable supply of additional food. We have computed the regions of different dynamical behaviour in the quantity–quality parametric plane. From our study we conclude that chaotic population dynamics of predator prey system can be controlled to obtain regular population dynamics only by supplying additional food to top predator. This study is aimed to introduce a new non-chemical chaos control mechanism in a predator–prey system with the

  2. Nuclear inertia for fission in a generalized cranking model

    International Nuclear Information System (INIS)

    Kunz, J.; Nix, J.R.

    1984-01-01

    The Inglis cranking model has been widely used to calculate the nuclear inertia associated with collective degrees of freedom. After the inclusion of pairing correlations, theoretical results obtained with the cranking model for nuclear rotations and γ-vibrations were in relatively good agreement with experimental data. Calculations of β-vibrational inertias were also performed in the cranking model for fission deformations. Theoretical results were several times the irrotational values and gave reasonable agreement with experimental spontaneous-fission lifetimes, although in one study a renormalization factor of 0.8 was required. However, as pointed out by many authors, the Inglis cranking model possesses two serious deficiencies. First, problems arise when the single-particle potential contains momentum-dependence terms. Second, in the limit of large pairing strength the inertia approaches zero instead of a finite (irrotational) limit. Alternative approaches to the cranking model which did not lead to such unacceptable results were developed by Migdal, Belyaev and Thouless and Valatin. They showed that these deficiencies of the cranking model are due to a lack of self-consistency, since the reaction of the mean field to the collective motion is neglected in the Inglis model. Previously we used their arguments and developed a generalized cranking model for stationary collective motion. Here it is shown how to develop a time-dependent formalism appropriate to β-vibrations and fission. 10 references

  3. A general modeling framework for describing spatially structured population dynamics

    Science.gov (United States)

    Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

    2017-01-01

    Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance

  4. Research on Capacity Addition using Market Model with Transmission Congestion under Competitive Environment

    Science.gov (United States)

    Katsura, Yasufumi; Attaviriyanupap, Pathom; Kataoka, Yoshihiko

    In this research, the fundamental premises for deregulation of the electric power industry are reevaluated. The authors develop a simple model to represent wholesale electricity market with highly congested network. The model is developed by simplifying the power system and market in New York ISO based on available data of New York ISO in 2004 with some estimation. Based on the developed model and construction cost data from the past, the economic impact of transmission line addition on market participants and the impact of deregulation on power plant additions under market with transmission congestion are studied. Simulation results show that the market signals may fail to facilitate proper capacity additions and results in the undesirable over-construction and insufficient-construction cycle of capacity addition.

  5. Incorporating additional tree and environmental variables in a lodgepole pine stem profile model

    Science.gov (United States)

    John C. Byrne

    1993-01-01

    A new variable-form segmented stem profile model is developed for lodgepole pine (Pinus contorta) trees from the northern Rocky Mountains of the United States. I improved estimates of stem diameter by predicting two of the model coefficients with linear equations using a measure of tree form, defined as a ratio of dbh and total height. Additional improvements were...

  6. General Potential-Current Model and Validation for Electrocoagulation

    International Nuclear Information System (INIS)

    Dubrawski, Kristian L.; Du, Codey; Mohseni, Madjid

    2014-01-01

    A model relating potential and current in continuous parallel plate iron electrocoagulation (EC) was developed for application in drinking water treatment. The general model can be applied to any EC parallel plate system relying only on geometric and tabulated input variables without the need of system-specific experimentally derived constants. For the theoretical model, the anode and cathode were vertically divided into n equipotential segments in a single pass, upflow, and adiabatic EC reactor. Potential and energy balances were simultaneously solved at each vertical segment, which included the contribution of ionic concentrations, solution temperature and conductivity, cathodic hydrogen flux, and gas/liquid ratio. We experimentally validated the numerical model with a vertical upflow EC reactor using a 24 cm height 99.99% pure iron anode divided into twelve 2 cm segments. Individual experimental currents from each segment were summed to determine total current, and compared with the theoretically derived value. Several key variables were studied to determine their impact on model accuracy: solute type, solute concentration, current density, flow rate, inter-electrode gap, and electrode surface condition. Model results were in good agreement with experimental values at cell potentials of 2-20 V (corresponding to a current density range of approximately 50-800 A/m 2 ), with mean relative deviation of 9% for low flow rate, narrow electrode gap, polished electrodes, and 150 mg/L NaCl. Highest deviation occurred with a large electrode gap, unpolished electrodes, and Na 2 SO 4 electrolyte, due to parasitic H 2 O oxidation and less than unity current efficiency. This is the first general model which can be applied to any parallel plate EC system for accurate electrochemical voltage or current prediction

  7. Between and beyond additivity and non-additivity : the statistical modelling of genotype by environment interaction in plant breeding

    NARCIS (Netherlands)

    Eeuwijk, van F.A.

    1996-01-01

    In plant breeding it is a common observation to see genotypes react differently to environmental changes. This phenomenon is called genotype by environment interaction. Many statistical approaches for analysing genotype by environment interaction rely heavily on the analysis of variance model.

  8. A Generalized Dynamic Model of Geared System: Establishment and Application

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2011-12-01

    Full Text Available In order to make the dynamic characteristic simulation of the ordinary and planetary gears drive more accurate and more efficient , a generalized dynamic model of geared system is established including internal and external mesh gears in this paper. It is used to build a mathematical model, which achieves the auto judgment of the gear mesh state. We do not need to concern about active or passive gears any more, and the complicated power flow analysis can be avoided. With the numerical integration computation, the axis orbits diagram and dynamic gear mesh force characteristic are acquired and the results show that the dynamic response of translational displacement is greater when contacting line direction change is considered, and with the quickly change of direction of contacting line, the amplitude of mesh force would be increased, which easily causes the damage to the gear tooth. Moreover, compared with ordinary gear, dynamic responses of planetary gear would be affected greater by the gear backlash. Simulation results show the effectiveness of the generalized dynamic model and the mathematical model.

  9. Consensus-based training and assessment model for general surgery.

    Science.gov (United States)

    Szasz, P; Louridas, M; de Montbrun, S; Harris, K A; Grantcharov, T P

    2016-05-01

    Surgical education is becoming competency-based with the implementation of in-training milestones. Training guidelines should reflect these changes and determine the specific procedures for such milestone assessments. This study aimed to develop a consensus view regarding operative procedures and tasks considered appropriate for junior and senior trainees, and the procedures that can be used as technical milestone assessments for trainee progression in general surgery. A Delphi process was followed where questionnaires were distributed to all 17 Canadian general surgery programme directors. Items were ranked on a 5-point Likert scale, with consensus defined as Cronbach's α of at least 0·70. Items rated 4 or above on the 5-point Likert scale by 80 per cent of the programme directors were included in the models. Two Delphi rounds were completed, with 14 programme directors taking part in round one and 11 in round two. The overall consensus was high (Cronbach's α = 0·98). The training model included 101 unique procedures and tasks, 24 specific to junior trainees, 68 specific to senior trainees, and nine appropriate to all. The assessment model included four procedures. A system of operative procedures and tasks for junior- and senior-level trainees has been developed along with an assessment model for trainee progression. These can be used as milestones in competency-based assessments. © 2016 BJS Society Ltd Published by John Wiley & Sons Ltd.

  10. Analog quantum simulation of generalized Dicke models in trapped ions

    Science.gov (United States)

    Aedo, Ibai; Lamata, Lucas

    2018-04-01

    We propose the analog quantum simulation of generalized Dicke models in trapped ions. By combining bicromatic laser interactions on multiple ions we can generate all regimes of light-matter coupling in these models, where here the light mode is mimicked by a motional mode. We present numerical simulations of the three-qubit Dicke model both in the weak field (WF) regime, where the Jaynes-Cummings behavior arises, and the ultrastrong coupling (USC) regime, where a rotating-wave approximation cannot be considered. We also simulate the two-qubit biased Dicke model in the WF and USC regimes and the two-qubit anisotropic Dicke model in the USC regime and the deep-strong coupling regime. The agreement between the mathematical models and the ion system convinces us that these quantum simulations can be implemented in the laboratory with current or near-future technology. This formalism establishes an avenue for the quantum simulation of many-spin Dicke models in trapped ions.

  11. One-dimensional model of steady, compressible channel flow with mass, momentum, and energy addition

    International Nuclear Information System (INIS)

    Johnston, S.C.

    1976-09-01

    A one-dimensional model of steady, compressible channel flow with mass, momentum and energy addition is discussed. An exact solution to the governing equations was found and from it a similarity parameter relating dimensionless mass, momentum and energy addition identified. This similarity parameter is used to make two flows having different dimensionless mass, momentum and energy additions equivalent. Application of the similarity parameter to the LASL Intense Neutron Source experiment and the Sandia simulation of that experiment results in an expression relating the dimensionless mass addition of combustible gas required in the Sandia experiment to dimensionless energy addition in the LASL experiment. Results of the analysis indicate that the Sandia experiment can realistically simulate the energy addition in the LASL Intense Neutron Source experiment

  12. Topics in conformal invariance and generalized sigma models

    International Nuclear Information System (INIS)

    Bernardo, L.M.; Lawrence Berkeley National Lab., CA

    1997-05-01

    This thesis consists of two different parts, having in common the fact that in both, conformal invariance plays a central role. In the first part, the author derives conditions for conformal invariance, in the large N limit, and for the existence of an infinite number of commuting classical conserved quantities, in the Generalized Thirring Model. The treatment uses the bosonized version of the model. Two different approaches are used to derive conditions for conformal invariance: the background field method and the Hamiltonian method based on an operator algebra, and the agreement between them is established. The author constructs two infinite sets of non-local conserved charges, by specifying either periodic or open boundary conditions, and he finds the Poisson Bracket algebra satisfied by them. A free field representation of the algebra satisfied by the relevant dynamical variables of the model is also presented, and the structure of the stress tensor in terms of free fields (and free currents) is studied in detail. In the second part, the author proposes a new approach for deriving the string field equations from a general sigma model on the world sheet. This approach leads to an equation which combines some of the attractive features of both the renormalization group method and the covariant beta function treatment of the massless excitations. It has the advantage of being covariant under a very general set of both local and non-local transformations in the field space. The author applies it to the tachyon, massless and first massive level, and shows that the resulting field equations reproduce the correct spectrum of a left-right symmetric closed bosonic string

  13. A Model Independent General Search for new physics in ATLAS

    CERN Document Server

    Amoroso, S; The ATLAS collaboration

    2016-01-01

    We present results of a model-independent general search for new phenomena in proton-proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS detector at the LHC. The data set corresponds to a total integrated luminosity of 20.3~\\ifb. Event topologies involving isolated electrons, photons and muons, as well as jets, including those identified as originating from \\textit{b}-quarks (\\textit{b}-jets) and missing transverse momentum are investigated. The events are subdivided according to their final states into exclusive event classes. For the 697 classes with a Standard Model expectation greater than 0.1 events, a search algorithm tests the compatibility of data against the Monte Carlo simulated background in three kinematic variables sensitive to new physics effects. No significant deviation is found in data. The number and size of the observed deviations follow the Standard Model expectation obtained from simulated pseudo-experiments.

  14. A Model Independent General Search for new physics in ATLAS

    Science.gov (United States)

    Amoroso, S.; ATLAS Collaboration

    2016-04-01

    We present results of a model-independent general search for new phenomena in proton-proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS detector at the LHC. The data set corresponds to a total integrated luminosity of 20.3 fb-1. Event topologies involving isolated electrons, photons and muons, as well as jets, including those identified as originating from b-quarks (b-jets) and missing transverse momentum are investigated. The events are subdivided according to their final states into exclusive event classes. For the 697 classes with a Standard Model expectation greater than 0.1 events, a search algorithm tests the compatibility of data against the Monte Carlo simulated background in three kinematic variables sensitive to new physics effects. No significant deviation is found in data. The number and size of the observed deviations follow the Standard Model expectation obtained from simulated pseudo-experiments.

  15. Statistical mechanics of sparse generalization and graphical model selection

    International Nuclear Information System (INIS)

    Lage-Castellanos, Alejandro; Pagnani, Andrea; Weigt, Martin

    2009-01-01

    One of the crucial tasks in many inference problems is the extraction of an underlying sparse graphical model from a given number of high-dimensional measurements. In machine learning, this is frequently achieved using, as a penalty term, the L p norm of the model parameters, with p≤1 for efficient dilution. Here we propose a statistical mechanics analysis of the problem in the setting of perceptron memorization and generalization. Using a replica approach, we are able to evaluate the relative performance of naive dilution (obtained by learning without dilution, following by applying a threshold to the model parameters), L 1 dilution (which is frequently used in convex optimization) and L 0 dilution (which is optimal but computationally hard to implement). Whereas both L p diluted approaches clearly outperform the naive approach, we find a small region where L 0 works almost perfectly and strongly outperforms the simpler to implement L 1 dilution

  16. Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

    Science.gov (United States)

    Sumner, Jeremy G

    2017-03-01

    We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

  17. Toward a general psychological model of tension and suspense.

    Science.gov (United States)

    Lehne, Moritz; Koelsch, Stefan

    2015-01-01

    Tension and suspense are powerful emotional experiences that occur in a wide variety of contexts (e.g., in music, film, literature, and everyday life). The omnipresence of tension and suspense suggests that they build on very basic cognitive and affective mechanisms. However, the psychological underpinnings of tension experiences remain largely unexplained, and tension and suspense are rarely discussed from a general, domain-independent perspective. In this paper, we argue that tension experiences in different contexts (e.g., musical tension or suspense in a movie) build on the same underlying psychological processes. We discuss key components of tension experiences and propose a domain-independent model of tension and suspense. According to this model, tension experiences originate from states of conflict, instability, dissonance, or uncertainty that trigger predictive processes directed at future events of emotional significance. We also discuss possible neural mechanisms underlying tension and suspense. The model provides a theoretical framework that can inform future empirical research on tension phenomena.

  18. A generalized and parameterized interference model for cognitive radio networks

    KAUST Repository

    Mahmood, Nurul Huda

    2011-06-01

    For meaningful co-existence of cognitive radios with primary system, it is imperative that the cognitive radio system is aware of how much interference it generates at the primary receivers. This can be done through statistical modeling of the interference as perceived at the primary receivers. In this work, we propose a generalized model for the interference generated by a cognitive radio network, in the presence of small and large scale fading, at a primary receiver located at the origin. We then demonstrate how this model can be used to estimate the impact of cognitive radio transmission on the primary receiver in terms of different outage probabilities. Finally, our analytical findings are validated through some selected computer-based simulations. © 2011 IEEE.

  19. Insights into the Electronic Structure of Ozone and Sulfur Dioxide from Generalized Valence Bond Theory: Addition of Hydrogen Atoms.

    Science.gov (United States)

    Lindquist, Beth A; Takeshita, Tyler Y; Dunning, Thom H

    2016-05-05

    Ozone (O3) and sulfur dioxide (SO2) are valence isoelectronic species, yet their properties and reactivities differ dramatically. In particular, O3 is highly reactive, whereas SO2 is chemically relatively stable. In this paper, we investigate serial addition of hydrogen atoms to both the terminal atoms of O3 and SO2 and to the central atom of these species. It is well-known that the terminal atoms of O3 are much more amenable to bond formation than those of SO2. We show that the differences in the electronic structure of the π systems in the parent triatomic species account for the differences in the addition of hydrogen atoms to the terminal atoms of O3 and SO2. Further, we find that the π system in SO2, which is a recoupled pair bond dyad, facilitates the addition of hydrogen atoms to the sulfur atom, resulting in stable HSO2 and H2SO2 species.

  20. The generalized hedgehog and the projected chiral soliton model

    International Nuclear Information System (INIS)

    Fiolhais, M.; Kernforschungsanlage Juelich G.m.b.H.; Goeke, K.; Bochum Univ.; Gruemmer, F.; Urbano, J.N.

    1988-01-01

    The linear chiral soliton model with quark fields and elementary pion and sigma fields is solved in order to describe static properties of the nucleon and the delta resonance. To this end a Fock state of the system is constructed which consists of three valence quarks in a 1s orbit with a generalized hedgehog spin-flavour configuration cosηvertical strokeu↓> - sin ηvertical stroked↑>. Coherent states are used to provide a quantum description for the mesonic parts of the total wave function. The corresponding classical pion field also exhibits a generalized hedgehog structure. Various nucleon properties are calculated. These include proton and neutron charge raii, and the mangnetic moment of the proton for which experiment is obtained. (orig./HSI)

  1. General Business Model Patterns for Local Energy Management Concepts

    Energy Technology Data Exchange (ETDEWEB)

    Facchinetti, Emanuele, E-mail: emanuele.facchinetti@hslu.ch; Sulzer, Sabine [Lucerne Competence Center for Energy Research, Lucerne University of Applied Science and Arts, Horw (Switzerland)

    2016-03-03

    The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.

  2. General Business Model Patterns for Local Energy Management Concepts

    International Nuclear Information System (INIS)

    Facchinetti, Emanuele; Sulzer, Sabine

    2016-01-01

    The transition toward a more sustainable global energy system, significantly relying on renewable energies and decentralized energy systems, requires a deep reorganization of the energy sector. The way how energy services are generated, delivered, and traded is expected to be very different in the coming years. Business model innovation is recognized as a key driver for the successful implementation of the energy turnaround. This work contributes to this topic by introducing a heuristic methodology easing the identification of general business model patterns best suited for Local Energy Management concepts such as Energy Hubs. A conceptual framework characterizing the Local Energy Management business model solution space is developed. Three reference business model patterns providing orientation across the defined solution space are identified, analyzed, and compared. Through a market review, a number of successfully implemented innovative business models have been analyzed and allocated within the defined solution space. The outcomes of this work offer to potential stakeholders a starting point and guidelines for the business model innovation process, as well as insights for policy makers on challenges and opportunities related to Local Energy Management concepts.

  3. A General Accelerated Degradation Model Based on the Wiener Process

    Directory of Open Access Journals (Sweden)

    Le Liu

    2016-12-01

    Full Text Available Accelerated degradation testing (ADT is an efficient tool to conduct material service reliability and safety evaluations by analyzing performance degradation data. Traditional stochastic process models are mainly for linear or linearization degradation paths. However, those methods are not applicable for the situations where the degradation processes cannot be linearized. Hence, in this paper, a general ADT model based on the Wiener process is proposed to solve the problem for accelerated degradation data analysis. The general model can consider the unit-to-unit variation and temporal variation of the degradation process, and is suitable for both linear and nonlinear ADT analyses with single or multiple acceleration variables. The statistical inference is given to estimate the unknown parameters in both constant stress and step stress ADT. The simulation example and two real applications demonstrate that the proposed method can yield reliable lifetime evaluation results compared with the existing linear and time-scale transformation Wiener processes in both linear and nonlinear ADT analyses.

  4. Generalized fish life-cycle poplulation model and computer program

    International Nuclear Information System (INIS)

    DeAngelis, D.L.; Van Winkle, W.; Christensen, S.W.; Blum, S.R.; Kirk, B.L.; Rust, B.W.; Ross, C.

    1978-03-01

    A generalized fish life-cycle population model and computer program have been prepared to evaluate the long-term effect of changes in mortality in age class 0. The general question concerns what happens to a fishery when density-independent sources of mortality are introduced that act on age class 0, particularly entrainment and impingement at power plants. This paper discusses the model formulation and computer program, including sample results. The population model consists of a system of difference equations involving age-dependent fecundity and survival. The fecundity for each age class is assumed to be a function of both the fraction of females sexually mature and the weight of females as they enter each age class. Natural mortality for age classes 1 and older is assumed to be independent of population size. Fishing mortality is assumed to vary with the number and weight of fish available to the fishery. Age class 0 is divided into six life stages. The probability of survival for age class 0 is estimated considering both density-independent mortality (natural and power plant) and density-dependent mortality for each life stage. Two types of density-dependent mortality are included. These are cannibalism of each life stage by older age classes and intra-life-stage competition

  5. A general relativistic hydrostatic model for a galaxy

    International Nuclear Information System (INIS)

    Hojman, R.; Pena, L.; Zamorano, N.

    1991-08-01

    The existence of huge amounts of mass laying at the center of some galaxies has been inferred by data gathered at different wavelengths. It seems reasonable then, to incorporate general relativity in the study of these objects. A general relativistic hydrostatic model for a galaxy is studied. We assume that the galaxy is dominated by the dark mass except at the nucleus, where the luminous matter prevails. It considers four different concentric spherically symmetric regions, properly matched and with a specific equation of state for each of them. It yields a slowly raising orbital velocity for a test particle moving in the background gravitational field of the dark matter region. In this sense we think of this model as representing a spiral galaxy. The dependence of the mass on the radius in cluster and field spiral galaxies published recently, can be used to fix the size of the inner luminous core. A vanishing pressure at the edge of the galaxy and the assumption of hydrostatic equilibrium everywhere generates a jump in the density and the orbital velocity at the shell enclosing the galaxy. This is a prediction of this model. The ratio between the size core and the shells introduced here are proportional to their densities. In this sense the model is scale invariant. It can be used to reproduce a galaxy or the central region of a galaxy. We have also compared our results with those obtained with the Newtonian isothermal sphere. The luminosity is not included in our model as an extra variable in the determination of the orbital velocity. (author). 29 refs, 10 figs

  6. A generalized logarithmic image processing model based on the gigavision sensor model.

    Science.gov (United States)

    Deng, Guang

    2012-03-01

    The logarithmic image processing (LIP) model is a mathematical theory providing generalized linear operations for image processing. The gigavision sensor (GVS) is a new imaging device that can be described by a statistical model. In this paper, by studying these two seemingly unrelated models, we develop a generalized LIP (GLIP) model. With the LIP model being its special case, the GLIP model not only provides new insights into the LIP model but also defines new image representations and operations for solving general image processing problems that are not necessarily related to the GVS. A new parametric LIP model is also developed. To illustrate the application of the new scalar multiplication operation, we propose an energy-preserving algorithm for tone mapping, which is a necessary step in image dehazing. By comparing with results using two state-of-the-art algorithms, we show that the new scalar multiplication operation is an effective tool for tone mapping.

  7. A GENERALIZATION OF TRADITIONAL KANO MODEL FOR CUSTOMER REQUIREMENTS ANALYSIS

    Directory of Open Access Journals (Sweden)

    Renáta Turisová

    2015-07-01

    Full Text Available Purpose: The theory of attractiveness determines the relationship between the technically achieved and customer perceived quality of product attributes. The most frequently used approach in the theory of attractiveness is the implementation of Kano‘s model. There exist a lot of generalizations of that model which take into consideration various aspects and approaches focused on understanding the customer preferences and identification of his priorities for a selling  product. The aim of this article is to outline another possible generalization of Kano‘s model.Methodology/Approach: The traditional Kano’s model captures the nonlinear relationship between reached attributes of quality and customer requirements. The individual attributes of quality are divided into three main categories: must-be, one-dimensional, attractive quality and into two side categories: indifferent and reverse quality. The well selling product has to contain the must-be attribute. It should contain as many one-dimensional attributes as possible. If there are also supplementary attractive attributes, it means that attractiveness of the entire product, from the viewpoint of the customer, nonlinearly sharply rises what has a direct positive impact on a decision of potential customer when purchasing the product. In this article, we show that inclusion of individual quality attributes of a product to the mentioned categories depends, among other things, also on costs on life cycle of the product, respectively on a price of the product on the market.Findings: In practice, we are often encountering the inclusion of products into different price categories: lower, middle and upper class. For a certain type of products the category is either directly declared by a producer (especially in automotive industry, or is determined by a customer by means of assessment of available market prices. To each of those groups of a products different customer expectations can be assigned

  8. Water tracers in the general circulation model ECHAM

    International Nuclear Information System (INIS)

    Hoffmann, G.; Heimann, M.

    1993-01-01

    We have installed a water tracer model into the ECHAM General Circulation Model (GCM) parameterizing all fractionation processes of the stable water isotopes ( 1 H 2 18 O and 1 H 2 H 16 O). A five year simulation was performed under present day conditions. We focus on the applicability of such a water tracer model to obtain information about the quality of the hydrological cycle of the GCM. The analysis of the simulated 1 H 2 18 O composition of the precipitation indicates too weak fractionated precipitation over the Antarctic and Greenland ice sheets and too strong fractionated precipitation over large areas of the tropical and subtropical land masses. We can show that these deficiencies are connected with problems of model quantities such as the precipitation and the resolution of the orography. The linear relationship between temperature and the δ 18 O value, i.e. the Dansgaard slope, is reproduced quite well in the model. The slope is slightly too flat and the strong correlation between temperature and δ 18 O vanishes at very low temperatures compared to the observations. (orig.)

  9. Scaling of Precipitation Extremes Modelled by Generalized Pareto Distribution

    Science.gov (United States)

    Rajulapati, C. R.; Mujumdar, P. P.

    2017-12-01

    Precipitation extremes are often modelled with data from annual maximum series or peaks over threshold series. The Generalized Pareto Distribution (GPD) is commonly used to fit the peaks over threshold series. Scaling of precipitation extremes from larger time scales to smaller time scales when the extremes are modelled with the GPD is burdened with difficulties arising from varying thresholds for different durations. In this study, the scale invariance theory is used to develop a disaggregation model for precipitation extremes exceeding specified thresholds. A scaling relationship is developed for a range of thresholds obtained from a set of quantiles of non-zero precipitation of different durations. The GPD parameters and exceedance rate parameters are modelled by the Bayesian approach and the uncertainty in scaling exponent is quantified. A quantile based modification in the scaling relationship is proposed for obtaining the varying thresholds and exceedance rate parameters for shorter durations. The disaggregation model is applied to precipitation datasets of Berlin City, Germany and Bangalore City, India. From both the applications, it is observed that the uncertainty in the scaling exponent has a considerable effect on uncertainty in scaled parameters and return levels of shorter durations.

  10. General mirror pairs for gauged linear sigma models

    Energy Technology Data Exchange (ETDEWEB)

    Aspinwall, Paul S.; Plesser, M. Ronen [Departments of Mathematics and Physics, Duke University,Box 90320, Durham, NC 27708-0320 (United States)

    2015-11-05

    We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.

  11. General mirror pairs for gauged linear sigma models

    International Nuclear Information System (INIS)

    Aspinwall, Paul S.; Plesser, M. Ronen

    2015-01-01

    We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.

  12. Comparison of different stepwise screening strategies for type 2 diabetes: Finding from Danish general practice, Addition-DK.

    Science.gov (United States)

    Dalsgaard, Else-Marie; Christensen, Jesper O; Skriver, Mette Vinter; Borch-Johnsen, Knut; Lauritzen, Torsten; Sandbaek, Annelli

    2010-12-01

    To examine attendance, number of people with T2DM and costs of three different stepwise screening strategies for T2DM in general practice (GP). Diabetes risk questionnaires were mailed to individuals aged 40-69 years from 45 general practices in 2001-2002 and individuals at high risk for T2DM, were asked to contact their GP to arrange a screening test. In 2005-2006, 26 general practices were randomised into two different opportunistic screening programmes (OP-direct and OP-subsequent) and risk questionnaires were distributed to individuals aged 40-69 years during GP consultations. In the OP-direct approach, high-risk individuals were offered to start the screening during the actual consultation while high-risk individuals in the OP-subsequent approach, were invited to a screening test at a later date. We report attendance, number of people with T2DM and costs of each screening approach. The mail-distributed approach identified 0.8% of the target population with T2DM, the OP-direct approach and the OP-subsequent approach, 0.9% and 0.5% respectively. Cost per person with T2DM was in the mail-distributed approach: € 1058, OP-direct approach: € 707 and the OP-subsequent approach: € 727. This study indicates that opportunistic screening identifies the same level of unknown diabetes as a mail-distributed approach but with lower costs. Copyright © 2010 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.

  13. On the Symbol Error Rate of M-ary MPSK over Generalized Fading Channels with Additive Laplacian Noise

    KAUST Repository

    Soury, Hamza

    2015-01-07

    This work considers the symbol error rate of M-ary phase shift keying (MPSK) constellations over extended Generalized-K fading with Laplacian noise and using a minimum distance detector. A generic closed form expression of the conditional and the average probability of error is obtained and simplified in terms of the Fox’s H function. More simplifications to well known functions for some special cases of fading are also presented. Finally, the mathematical formalism is validated with some numerical results examples done by computer based simulations [1].

  14. On the symbol error rate of M-ary MPSK over generalized fading channels with additive Laplacian noise

    KAUST Repository

    Soury, Hamza

    2014-06-01

    This paper considers the symbol error rate of M-ary phase shift keying (MPSK) constellations over extended Generalized-K fading with Laplacian noise and using a minimum distance detector. A generic closed form expression of the conditional and the average probability of error is obtained and simplified in terms of the Fox\\'s H function. More simplifications to well known functions for some special cases of fading are also presented. Finally, the mathematical formalism is validated with some numerical results examples done by computer based simulations. © 2014 IEEE.

  15. On the symbol error rate of M-ary MPSK over generalized fading channels with additive Laplacian noise

    KAUST Repository

    Soury, Hamza; Alouini, Mohamed-Slim

    2014-01-01

    This paper considers the symbol error rate of M-ary phase shift keying (MPSK) constellations over extended Generalized-K fading with Laplacian noise and using a minimum distance detector. A generic closed form expression of the conditional and the average probability of error is obtained and simplified in terms of the Fox's H function. More simplifications to well known functions for some special cases of fading are also presented. Finally, the mathematical formalism is validated with some numerical results examples done by computer based simulations. © 2014 IEEE.

  16. On the Symbol Error Rate of M-ary MPSK over Generalized Fading Channels with Additive Laplacian Noise

    KAUST Repository

    Soury, Hamza; Alouini, Mohamed-Slim

    2015-01-01

    This work considers the symbol error rate of M-ary phase shift keying (MPSK) constellations over extended Generalized-K fading with Laplacian noise and using a minimum distance detector. A generic closed form expression of the conditional and the average probability of error is obtained and simplified in terms of the Fox’s H function. More simplifications to well known functions for some special cases of fading are also presented. Finally, the mathematical formalism is validated with some numerical results examples done by computer based simulations [1].

  17. Estimation of direct effects for survival data by using the Aalen additive hazards model

    DEFF Research Database (Denmark)

    Martinussen, Torben; Vansteelandt, Stijn; Gerster, Mette

    2011-01-01

    We extend the definition of the controlled direct effect of a point exposure on a survival outcome, other than through some given, time-fixed intermediate variable, to the additive hazard scale. We propose two-stage estimators for this effect when the exposure is dichotomous and randomly assigned...... Aalen's additive regression for the event time, given exposure, intermediate variable and confounders. The second stage involves applying Aalen's additive model, given the exposure alone, to a modified stochastic process (i.e. a modification of the observed counting process based on the first...

  18. A Bayesian, generalized frailty model for comet assays.

    Science.gov (United States)

    Ghebretinsae, Aklilu Habteab; Faes, Christel; Molenberghs, Geert; De Boeck, Marlies; Geys, Helena

    2013-05-01

    This paper proposes a flexible modeling approach for so-called comet assay data regularly encountered in preclinical research. While such data consist of non-Gaussian outcomes in a multilevel hierarchical structure, traditional analyses typically completely or partly ignore this hierarchical nature by summarizing measurements within a cluster. Non-Gaussian outcomes are often modeled using exponential family models. This is true not only for binary and count data, but also for, example, time-to-event outcomes. Two important reasons for extending this family are for (1) the possible occurrence of overdispersion, meaning that the variability in the data may not be adequately described by the models, which often exhibit a prescribed mean-variance link, and (2) the accommodation of a hierarchical structure in the data, owing to clustering in the data. The first issue is dealt with through so-called overdispersion models. Clustering is often accommodated through the inclusion of random subject-specific effects. Though not always, one conventionally assumes such random effects to be normally distributed. In the case of time-to-event data, one encounters, for example, the gamma frailty model (Duchateau and Janssen, 2007 ). While both of these issues may occur simultaneously, models combining both are uncommon. Molenberghs et al. ( 2010 ) proposed a broad class of generalized linear models accommodating overdispersion and clustering through two separate sets of random effects. Here, we use this method to model data from a comet assay with a three-level hierarchical structure. Although a conjugate gamma random effect is used for the overdispersion random effect, both gamma and normal random effects are considered for the hierarchical random effect. Apart from model formulation, we place emphasis on Bayesian estimation. Our proposed method has an upper hand over the traditional analysis in that it (1) uses the appropriate distribution stipulated in the literature; (2) deals

  19. Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review

    Directory of Open Access Journals (Sweden)

    Gianpaolo Savio

    2018-01-01

    Full Text Available Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed.

  20. Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review.

    Science.gov (United States)

    Savio, Gianpaolo; Rosso, Stefano; Meneghello, Roberto; Concheri, Gianmaria

    2018-01-01

    Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed.

  1. Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review

    Science.gov (United States)

    Rosso, Stefano; Meneghello, Roberto; Concheri, Gianmaria

    2018-01-01

    Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed. PMID:29487626

  2. Enhancing the performance of model-based elastography by incorporating additional a priori information in the modulus image reconstruction process

    International Nuclear Information System (INIS)

    Doyley, Marvin M; Srinivasan, Seshadri; Dimidenko, Eugene; Soni, Nirmal; Ophir, Jonathan

    2006-01-01

    Model-based elastography is fraught with problems owing to the ill-posed nature of the inverse elasticity problem. To overcome this limitation, we have recently developed a novel inversion scheme that incorporates a priori information concerning the mechanical properties of the underlying tissue structures, and the variance incurred during displacement estimation in the modulus image reconstruction process. The information was procured by employing standard strain imaging methodology, and introduced in the reconstruction process through the generalized Tikhonov approach. In this paper, we report the results of experiments conducted on gelatin phantoms to evaluate the performance of modulus elastograms computed with the generalized Tikhonov (GTK) estimation criterion relative to those computed by employing the un-weighted least-squares estimation criterion, the weighted least-squares estimation criterion and the standard Tikhonov method (i.e., the generalized Tikhonov method with no modulus prior). The results indicate that modulus elastograms computed with the generalized Tikhonov approach had superior elastographic contrast discrimination and contrast recovery. In addition, image reconstruction was more resilient to structural decorrelation noise when additional constraints were imposed on the reconstruction process through the GTK method

  3. Generalized Skyrme model with the loosely bound potential

    Science.gov (United States)

    Gudnason, Sven Bjarke; Zhang, Baiyang; Ma, Nana

    2016-12-01

    We study a generalization of the loosely bound Skyrme model which consists of the Skyrme model with a sixth-order derivative term—motivated by its fluidlike properties—and the second-order loosely bound potential—motivated by lowering the classical binding energies of higher-charged Skyrmions. We use the rational map approximation for the Skyrmion of topological charge B =4 , calculate the binding energy of the latter, and estimate the systematic error in using this approximation. In the parameter space that we can explore within the rational map approximation, we find classical binding energies as low as 1.8%, and once taking into account the contribution from spin-isospin quantization, we obtain binding energies as low as 5.3%. We also calculate the contribution from the sixth-order derivative term to the electric charge density and axial coupling.

  4. Generalized flux states of the t-J model

    International Nuclear Information System (INIS)

    Nori, F.; Abrahams, E.; Zimanyi, G.T.

    1990-01-01

    We investigate certain generalized flux phases arising in a mean-field approach to the t-J model. First, we establish that the energy of noninteracting electrons moving in a uniform magnetic field has an absolute minimum as a function of the flux at exactly one flux quantum per particle. Using this result, we show that if the hard-core nature of the hole bosons is taken into account, then the slave-boson mean-field approximation for the t-J Hamiltonian allows for a solution where both the spinons and the holons experience an average flux of one flux quantum per particle. This enables them to achieve the lowest possible energy within the manifold of spatially uniform flux states. In the case of the continuum model, this is possible only for certain fractional fillings and we speculate that the system may react to this frustration effect by phase separation

  5. Optimisation of a parallel ocean general circulation model

    Directory of Open Access Journals (Sweden)

    M. I. Beare

    1997-10-01

    Full Text Available This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

  6. Optimisation of a parallel ocean general circulation model

    Directory of Open Access Journals (Sweden)

    M. I. Beare

    Full Text Available This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

  7. [Treatment of cloud radiative effects in general circulation models

    International Nuclear Information System (INIS)

    Wang, W.C.

    1993-01-01

    This is a renewal proposal for an on-going project of the Department of Energy (DOE)/Atmospheric Radiation Measurement (ARM) Program. The objective of the ARM Program is to improve the treatment of radiation-cloud in GCMs so that reliable predictions of the timing and magnitude of greenhouse gas-induced global warming and regional responses can be made. The ARM Program supports two research areas: (I) The modeling and analysis of data related to the parameterization of clouds and radiation in general circulation models (GCMs); and (II) the development of advanced instrumentation for both mapping the three-dimensional structure of the atmosphere and high accuracy/precision radiometric observations. The present project conducts research in area (I) and focuses on GCM treatment of cloud life cycle, optical properties, and vertical overlapping. The project has two tasks: (1) Development and Refinement of GCM Radiation-Cloud Treatment Using ARM Data; and (2) Validation of GCM Radiation-Cloud Treatment

  8. Explicit estimating equations for semiparametric generalized linear latent variable models

    KAUST Repository

    Ma, Yanyuan

    2010-07-05

    We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n consistency and asymptotic normality. We explain the computational implementation of our method and illustrate the numerical performance of the estimators in finite sample situations via extensive simulation studies. The advantage of our estimators over the existing likelihood approach is also shown via numerical comparison. We employ the method to analyse a real data example from economics. © 2010 Royal Statistical Society.

  9. Generalized one-loop neutrino mass model with charged particles

    Science.gov (United States)

    Cheung, Kingman; Okada, Hiroshi

    2018-04-01

    We propose a radiative neutrino-mass model by introducing 3 generations of fermion pairs E-(N +1 )/2E+(N +1 )/2 and a couple of multicharged bosonic doublet fields ΦN /2,ΦN /2 +1, where N =1 , 3, 5, 7, 9. We show that the models can satisfy the neutrino masses and oscillation data, and are consistent with lepton-flavor violations, the muon anomalous magnetic moment, the oblique parameters, and the beta function of the U (1 )Y hypercharge gauge coupling. We also discuss the collider signals for various N , namely, multicharged leptons in the final state from the Drell-Yan production of E-(N +1 )/2E+(N +1 )/2. In general, the larger the N the more charged leptons will appear in the final state.

  10. A stratiform cloud parameterization for General Circulation Models

    International Nuclear Information System (INIS)

    Ghan, S.J.; Leung, L.R.; Chuang, C.C.; Penner, J.E.; McCaa, J.

    1994-01-01

    The crude treatment of clouds in General Circulation Models (GCMs) is widely recognized as a major limitation in the application of these models to predictions of global climate change. The purpose of this project is to develop a paxameterization for stratiform clouds in GCMs that expresses stratiform clouds in terms of bulk microphysical properties and their subgrid variability. In this parameterization, precipitating cloud species are distinguished from non-precipitating species, and the liquid phase is distinguished from the ice phase. The size of the non-precipitating cloud particles (which influences both the cloud radiative properties and the conversion of non-precipitating cloud species to precipitating species) is determined by predicting both the mass and number concentrations of each species

  11. A stratiform cloud parameterization for general circulation models

    International Nuclear Information System (INIS)

    Ghan, S.J.; Leung, L.R.; Chuang, C.C.; Penner, J.E.; McCaa, J.

    1994-01-01

    The crude treatment of clouds in general circulation models (GCMs) is widely recognized as a major limitation in applying these models to predictions of global climate change. The purpose of this project is to develop in GCMs a stratiform cloud parameterization that expresses clouds in terms of bulk microphysical properties and their subgrid variability. Various clouds variables and their interactions are summarized. Precipitating cloud species are distinguished from non-precipitating species, and the liquid phase is distinguished from the ice phase. The size of the non-precipitating cloud particles (which influences both the cloud radiative properties and the conversion of non-precipitating cloud species to precipitating species) is determined by predicting both the mass and number concentrations of each species

  12. On the thermodynamic properties of the generalized Gaussian core model

    Directory of Open Access Journals (Sweden)

    B.M.Mladek

    2005-01-01

    Full Text Available We present results of a systematic investigation of the properties of the generalized Gaussian core model of index n. The potential of this system interpolates via the index n between the potential of the Gaussian core model and the penetrable sphere system, thereby varying the steepness of the repulsion. We have used both conventional and self-consistent liquid state theories to calculate the structural and thermodynamic properties of the system; reference data are provided by computer simulations. The results indicate that the concept of self-consistency becomes indispensable to guarantee excellent agreement with simulation data; in particular, structural consistency (in our approach taken into account via the zero separation theorem is obviously a very important requirement. Simulation results for the dimensionless equation of state, β P / ρ, indicate that for an index-value of 4, a clustering transition, possibly into a structurally ordered phase might set in as the system is compressed.

  13. Convex Relaxations for a Generalized Chan-Vese Model

    KAUST Repository

    Bae, Egil

    2013-01-01

    We revisit the Chan-Vese model of image segmentation with a focus on the encoding with several integer-valued labeling functions. We relate several representations with varying amount of complexity and demonstrate the connection to recent relaxations for product sets and to dual maxflow-based formulations. For some special cases, it can be shown that it is possible to guarantee binary minimizers. While this is not true in general, we show how to derive a convex approximation of the combinatorial problem for more than 4 phases. We also provide a method to avoid overcounting of boundaries in the original Chan-Vese model without departing from the efficient product-set representation. Finally, we derive an algorithm to solve the associated discretized problem, and demonstrate that it allows to obtain good approximations for the segmentation problem with various number of regions. © 2013 Springer-Verlag.

  14. The generalized chiral Schwinger model on the two-sphere

    International Nuclear Information System (INIS)

    Bassetto, A.

    1995-01-01

    A family of theories which interpolate between vector and chiral Schwinger models is studied on the two-sphere S 2 . The conflict between the loss of gauge invariance and global geometrical properties is solved by introducing a fixed background connection. In this way the generalized Dirac-Weyl operator can be globally defined on S 2 . The generating functional of the Green functions is obtained by taking carefully into account the contribution of gauge fields with non-trivial topological charge and of the related zero-modes of the Dirac determinant. In the decompactification limit, the Green functions of the flat case are recovered; in particular the fermionic condensate in the vacuum vanishes, at variance with its behaviour in the vector Schwinger model. ((orig.))

  15. A more general interacting model of holographic dark energy

    International Nuclear Information System (INIS)

    Yu Fei; Zhang Jingfei; Lu Jianbo; Wang Wei; Gui Yuanxing

    2010-01-01

    So far, there have been no theories or observational data that deny the presence of interaction between dark energy and dark matter. We extend naturally the holographic dark energy (HDE) model, proposed by Granda and Oliveros, in which the dark energy density includes not only the square of the Hubble scale, but also the time derivative of the Hubble scale to the case with interaction and the analytic forms for the cosmic parameters are obtained under the specific boundary conditions. The various behaviors concerning the cosmic expansion depend on the introduced numerical parameters which are also constrained. The more general interacting model inherits the features of the previous ones of HDE, keeping the consistency of the theory.

  16. A generalization of the quantum Rabi model: exact solution and spectral structure

    International Nuclear Information System (INIS)

    Eckle, Hans-Peter; Johannesson, Henrik

    2017-01-01

    We consider a generalization of the quantum Rabi model where the two-level system and the single-mode cavity oscillator are coupled by an additional Stark-like term. By adapting a method recently introduced by Braak (2011 Phys. Rev. Lett . 107 100401), we solve the model exactly. The low-lying spectrum in the experimentally relevant ultrastrong and deep strong regimes of the Rabi coupling is found to exhibit two striking features absent from the original quantum Rabi model: avoided level crossings for states of the same parity and an anomalously rapid onset of two-fold near-degenerate levels as the Rabi coupling increases. (paper)

  17. Generalized Lorenz models and their routes to chaos. II. Energy-conserving horizontal mode truncations

    International Nuclear Information System (INIS)

    Roy, D.; Musielak, Z.E.

    2007-01-01

    All attempts to generalize the three-dimensional Lorenz model by selecting higher-order Fourier modes can be divided into three categories, namely: vertical, horizontal and vertical-horizontal mode truncations. The previous study showed that the first method allowed only construction of a nine-dimensional system when the selected modes were energy-conserving. The results presented in this paper demonstrate that a five-dimensional model is the lowest-order generalized Lorenz model that can be constructed by the second method and that its route to chaos is the same as that observed in the original Lorenz model. It is shown that the onset of chaos in both systems is determined by a number of modes that describe the vertical temperature difference in a convection roll. In addition, a simple rule that allows selecting modes that conserve energy for each method is derived

  18. Estimation of additive and dominance variance for reproductive traits from different models in Duroc purebred

    Directory of Open Access Journals (Sweden)

    Talerngsak Angkuraseranee

    2010-05-01

    Full Text Available The additive and dominance genetic variances of 5,801 Duroc reproductive and growth records were estimated usingBULPF90 PC-PACK. Estimates were obtained for number born alive (NBA, birth weight (BW, number weaned (NW, andweaning weight (WW. Data were analyzed using two mixed model equations. The first model included fixed effects andrandom effects identifying inbreeding depression, additive gene effect and permanent environments effects. The secondmodel was similar to the first model, but included the dominance genotypic effect. Heritability estimates of NBA, BW, NWand WW from the two models were 0.1558/0.1716, 0.1616/0.1737, 0.0372/0.0874 and 0.1584/0.1516 respectively. Proportionsof dominance effect to total phenotypic variance from the dominance model were 0.1024, 0.1625, 0.0470, and 0.1536 for NBA,BW, NW and WW respectively. Dominance effects were found to have sizable influence on the litter size traits analyzed.Therefore, genetic evaluation with the dominance model (Model 2 is found more appropriate than the animal model (Model 1.

  19. Integrated reservoir characterization: Improvement in heterogeneities stochastic modelling by integration of additional external constraints

    Energy Technology Data Exchange (ETDEWEB)

    Doligez, B.; Eschard, R. [Institut Francais du Petrole, Rueil Malmaison (France); Geffroy, F. [Centre de Geostatistique, Fontainebleau (France)] [and others

    1997-08-01

    The classical approach to construct reservoir models is to start with a fine scale geological model which is informed with petrophysical properties. Then scaling-up techniques allow to obtain a reservoir model which is compatible with the fluid flow simulators. Geostatistical modelling techniques are widely used to build the geological models before scaling-up. These methods provide equiprobable images of the area under investigation, which honor the well data, and which variability is the same than the variability computed from the data. At an appraisal phase, when few data are available, or when the wells are insufficient to describe all the heterogeneities and the behavior of the field, additional constraints are needed to obtain a more realistic geological model. For example, seismic data or stratigraphic models can provide average reservoir information with an excellent areal coverage, but with a poor vertical resolution. New advances in modelisation techniques allow now to integrate this type of additional external information in order to constrain the simulations. In particular, 2D or 3D seismic derived information grids, or sand-shale ratios maps coming from stratigraphic models can be used as external drifts to compute the geological image of the reservoir at the fine scale. Examples are presented to illustrate the use of these new tools, their impact on the final reservoir model, and their sensitivity to some key parameters.

  20. Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series.

    Science.gov (United States)

    Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

    2018-03-01

    Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

  1. Modeling long correlation times using additive binary Markov chains: Applications to wind generation time series

    Science.gov (United States)

    Weber, Juliane; Zachow, Christopher; Witthaut, Dirk

    2018-03-01

    Wind power generation exhibits a strong temporal variability, which is crucial for system integration in highly renewable power systems. Different methods exist to simulate wind power generation but they often cannot represent the crucial temporal fluctuations properly. We apply the concept of additive binary Markov chains to model a wind generation time series consisting of two states: periods of high and low wind generation. The only input parameter for this model is the empirical autocorrelation function. The two-state model is readily extended to stochastically reproduce the actual generation per period. To evaluate the additive binary Markov chain method, we introduce a coarse model of the electric power system to derive backup and storage needs. We find that the temporal correlations of wind power generation, the backup need as a function of the storage capacity, and the resting time distribution of high and low wind events for different shares of wind generation can be reconstructed.

  2. Bayesian inference in an item response theory model with a generalized student t link function

    Science.gov (United States)

    Azevedo, Caio L. N.; Migon, Helio S.

    2012-10-01

    In this paper we introduce a new item response theory (IRT) model with a generalized Student t-link function with unknown degrees of freedom (df), named generalized t-link (GtL) IRT model. In this model we consider only the difficulty parameter in the item response function. GtL is an alternative to the two parameter logit and probit models, since the degrees of freedom (df) play a similar role to the discrimination parameter. However, the behavior of the curves of the GtL is different from those of the two parameter models and the usual Student t link, since in GtL the curve obtained from different df's can cross the probit curves in more than one latent trait level. The GtL model has similar proprieties to the generalized linear mixed models, such as the existence of sufficient statistics and easy parameter interpretation. Also, many techniques of parameter estimation, model fit assessment and residual analysis developed for that models can be used for the GtL model. We develop fully Bayesian estimation and model fit assessment tools through a Metropolis-Hastings step within Gibbs sampling algorithm. We consider a prior sensitivity choice concerning the degrees of freedom. The simulation study indicates that the algorithm recovers all parameters properly. In addition, some Bayesian model fit assessment tools are considered. Finally, a real data set is analyzed using our approach and other usual models. The results indicate that our model fits the data better than the two parameter models.

  3. Evaluation of additional biogeochemical impacts on mitigation pathways in an energy sytem integrated assessment model.

    Science.gov (United States)

    Dessens, O.

    2017-12-01

    Within the last IPCC AR5 a large and systematic sensitivity study around available technologies and timing of policies applied in IAMs to achieve the 2°C target has been conducted. However the simple climate representations included in IAMs are generally tuned to the results of ensemble means. This may result in hiding within the ensemble mean results possible challenging mitigation pathways for the economy or the technology future scenarios. This work provides new insights on the sensitivity of the socio-economic response to different climate factors under a 2°C climate change target in order to help guide future efforts to reduce uncertainty in the climate mitigation decisions. The main objective is to understand and bring new insights on how future global warming will affect the natural biochemical feedbacks on the climate system and what could be the consequences of these feedbacks on the anthropogenic emission pathways with a specific focus on the energy-economy system. It specifically focuses on three issues of the climate representation affecting the energy system transformation and GHG emissions pathways: 1- Impacts of the climate sensitivity (or TCR); 2- Impacts of warming on the radiative forcing (cloudiness,...); 3- Impacts of warming on the carbon cycle (carbon cycle feedback). We use the integrated assessment model TIAM-UCL to examine the mitigation pathways compatible with the 2C target depending on assumptions regarding the 3 issues of the climate representation introduced above. The following key conclusions drawn from this study are that mitigation to 2°C is still possible under strong climate sensitivity (TCR), strong carbon cycle amplification or positive radiative forcing feedback. However, this level of climate mitigation will require a significant transformation in the way we produce and consume energy. Carbon capture and sequestration on electricity generation, industry and biomass is part of the technology pool needed to achieve this

  4. Dark Matter candidate in Inert Doublet Model with additional local gauge symmetry U (1)

    International Nuclear Information System (INIS)

    Gaitán, R.; De Oca, J.H. Montes; Garcés, E. A.; Cabral-Rosetti, L. G.

    2016-01-01

    We consider the Inert Doublet Model (IDM) with an additional local gauge symmetry U (1) and a complex singlet scalar to break the symmetry U (1). The continuous symmetry U (1) is introduced to control the CP-conserving interaction instead of some discrete symmetries as usually. We present the mass spectrum for neutral scalar and gauge bosons and the values of the charges under U (1) for which the model could have a candidate to dark matter. (paper)

  5. Singular solitons of generalized Camassa-Holm models

    International Nuclear Information System (INIS)

    Tian Lixin; Sun Lu

    2007-01-01

    Two generalizations of the Camassa-Holm system associated with the singular analysis are proposed for Painleve integrability properties and the extensions of already known analytic solitons. A remarkable feature of the physical model is that it has peakon solution which has peak form. An alternative WTC test which allowed the identifying of such models directly if formulated in terms of inserting a formed ansatz into these models. For the two models have Painleve property, Painleve-Baecklund systems can be constructed through the expansion of solitons about the singularity manifold. By the implementations of Maple, plentiful new type solitonic structures and some kink waves, which are affected by the variation of energy, are explored. If the energy is infinite in finite time, there will be a collapse in soliton systems by direct numerical simulations. Particularly, there are two collapses coexisting in our regular solitons, which occurred around its central regions. Simulation shows that in the bottom of periodic waves arises the non-zero parts of compactons and anti-compactons. We also get floating solitary waves whose amplitude is infinite. In contrary to which a finite-amplitude blow-up soliton is obtained. Periodic blow-ups are found too. Special kinks which have periodic cuspons are derived

  6. A general evolving model for growing bipartite networks

    International Nuclear Information System (INIS)

    Tian, Lixin; He, Yinghuan; Liu, Haijun; Du, Ruijin

    2012-01-01

    In this Letter, we propose and study an inner evolving bipartite network model. Significantly, we prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. Furthermore, the joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks. Numerical simulations and empirical results are given to verify the theoretical results. -- Highlights: ► We proposed a general evolving bipartite network model which was based on priority connection, reconnection and breaking edges. ► We prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. ► The joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. ► The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks.

  7. Generalized model for k -core percolation and interdependent networks

    Science.gov (United States)

    Panduranga, Nagendra K.; Gao, Jianxi; Yuan, Xin; Stanley, H. Eugene; Havlin, Shlomo

    2017-09-01

    Cascading failures in complex systems have been studied extensively using two different models: k -core percolation and interdependent networks. We combine the two models into a general model, solve it analytically, and validate our theoretical results through extensive simulations. We also study the complete phase diagram of the percolation transition as we tune the average local k -core threshold and the coupling between networks. We find that the phase diagram of the combined processes is very rich and includes novel features that do not appear in the models studying each of the processes separately. For example, the phase diagram consists of first- and second-order transition regions separated by two tricritical lines that merge and enclose a two-stage transition region. In the two-stage transition, the size of the giant component undergoes a first-order jump at a certain occupation probability followed by a continuous second-order transition at a lower occupation probability. Furthermore, at certain fixed interdependencies, the percolation transition changes from first-order → second-order → two-stage → first-order as the k -core threshold is increased. The analytic equations describing the phase boundaries of the two-stage transition region are set up, and the critical exponents for each type of transition are derived analytically.

  8. General Description of Fission Observables - JEFF Report 24. GEF Model

    International Nuclear Information System (INIS)

    Schmidt, Karl-Heinz; Jurado, Beatriz; Amouroux, Charlotte

    2014-06-01

    The Joint Evaluated Fission and Fusion (JEFF) Project is a collaborative effort among the member countries of the OECD Nuclear Energy Agency (NEA) Data Bank to develop a reference nuclear data library. The JEFF library contains sets of evaluated nuclear data, mainly for fission and fusion applications; it contains a number of different data types, including neutron and proton interaction data, radioactive decay data, fission yield data and thermal scattering law data. The General fission (GEF) model is based on novel theoretical concepts and ideas developed to model low energy nuclear fission. The GEF code calculates fission-fragment yields and associated quantities (e.g. prompt neutron and gamma) for a large range of nuclei and excitation energy. This opens up the possibility of a qualitative step forward to improve further the JEFF fission yields sub-library. This report describes the GEF model which explains the complex appearance of fission observables by universal principles of theoretical models and considerations on the basis of fundamental laws of physics and mathematics. The approach reveals a high degree of regularity and provides a considerable insight into the physics of the fission process. Fission observables can be calculated with a precision that comply with the needs for applications in nuclear technology. The relevance of the approach for examining the consistency of experimental results and for evaluating nuclear data is demonstrated. (authors)

  9. Modeling containment of large wildfires using generalized linear mixed-model analysis

    Science.gov (United States)

    Mark Finney; Isaac C. Grenfell; Charles W. McHugh

    2009-01-01

    Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and...

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

    Science.gov (United States)

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

    2017-01-01

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

  11. Generalized PSF modeling for optimized quantitation in PET imaging.

    Science.gov (United States)

    Ashrafinia, Saeed; Mohy-Ud-Din, Hassan; Karakatsanis, Nicolas A; Jha, Abhinav K; Casey, Michael E; Kadrmas, Dan J; Rahmim, Arman

    2017-06-21

    modeling does not offer optimized PET quantitation, and that PSF overestimation may provide enhanced SUV quantitation. Furthermore, generalized PSF modeling may provide a valuable approach for quantitative tasks such as treatment-response assessment and prognostication.

  12. Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks

    Science.gov (United States)

    Kanevski, Mikhail

    2015-04-01

    The research deals with an adaptation and application of Adaptive General Regression Neural Networks (GRNN) to high dimensional environmental data. GRNN [1,2,3] are efficient modelling tools both for spatial and temporal data and are based on nonparametric kernel methods closely related to classical Nadaraya-Watson estimator. Adaptive GRNN, using anisotropic kernels, can be also applied for features selection tasks when working with high dimensional data [1,3]. In the present research Adaptive GRNN are used to study geospatial data predictability and relevant feature selection using both simulated and real data case studies. The original raw data were either three dimensional monthly precipitation data or monthly wind speeds embedded into 13 dimensional space constructed by geographical coordinates and geo-features calculated from digital elevation model. GRNN were applied in two different ways: 1) adaptive GRNN with the resulting list of features ordered according to their relevancy; and 2) adaptive GRNN applied to evaluate all possible models N [in case of wind fields N=(2^13 -1)=8191] and rank them according to the cross-validation error. In both cases training were carried out applying leave-one-out procedure. An important result of the study is that the set of the most relevant features depends on the month (strong seasonal effect) and year. The predictabilities of precipitation and wind field patterns, estimated using the cross-validation and testing errors of raw and shuffled data, were studied in detail. The results of both approaches were qualitatively and quantitatively compared. In conclusion, Adaptive GRNN with their ability to select features and efficient modelling of complex high dimensional data can be widely used in automatic/on-line mapping and as an integrated part of environmental decision support systems. 1. Kanevski M., Pozdnoukhov A., Timonin V. Machine Learning for Spatial Environmental Data. Theory, applications and software. EPFL Press

  13. Evaluation of the H-point standard additions method (HPSAM) and the generalized H-point standard additions method (GHPSAM) for the UV-analysis of two-component mixtures.

    Science.gov (United States)

    Hund, E; Massart, D L; Smeyers-Verbeke, J

    1999-10-01

    The H-point standard additions method (HPSAM) and two versions of the generalized H-point standard additions method (GHPSAM) are evaluated for the UV-analysis of two-component mixtures. Synthetic mixtures of anhydrous caffeine and phenazone as well as of atovaquone and proguanil hydrochloride were used. Furthermore, the method was applied to pharmaceutical formulations that contain these compounds as active drug substances. This paper shows both the difficulties that are related to the methods and the conditions by which acceptable results can be obtained.

  14. Mathematical Modelling of the Evaporating Liquid Films on the Basis of the Generalized Interface Conditions

    Directory of Open Access Journals (Sweden)

    Goncharova Olga

    2016-01-01

    Full Text Available The two-dimensional films, flowing down an inclined, non-uniformly heated substrate are studied. The results contain the new mathematical models developed with the help of the long-wave approximation of the Navier-Stokes and heat transfer equations or Oberbeck-Boussinesq equations in the case, when the generalized conditions are formulated at thermocapillary interface. The evolution equations for the film thickness include the effects of gravity, viscosity, capillarity, thermocapillarity, additional stress effects and evaporation.

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

    Science.gov (United States)

    Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens

    2016-01-01

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

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

    Science.gov (United States)

    Baeder, Desiree Y; Yu, Guozhi; Hozé, Nathanaël; Rolff, Jens; Regoes, Roland R

    2016-05-26

    Antimicrobial peptides (AMPs) and antibiotics reduce the net growth rate of bacterial populations they target. It is relevant to understand if effects of multiple antimicrobials are synergistic or antagonistic, in particular for AMP responses, because naturally occurring responses involve multiple AMPs. There are several competing proposals describing how multiple types of antimicrobials add up when applied in combination, such as Loewe additivity or Bliss independence. These additivity terms are defined ad hoc from abstract principles explaining the supposed interaction between the antimicrobials. Here, we link these ad hoc combination terms to a mathematical model that represents the dynamics of antimicrobial molecules hitting targets on bacterial cells. In this multi-hit model, bacteria are killed when a certain number of targets are hit by antimicrobials. Using this bottom-up approach reveals that Bliss independence should be the model of choice if no interaction between antimicrobial molecules is expected. Loewe additivity, on the other hand, describes scenarios in which antimicrobials affect the same components of the cell, i.e. are not acting independently. While our approach idealizes the dynamics of antimicrobials, it provides a conceptual underpinning of the additivity terms. The choice of the additivity term is essential to determine synergy or antagonism of antimicrobials.This article is part of the themed issue 'Evolutionary ecology of arthropod antimicrobial peptides'. © 2016 The Author(s).

  17. Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

    Science.gov (United States)

    Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

    2014-04-02

    The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method.

  18. Additive quark model and double scattering of pions and protons in deuterium

    International Nuclear Information System (INIS)

    Bialas, A.; Czyz, W.; Kisielewska, D.

    1981-01-01

    It is shown that the additive quark model is compatible with the data on double scattering of pions and protons in deuterium. The cross-section for interaction of the hadrons created in the first collision with the second nucleon of the target is determined to be 20-25 mb. (author)

  19. Declarations pursuant to the Articles 2 and 3 of the Model Additional Protocol

    International Nuclear Information System (INIS)

    Fernandez Moreno, Sonia

    2001-01-01

    Articles 2 and 3 of the Model Additional Protocol specify the content and the time limits of the information to be provided by the States into the framework of the Safeguard Agreements. To standardize the presentation of this information the IAEA has prepared guidelines for the preparation of the documents. A detailed explanation of the guidelines is given in the paper

  20. Entropy-optimal weight constraint elicitation with additive multi-attribute utility models

    NARCIS (Netherlands)

    Valkenhoef , van Gert; Tervonen, Tommi

    2016-01-01

    We consider the elicitation of incomplete preference information for the additive utility model in terms of linear constraints on the weights. Eliciting incomplete preferences using holistic pair-wise judgments is convenient for the decision maker, but selecting the best pair-wise comparison is

  1. Do downscaled general circulation models reliably simulate historical climatic conditions?

    Science.gov (United States)

    Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

    2018-01-01

    The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

  2. Perception Gaps on Food Additives among Various Groups in Korea: Food Experts, Teachers, Nutrition Teachers, Nongovernmental Organization Members, and General Consumers.

    Science.gov (United States)

    Kang, Hee-Jin; Kim, Suna; Lee, Gunyoung; Lim, Ho Soo; Yun, Sang Soon; Kim, Jeong-Weon

    2017-06-01

    The purpose of this study was to determine the perceptions and information needs of food experts, teachers, nutrition teachers, members of nongovernmental organizations, and general consumers concerning food additives. Questions in a survey format included perceptions, information needs, and preferred communication channels. The survey was conducted both off-line and on-line via e-mail and Google Drive in March 2015. The results indicated that most Korean consumers are concerned about the safety of using food additives in processed foods and do not recognize these additives as safe and useful materials as part of a modern diet. We also identified perception gaps among different groups regarding food additives. Nutrition teachers and members of nongovernmental organizations in Korea appeared to have a biased perception of food additives, which may cause general consumers to have a negative perception of food additives. The group of food experts did not have this bias. Governmental institutions must overcome the low confidence levels of various groups as an information provider about food additives. Based on the findings in this study, it will be possible to develop a strategy for risk communication about food additives for each group.

  3. Does the model of additive effect in placebo research still hold true? A narrative review

    Science.gov (United States)

    Berger, Bettina; Weger, Ulrich; Heusser, Peter

    2017-01-01

    Personalised and contextualised care has been turned into a major demand by people involved in healthcare suggesting to move toward person-centred medicine. The assessment of person-centred medicine can be most effectively achieved if treatments are investigated using ‘with versus without’ person-centredness or integrative study designs. However, this assumes that the components of an integrative or person-centred intervention have an additive relationship to produce the total effect. Beecher’s model of additivity assumes an additive relation between placebo and drug effects and is thus presenting an arithmetic summation. So far, no review has been carried out assessing the validity of the additive model, which is to be questioned and more closely investigated in this review. Initial searches for primary studies were undertaken in July 2016 using Pubmed and Google Scholar. In order to find matching publications of similar magnitude for the comparison part of this review, corresponding matches for all included reviews were sought. A total of 22 reviews and 3 clinical and experimental studies fulfilled the inclusion criteria. The results pointed to the following factors actively questioning the additive model: interactions of various effects, trial design, conditioning, context effects and factors, neurobiological factors, mechanism of action, statistical factors, intervention-specific factors (alcohol, caffeine), side-effects and type of intervention. All but one of the closely assessed publications was questioning the additive model. A closer examination of study design is necessary. An attempt in a more systematic approach geared towards solutions could be a suggestion for future research in this field. PMID:28321318

  4. About the Properties of a Modified Generalized Beverton-Holt Equation in Ecology Models

    Directory of Open Access Journals (Sweden)

    M. De La Sen

    2008-01-01

    Full Text Available This paper is devoted to the study of a generalized modified version of the well-known Beverton-Holt equation in ecology. The proposed model describes the population evolution of some species in a certain habitat driven by six parametrical sequences, namely, the intrinsic growth rate (associated with the reproduction capability, the degree of sympathy of the species with the habitat (described by a so-called environment carrying capacity, a penalty term to deal with overpopulation levels, the harvesting (fishing or hunting regulatory quota, or related to use of pesticides when fighting damaging plagues, and the independent consumption which basically quantifies predation. The independent consumption is considered as a part of a more general additive disturbance which also potentially includes another extra additive disturbance term which might be attributed to net migration from or to the habitat or modeling measuring errors. Both potential contributions are included for generalization purposes in the proposed modified generalized Beverton-Holt equation. The properties of stability and boundedness of the solution sequences, equilibrium points of the stationary model, and the existence of oscillatory solution sequences are investigated. A numerical example for a population of aphids is investigated with the theoretical tools developed in the paper.

  5. Modeling the use of sulfate additives for potassium chloride destruction in biomass combustion

    DEFF Research Database (Denmark)

    Wu, Hao; Grell, Morten Nedergaard; Jespersen, Jacob Boll

    2013-01-01

    Potassium chloride, KCl, formed from biomass combustion may lead to ash deposition and corrosion problems in boilers. Sulfates are effective additives for converting KCl to the less harmful K2SO4. In the present study, the decomposition of ammonium sulfate, aluminum sulfate and ferric sulfate...... of ammonium sulfate addition and ferric sulfation addition compared favorably with the experimental results. However, the model for aluminum sulfate addition under-predicted significantly the high sulfation degree of KCl observed in the experiments, possibly because of an under-estimation of the decomposition...... rate of aluminum. Under the boiler conditions of the present work, the simulation results suggested that the desirable temperature for the ferric sulfate injection was around 950-900oC, whereas for ammonium sulfate the preferable injection temperature was below 800oC....

  6. Formation and reduction of carcinogenic furan in various model systems containing food additives.

    Science.gov (United States)

    Kim, Jin-Sil; Her, Jae-Young; Lee, Kwang-Geun

    2015-12-15

    The aim of this study was to analyse and reduce furan in various model systems. Furan model systems consisting of monosaccharides (0.5M glucose and ribose), amino acids (0.5M alanine and serine) and/or 1.0M ascorbic acid were heated at 121°C for 25 min. The effects of food additives (each 0.1M) such as metal ions (iron sulphate, magnesium sulphate, zinc sulphate and calcium sulphate), antioxidants (BHT and BHA), and sodium sulphite on the formation of furan were measured. The level of furan formed in the model systems was 6.8-527.3 ng/ml. The level of furan in the model systems of glucose/serine and glucose/alanine increased 7-674% when food additives were added. In contrast, the level of furan decreased by 18-51% in the Maillard reaction model systems that included ribose and alanine/serine with food additives except zinc sulphate. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing

    Science.gov (United States)

    Lian, Yanping; Lin, Stephen; Yan, Wentao; Liu, Wing Kam; Wagner, Gregory J.

    2018-01-01

    In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.

  8. A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing

    Science.gov (United States)

    Lian, Yanping; Lin, Stephen; Yan, Wentao; Liu, Wing Kam; Wagner, Gregory J.

    2018-05-01

    In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.

  9. NB-PLC channel modelling with cyclostationary noise addition & OFDM implementation for smart grid

    Science.gov (United States)

    Thomas, Togis; Gupta, K. K.

    2016-03-01

    Power line communication (PLC) technology can be a viable solution for the future ubiquitous networks because it provides a cheaper alternative to other wired technology currently being used for communication. In smart grid Power Line Communication (PLC) is used to support communication with low rate on low voltage (LV) distribution network. In this paper, we propose the channel modelling of narrowband (NB) PLC in the frequency range 5 KHz to 500 KHz by using ABCD parameter with cyclostationary noise addition. Behaviour of the channel was studied by the addition of 11KV/230V transformer, by varying load location and load. Bit error rate (BER) Vs signal to noise ratio SNR) was plotted for the proposed model by employing OFDM. Our simulation results based on the proposed channel model show an acceptable performance in terms of bit error rate versus signal to noise ratio, which enables communication required for smart grid applications.

  10. A generalized model for estimating the energy density of invertebrates

    Science.gov (United States)

    James, Daniel A.; Csargo, Isak J.; Von Eschen, Aaron; Thul, Megan D.; Baker, James M.; Hayer, Cari-Ann; Howell, Jessica; Krause, Jacob; Letvin, Alex; Chipps, Steven R.

    2012-01-01

    Invertebrate energy density (ED) values are traditionally measured using bomb calorimetry. However, many researchers rely on a few published literature sources to obtain ED values because of time and sampling constraints on measuring ED with bomb calorimetry. Literature values often do not account for spatial or temporal variability associated with invertebrate ED. Thus, these values can be unreliable for use in models and other ecological applications. We evaluated the generality of the relationship between invertebrate ED and proportion of dry-to-wet mass (pDM). We then developed and tested a regression model to predict ED from pDM based on a taxonomically, spatially, and temporally diverse sample of invertebrates representing 28 orders in aquatic (freshwater, estuarine, and marine) and terrestrial (temperate and arid) habitats from 4 continents and 2 oceans. Samples included invertebrates collected in all seasons over the last 19 y. Evaluation of these data revealed a significant relationship between ED and pDM (r2  =  0.96, p cost savings compared to traditional bomb calorimetry approaches. This model should prove useful for a wide range of ecological studies because it is unaffected by taxonomic, seasonal, or spatial variability.

  11. General relativity cosmological models without the big bang

    International Nuclear Information System (INIS)

    Rosen, N.

    1985-01-01

    Attention is given to the so-called standard model of the universe in the framework of the general theory of relativity. This model is taken to be homogeneous and isotropic and filled with an ideal fluid characterized by a density and a pressure. Taking into consideration, however, the assumption that the universe began in a singular state, it is found hard to understand why the universe is so nearly homogeneous and isotropic at present for a singularity represents a breakdown of physical laws, and the initial singularity cannot, therefore, predetermine the subsequent symmetries of the universe. The present investigation has the objective to find a way of avoiding this initial singularity, i.e., to look for a cosmological model without the big bang. The idea is proposed that there exists a limiting density of matter of the order of magnitude of the Planck density, and that this was the density of matter at the moment at which the universe began to expand

  12. Density prediction and dimensionality reduction of mid-term electricity demand in China: A new semiparametric-based additive model

    International Nuclear Information System (INIS)

    Shao, Zhen; Yang, Shan-Lin; Gao, Fei

    2014-01-01

    Highlights: • A new stationary time series smoothing-based semiparametric model is established. • A novel semiparametric additive model based on piecewise smooth is proposed. • We model the uncertainty of data distribution for mid-term electricity forecasting. • We provide efficient long horizon simulation and extraction for external variables. • We provide stable and accurate density predictions for mid-term electricity demand. - Abstract: Accurate mid-term electricity demand forecasting is critical for efficient electric planning, budgeting and operating decisions. Mid-term electricity demand forecasting is notoriously complicated, since the demand is subject to a range of external drivers, such as climate change, economic development, which will exhibit monthly, seasonal, and annual complex variations. Conventional models are based on the assumption that original data is stable and normally distributed, which is generally insignificant in explaining actual demand pattern. This paper proposes a new semiparametric additive model that, in addition to considering the uncertainty of the data distribution, includes practical discussions covering the applications of the external variables. To effectively detach the multi-dimensional volatility of mid-term demand, a novel piecewise smooth method which allows reduction of the data dimensionality is developed. Besides, a semi-parametric procedure that makes use of bootstrap algorithm for density forecast and model estimation is presented. Two typical cases in China are presented to verify the effectiveness of the proposed methodology. The results suggest that both meteorological and economic variables play a critical role in mid-term electricity consumption prediction in China, while the extracted economic factor is adequate to reveal the potentially complex relationship between electricity consumption and economic fluctuation. Overall, the proposed model can be easily applied to mid-term demand forecasting, and

  13. Extending the linear model with R generalized linear, mixed effects and nonparametric regression models

    CERN Document Server

    Faraway, Julian J

    2005-01-01

    Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway''s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author''s treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the ...

  14. 41 CFR 102-38.335 - Is there any additional personal property sales information that we must submit to the General...

    Science.gov (United States)

    2010-07-01

    ... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Is there any additional personal property sales information that we must submit to the General Services Administration? 102-38.335 Section 102-38.335 Public Contracts and Property Management Federal Property Management Regulations System...

  15. A general Bayes weibull inference model for accelerated life testing

    International Nuclear Information System (INIS)

    Dorp, J. Rene van; Mazzuchi, Thomas A.

    2005-01-01

    This article presents the development of a general Bayes inference model for accelerated life testing. The failure times at a constant stress level are assumed to belong to a Weibull distribution, but the specification of strict adherence to a parametric time-transformation function is not required. Rather, prior information is used to indirectly define a multivariate prior distribution for the scale parameters at the various stress levels and the common shape parameter. Using the approach, Bayes point estimates as well as probability statements for use-stress (and accelerated) life parameters may be inferred from a host of testing scenarios. The inference procedure accommodates both the interval data sampling strategy and type I censored sampling strategy for the collection of ALT test data. The inference procedure uses the well-known MCMC (Markov Chain Monte Carlo) methods to derive posterior approximations. The approach is illustrated with an example

  16. Generalized Swept Mid-structure for Polygonal Models

    KAUST Repository

    Martin, Tobias; Chen, Guoning; Musuvathy, Suraj; Cohen, Elaine; Hansen, Charles

    2012-01-01

    We introduce a novel mid-structure called the generalized swept mid-structure (GSM) of a closed polygonal shape, and a framework to compute it. The GSM contains both curve and surface elements and has consistent sheet-by-sheet topology, versus triangle-by-triangle topology produced by other mid-structure methods. To obtain this structure, a harmonic function, defined on the volume that is enclosed by the surface, is used to decompose the volume into a set of slices. A technique for computing the 1D mid-structures of these slices is introduced. The mid-structures of adjacent slices are then iteratively matched through a boundary similarity computation and triangulated to form the GSM. This structure respects the topology of the input surface model is a hybrid mid-structure representation. The construction and topology of the GSM allows for local and global simplification, used in further applications such as parameterization, volumetric mesh generation and medical applications.

  17. Generalized Swept Mid-structure for Polygonal Models

    KAUST Repository

    Martin, Tobias

    2012-05-01

    We introduce a novel mid-structure called the generalized swept mid-structure (GSM) of a closed polygonal shape, and a framework to compute it. The GSM contains both curve and surface elements and has consistent sheet-by-sheet topology, versus triangle-by-triangle topology produced by other mid-structure methods. To obtain this structure, a harmonic function, defined on the volume that is enclosed by the surface, is used to decompose the volume into a set of slices. A technique for computing the 1D mid-structures of these slices is introduced. The mid-structures of adjacent slices are then iteratively matched through a boundary similarity computation and triangulated to form the GSM. This structure respects the topology of the input surface model is a hybrid mid-structure representation. The construction and topology of the GSM allows for local and global simplification, used in further applications such as parameterization, volumetric mesh generation and medical applications.

  18. Effect of niobium addition to the Fe-17% Cr alloy on the resistance to generalized corrosion in sulfuric acid

    International Nuclear Information System (INIS)

    Alonso, Neusa; Wolynec, Stephan

    1992-01-01

    The aim of present work was to investigate the influence of Nb upon the corrosion resistance to o.5 M H2 SO 4 cf 17% Cr ferritic stainless steels, to which it was added in amounts larger than those necessary for the stabilization of interstitial elements. The performance of Fe-17% Cr alloys containing 0.31%, 0.58%, 1.,62% Nb was compared to that of two other Fe-17% Cr alloys containing 0.31%, 0.58% and 1.62% Nb was compared to that of two other Fe-175 Cr alloys, one without additions and another containing 0.93% Nb. Through weight and electrochemical measurements and through morphologic examination of corroded surface it was found that in o.5 M H 2 SO 4 solution the corrosion of these alloys, with the exception of that containing molybdenum, products in two different stages. In the first stage (up to about 60 minutes the rate practically does not change with time, the lower rates being displayed by alloys containing larger mounts of Nb. In the second stage (for immersion times larger than 60 minutes) the corrosion rate increases with time. the corrosion rate of Mo containing alloy is constant with time so that for longer immersion times this alloy becomes the most resistant. The first stage was discussed in terms of electromechanical properties of Nb and its ability to combine with steel impurities, while the second stage was considered as affected by corrosion products formed on the surface of these alloys after certain time of immersion. (author)

  19. The potential application of European market research data in dietary exposure modelling of food additives.

    Science.gov (United States)

    Tennant, David Robin; Bruyninckx, Chris

    2018-03-01

    Consumer exposure assessments for food additives are incomplete without information about the proportions of foods in each authorised category that contain the additive. Such information has been difficult to obtain but the Mintel Global New Products Database (GNPD) provides information about product launches across Europe over the past 20 years. These data can be searched to identify products with specific additives listed on product labels and the numbers compared with total product launches for food and drink categories in the same database to determine the frequency of occurrence. There are uncertainties associated with the data but these can be managed by adopting a cautious and conservative approach. GNPD data can be mapped with authorised food categories and with food descriptions used in the EFSA Comprehensive European Food Consumption Surveys Database for exposure modelling. The data, when presented as percent occurrence, could be incorporated into the EFSA ANS Panel's 'brand-loyal/non-brand loyal exposure model in a quantitative way. Case studies of preservative, antioxidant, colour and sweetener additives showed that the impact of including occurrence data is greatest in the non-brand loyal scenario. Recommendations for future research include identifying occurrence data for alcoholic beverages, linking regulatory food codes, FoodEx and GNPD product descriptions, developing the use of occurrence data for carry-over foods and improving understanding of brand loyalty in consumer exposure models.

  20. Efectivity of Additive Spline for Partial Least Square Method in Regression Model Estimation

    Directory of Open Access Journals (Sweden)

    Ahmad Bilfarsah

    2005-04-01

    Full Text Available Additive Spline of Partial Least Square method (ASPL as one generalization of Partial Least Square (PLS method. ASPLS method can be acommodation to non linear and multicollinearity case of predictor variables. As a principle, The ASPLS method approach is cahracterized by two idea. The first is to used parametric transformations of predictors by spline function; the second is to make ASPLS components mutually uncorrelated, to preserve properties of the linear PLS components. The performance of ASPLS compared with other PLS method is illustrated with the fisher economic application especially the tuna fish production.

  1. Updated Results from the Michigan Titan Thermospheric General Circulation Model (TTGCM)

    Science.gov (United States)

    Bell, J. M.; Bougher, S. W.; de Lahaye, V.; Waite, J. H.; Ridley, A.

    2006-05-01

    This paper presents updated results from the Michigan Titan Thermospheric General Circulation Model (TTGCM) that was recently unveiled in operational form (Bell et al 2005 Spring AGU). Since then, we have incorporated a suite of chemical reactions for the major neutral constituents in Titan's upper atmosphere (N2, CH4). Additionally, some selected minor neutral constituents and major ionic species are also supported in the framework. At this time, HCN, which remains one of the critical thermally active species in the upper atmosphere, remains specified at all altitudes, utilizing profiles derived from recent Cassini-Huygen's measurements. In addition to these improvements, a parallel effort is underway to develop a non-hydrostatic Titan Thermospheric General Circulation Model for further comparisons. In this work, we emphasize the impacts of self-consistent chemistry on the results of the updated TTGCM relative to its frozen chemistry predecessor. Meanwhile, the thermosphere's thermodynamics remains determined by the interplay of solar EUV forcing and HCN rotational cooling, which is calculated by a full line- by-line radiative transfer routine along the lines of Yelle (1991) and Mueller-Wodarg (2000, 2002). In addition to these primary drivers, a treatment of magnetospheric heating is further tested. The model's results will be compared with both the Cassini INMS data and the model of Mueller-Wodarg (2000,2002).

  2. Testing for constant nonparametric effects in general semiparametric regression models with interactions

    KAUST Repository

    Wei, Jiawei

    2011-07-01

    We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work was originally motivated by a unique testing problem in genetic epidemiology (Chatterjee, et al., 2006) that involved a typical generalized linear model but with an additional term reminiscent of the Tukey one-degree-of-freedom formulation, and their interest was in testing for main effects of the genetic variables, while gaining statistical power by allowing for a possible interaction between genes and the environment. Later work (Maity, et al., 2009) involved the possibility of modeling the environmental variable nonparametrically, but they focused on whether there was a parametric main effect for the genetic variables. In this paper, we consider the complementary problem, where the interest is in testing for the main effect of the nonparametrically modeled environmental variable. We derive a generalized likelihood ratio test for this hypothesis, show how to implement it, and provide evidence that our method can improve statistical power when compared to standard partially linear models with main effects only. We use the method for the primary purpose of analyzing data from a case-control study of colorectal adenoma.

  3. Bayes estimation of the general hazard rate model

    International Nuclear Information System (INIS)

    Sarhan, A.

    1999-01-01

    In reliability theory and life testing models, the life time distributions are often specified by choosing a relevant hazard rate function. Here a general hazard rate function h(t)=a+bt c-1 , where c, a, b are constants greater than zero, is considered. The parameter c is assumed to be known. The Bayes estimators of (a,b) based on the data of type II/item-censored testing without replacement are obtained. A large simulation study using Monte Carlo Method is done to compare the performance of Bayes with regression estimators of (a,b). The criterion for comparison is made based on the Bayes risk associated with the respective estimator. Also, the influence of the number of failed items on the accuracy of the estimators (Bayes and regression) is investigated. Estimations for the parameters (a,b) of the linearly increasing hazard rate model h(t)=a+bt, where a, b are greater than zero, can be obtained as the special case, letting c=2

  4. Generalized Functional Linear Models With Semiparametric Single-Index Interactions

    KAUST Repository

    Li, Yehua

    2010-06-01

    We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.

  5. CHAIN-WISE GENERALIZATION OF ROAD NETWORKS USING MODEL SELECTION

    Directory of Open Access Journals (Sweden)

    D. Bulatov

    2017-05-01

    Full Text Available Streets are essential entities of urban terrain and their automatized extraction from airborne sensor data is cumbersome because of a complex interplay of geometric, topological and semantic aspects. Given a binary image, representing the road class, centerlines of road segments are extracted by means of skeletonization. The focus of this paper lies in a well-reasoned representation of these segments by means of geometric primitives, such as straight line segments as well as circle and ellipse arcs. We propose the fusion of raw segments based on similarity criteria; the output of this process are the so-called chains which better match to the intuitive perception of what a street is. Further, we propose a two-step approach for chain-wise generalization. First, the chain is pre-segmented using circlePeucker and finally, model selection is used to decide whether two neighboring segments should be fused to a new geometric entity. Thereby, we consider both variance-covariance analysis of residuals and model complexity. The results on a complex data-set with many traffic roundabouts indicate the benefits of the proposed procedure.

  6. Cognitive performance modeling based on general systems performance theory.

    Science.gov (United States)

    Kondraske, George V

    2010-01-01

    General Systems Performance Theory (GSPT) was initially motivated by problems associated with quantifying different aspects of human performance. It has proved to be invaluable for measurement development and understanding quantitative relationships between human subsystem capacities and performance in complex tasks. It is now desired to bring focus to the application of GSPT to modeling of cognitive system performance. Previous studies involving two complex tasks (i.e., driving and performing laparoscopic surgery) and incorporating measures that are clearly related to cognitive performance (information processing speed and short-term memory capacity) were revisited. A GSPT-derived method of task analysis and performance prediction termed Nonlinear Causal Resource Analysis (NCRA) was employed to determine the demand on basic cognitive performance resources required to support different levels of complex task performance. This approach is presented as a means to determine a cognitive workload profile and the subsequent computation of a single number measure of cognitive workload (CW). Computation of CW may be a viable alternative to measuring it. Various possible "more basic" performance resources that contribute to cognitive system performance are discussed. It is concluded from this preliminary exploration that a GSPT-based approach can contribute to defining cognitive performance models that are useful for both individual subjects and specific groups (e.g., military pilots).

  7. Critical rotation of general-relativistic polytropic models revisited

    Science.gov (United States)

    Geroyannis, V.; Karageorgopoulos, V.

    2013-09-01

    We develop a perturbation method for computing the critical rotational parameter as a function of the equatorial radius of a rigidly rotating polytropic model in the "post-Newtonia approximation" (PNA). We treat our models as "initial value problems" (IVP) of ordinary differential equations in the complex plane. The computations are carried out by the code dcrkf54.f95 (Geroyannis and Valvi 2012 [P1]; modified Runge-Kutta-Fehlberg code of fourth and fifth order for solving initial value problems in the complex plane). Such a complex-plane treatment removes the syndromes appearing in this particular family of IVPs (see e.g. P1, Sec. 3) and allows continuation of the numerical integrations beyond the surface of the star. Thus all the required values of the Lane-Emden function(s) in the post-Newtonian approximation are calculated by interpolation (so avoiding any extrapolation). An interesting point is that, in our computations, we take into account the complete correction due to the gravitational term, and this issue is a remarkable difference compared to the classical PNA. We solve the generalized density as a function of the equatorial radius and find the critical rotational parameter. Our computations are extended to certain other physical characteristics (like mass, angular momentum, rotational kinetic energy, etc). We find that our method yields results comparable with those of other reliable methods. REFERENCE: V.S. Geroyannis and F.N. Valvi 2012, International Journal of Modern Physics C, 23, No 5, 1250038:1-15.

  8. Generalized Functional Linear Models With Semiparametric Single-Index Interactions

    KAUST Repository

    Li, Yehua; Wang, Naisyin; Carroll, Raymond J.

    2010-01-01

    We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.

  9. Prognostic cloud water in the Los Alamos general circulation model

    International Nuclear Information System (INIS)

    Kristjansson, J.E.; Kao, C.Y.J.

    1993-01-01

    Most of today's general circulation models (GCMS) have a greatly simplified treatment of condensation and clouds. Recent observational studies of the earth's radiation budget have suggested cloud-related feedback mechanisms to be of tremendous importance for the issue of global change. Thus, there has arisen an urgent need for improvements in the treatment of clouds in GCMS, especially as the clouds relate to radiation. In the present paper, we investigate the effects of introducing pregnostic cloud water into the Los Alamos GCM. The cloud water field, produced by both stratiform and convective condensation, is subject to 3-dimensional advection and vertical diffusion. The cloud water enters the radiation calculations through the long wave emissivity calculations. Results from several sensitivity simulations show that realistic cloud water and precipitation fields can be obtained with the applied method. Comparisons with observations show that the most realistic results are obtained when more sophisticated schemes for moist convection are introduced at the same time. The model's cold bias is reduced and the zonal winds become stronger, due to more realistic tropical convection

  10. Prognostic cloud water in the Los Alamos general circulation model

    International Nuclear Information System (INIS)

    Kristjansson, J.E.; Kao, C.Y.J.

    1994-01-01

    Most of today's general circulation models (GCMs) have a greatly simplified treatment of condensation and clouds. Recent observational studies of the earth's radiation budget have suggested cloud-related feedback mechanisms to be of tremendous importance for the issue of global change. Thus, an urgent need for improvements in the treatment of clouds in GCMs has arisen, especially as the clouds relate to radiation. In this paper, we investigate the effects of introducing prognostic cloud water into the Los Alamos GCM. The cloud water field, produced by both stratiform and convective condensation, is subject to 3-dimensional advection and vertical diffusion. The cloud water enters the radiation calculations through the longwave emissivity calculations. Results from several sensitivity simulations show that realistic water and precipitation fields can be obtained with the applied method. Comparisons with observations show that the most realistic results are obtained when more sophisticated schemes for moist convection are introduced at the same time. The model's cold bias is reduced and the zonal winds becomes stronger because of more realistic tropical convection

  11. Modeling of sulfation of potassium chloride by ferric sulfate addition during grate-firing of biomass

    DEFF Research Database (Denmark)

    Wu, Hao; Jespersen, Jacob Boll; Aho, Martti

    2013-01-01

    Potassium chloride, KCl, formed from critical ash-forming elements released during combustion may lead to severe ash deposition and corrosion problems in biomass-fired boilers. Ferric sulfate, Fe2(SO4)3 is an effective additive, which produces sulfur oxides (SO2 and SO3) to convert KCl to the less...... harmful K2SO4. In the present study the decomposition of ferric sulfate is studied in a fast-heating rate thermogravimetric analyzer (TGA), and a kinetic model is proposed to describe the decomposition process. The yields of SO2 and SO3 from ferric sulfate decomposition are investigated in a laboratory......-scale tube reactor. It is revealed that approximately 40% of the sulfur is released as SO3, the remaining fraction being released as SO2. The proposed decomposition model of ferric sulfate is combined with a detailed gas phase kinetic model of KCl sulfation, and a simplified model of K2SO4 condensation...

  12. ZVI Addition in Continuous Anaerobic Digestion Systems Dramatically Decreases P Recovery Potential: Dynamic Modelling

    DEFF Research Database (Denmark)

    Puyol, D.; Flores Alsina, Xavier; Segura, Y.

    2017-01-01

    The objective of this study is to show the preliminary results of a (dynamic) mathematical model describing the effects of zero valent iron (ZVI) addition during the anaerobic digestion of waste activated sludge from wastewater treatment systems. A modified version of the Anaerobic Digestion Model...... No. 1 (ADM1) upgraded with an improved physico-chemical description, ZVI corrosion, propionate uptake enhancement and multiple mineral precipitation is used as a modelling platform. The proposed approach is tested against two case studies which correspond to two lab scale anaerobic digesters (AD2, AD....... Simulations demonstrate that the model is capable to satisfactorily reproduce the dynamics of hydrolysis, acetogenesis, acidogenesis, nutrient release, pH and methanogenesis in the control anaerobic digester (AD1). This study also evidences the enhancement of methane production by the influence of ZVI...

  13. In silico modeling of structural and porosity properties of additive manufactured implants for regenerative medicine.

    Science.gov (United States)

    Brünler, Ronny; Aibibu, Dilbar; Wöltje, Michael; Anthofer, Anna-Maria; Cherif, Chokri

    2017-07-01

    Additive manufacturing technologies are a promising technology towards patient-specific implants for applications in regenerative medicine. The Net-Shape-Nonwoven technology is used to manufacture structures from short fibers with interconnected pores and large functional surfaces that are predestined for cell adhesion and growth. The present study reports on a modeling approach with a particular focus on the specific structural properties. The overall porosities and mean pore-sizes of the digital models are simulated according to liquid-displacement porosity in a tool implemented in the modeling software. This allows adjusting the process parameters fiber length and fiber diameter to generate biomimetic structures with pore-sizes adapted to the requirements of the tissue that is to be replaced. Modeling the structural and porosity properties of scaffolds and implants leads to an efficient use of the processed biomaterials as the trial-and-error method is avoided. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Boosted structured additive regression for Escherichia coli fed-batch fermentation modeling.

    Science.gov (United States)

    Melcher, Michael; Scharl, Theresa; Luchner, Markus; Striedner, Gerald; Leisch, Friedrich

    2017-02-01

    The quality of biopharmaceuticals and patients' safety are of highest priority and there are tremendous efforts to replace empirical production process designs by knowledge-based approaches. Main challenge in this context is that real-time access to process variables related to product quality and quantity is severely limited. To date comprehensive on- and offline monitoring platforms are used to generate process data sets that allow for development of mechanistic and/or data driven models for real-time prediction of these important quantities. Ultimate goal is to implement model based feed-back control loops that facilitate online control of product quality. In this contribution, we explore structured additive regression (STAR) models in combination with boosting as a variable selection tool for modeling the cell dry mass, product concentration, and optical density on the basis of online available process variables and two-dimensional fluorescence spectroscopic data. STAR models are powerful extensions of linear models allowing for inclusion of smooth effects or interactions between predictors. Boosting constructs the final model in a stepwise manner and provides a variable importance measure via predictor selection frequencies. Our results show that the cell dry mass can be modeled with a relative error of about ±3%, the optical density with ±6%, the soluble protein with ±16%, and the insoluble product with an accuracy of ±12%. Biotechnol. Bioeng. 2017;114: 321-334. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  15. A model for additive transport in metal halide lamps containing mercury and dysprosium tri-iodide

    International Nuclear Information System (INIS)

    Beks, M L; Haverlag, M; Mullen, J J A M van der

    2008-01-01

    The distribution of additives in a metal halide lamp is examined through numerical modelling. A model for a lamp containing sodium iodide additives has been modified to study a discharge containing dysprosium tri-iodide salts. To study the complex chemistry the method of Gibbs minimization is used to decide which species have to be taken into account and to fill lookup tables with the chemical composition at different combinations of elemental abundance, lamp pressure and temperature. The results from the model with dysprosium additives were compared with earlier results from the lamp containing sodium additives and a simulation of a pure mercury lamp. It was found that radial segregation creates the conditions required for axial segregation. Radial segregation occurs due to the unequal diffusion of atoms and molecules. Under the right conditions convection currents in the lamp can cause axial demixing. These conditions depend on the ratio of axial convection and radial diffusion as expressed by the Peclet number. At a Peclet number of unity axial segregation is most pronounced. At low Peclet numbers radial segregation is at its worst, while axial segregation is not present. At large Peclet numbers the discharge becomes homogeneously mixed. The degree of axial segregation at a Peclet number of unity depends on the temperature at which the additive under consideration fully dissociates. If the molecules dissociate very close to the walls no molecules are transported by the convective currents in the lamp, and hence axial segregation is limited. If they dissociate further away from the walls in the area where the downward convective currents are strongest, more axial segregation is observed

  16. The Additive Risk Model for Estimation of Effect of Haplotype Match in BMT Studies

    DEFF Research Database (Denmark)

    Scheike, Thomas; Martinussen, T; Zhang, MJ

    2011-01-01

    leads to a missing data problem. We show how Aalen's additive risk model can be applied in this setting with the benefit that the time-varying haplomatch effect can be easily studied. This problem has not been considered before, and the standard approach where one would use the expected-maximization (EM......) algorithm cannot be applied for this model because the likelihood is hard to evaluate without additional assumptions. We suggest an approach based on multivariate estimating equations that are solved using a recursive structure. This approach leads to an estimator where the large sample properties can...... be developed using product-integration theory. Small sample properties are investigated using simulations in a setting that mimics the motivating haplomatch problem....

  17. In-Situ monitoring and modeling of metal additive manufacturing powder bed fusion

    Science.gov (United States)

    Alldredge, Jacob; Slotwinski, John; Storck, Steven; Kim, Sam; Goldberg, Arnold; Montalbano, Timothy

    2018-04-01

    One of the major challenges in metal additive manufacturing is developing in-situ sensing and feedback control capabilities to eliminate build errors and allow qualified part creation without the need for costly and destructive external testing. Previously, many groups have focused on high fidelity numerical modeling and true temperature thermal imaging systems. These approaches require large computational resources or costly hardware that requires complex calibration and are difficult to integrate into commercial systems. In addition, due to the rapid change in the state of the material as well as its surface properties, getting true temperature is complicated and difficult. Here, we describe a different approach where we implement a low cost thermal imaging solution allowing for relative temperature measurements sufficient for detecting unwanted process variability. We match this with a faster than real time qualitative model that allows the process to be rapidly modeled during the build. The hope is to combine these two, allowing for the detection of anomalies in real time, enabling corrective action to potentially be taken, or parts to be stopped immediately after the error, saving material and time. Here we describe our sensor setup, its costs and abilities. We also show the ability to detect in real time unwanted process deviations. We also show that the output of our high speed model agrees qualitatively with experimental results. These results lay the groundwork for our vision of an integrated feedback and control scheme that combines low cost, easy to use sensors and fast modeling for process deviation monitoring.

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

    Science.gov (United States)

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

    2015-05-01

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

  19. Design and implementation of a generalized laboratory data model

    Directory of Open Access Journals (Sweden)

    Nhan Mike

    2007-09-01

    Full Text Available Abstract Background Investigators in the biological sciences continue to exploit laboratory automation methods and have dramatically increased the rates at which they can generate data. In many environments, the methods themselves also evolve in a rapid and fluid manner. These observations point to the importance of robust information management systems in the modern laboratory. Designing and implementing such systems is non-trivial and it appears that in many cases a database project ultimately proves unserviceable. Results We describe a general modeling framework for laboratory data and its implementation as an information management system. The model utilizes several abstraction techniques, focusing especially on the concepts of inheritance and meta-data. Traditional approaches commingle event-oriented data with regular entity data in ad hoc ways. Instead, we define distinct regular entity and event schemas, but fully integrate these via a standardized interface. The design allows straightforward definition of a "processing pipeline" as a sequence of events, obviating the need for separate workflow management systems. A layer above the event-oriented schema integrates events into a workflow by defining "processing directives", which act as automated project managers of items in the system. Directives can be added or modified in an almost trivial fashion, i.e., without the need for schema modification or re-certification of applications. Association between regular entities and events is managed via simple "many-to-many" relationships. We describe the programming interface, as well as techniques for handling input/output, process control, and state transitions. Conclusion The implementation described here has served as the Washington University Genome Sequencing Center's primary information system for several years. It handles all transactions underlying a throughput rate of about 9 million sequencing reactions of various kinds per month and

  20. Weather regimes in past climate atmospheric general circulation model simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kageyama, M.; Ramstein, G. [CEA Saclay, Gif-sur-Yvette (France). Lab. des Sci. du Climat et de l' Environnement; D' Andrea, F.; Vautard, R. [Laboratoire de Meteorologie Dynamique, Ecole Normale Superieure, Paris (France); Valdes, P.J. [Department of Meteorology, University of Reading (United Kingdom)

    1999-10-01

    We investigate the climates of the present-day, inception of the last glaciation (115000 y ago) and last glacial maximum (21000 y ago) in the extratropical north Atlantic and Europe, as simulated by the laboratoire de Meteorologie dynamique atmospheric general circulation model. We use these simulations to investigate the low-frequency variability of the model in different climates. The aim is to evaluate whether changes in the intraseasonal variability, which we characterize using weather regimes, can help describe the impact of different boundary conditions on climate and give a better understanding of climate change processes. Weather regimes are defined as the most recurrent patterns in the 500 hPa geopotential height, using a clustering algorithm method. The regimes found in the climate simulations of the present-day and inception of the last glaciation are similar in their number and their structure. It is the regimes' populations which are found to be different for these climates, with an increase of the model's blocked regime and a decrease in the zonal regime at the inception of the last glaciation. This description reinforces the conclusions from a study of the differences between the climatological averages of the different runs and confirms the northeastward shift to the tail of the Atlantic storm-track, which would favour more precipitation over the site of growth of the Fennoscandian ice-sheet. On the other hand, the last glacial maximum results over this sector are not found to be classifiable, showing that the change in boundary conditions can be responsible for severe changes in the weather regime and low-frequency dynamics. The LGM Atlantic low-frequency variability appears to be dominated by a large-scale retrogressing wave with a period 40 to 50 days. (orig.)