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.

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...

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.

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.

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...

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

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.

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...

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.

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...

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

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

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.)

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.

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...

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

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.

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.

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.)

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.

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.

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.

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...

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.

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)

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

Directory of Open Access Journals (Sweden)

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.

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.

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.

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.

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.

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.

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.

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.

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...

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.

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...

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...

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

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...

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

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

Directory of Open Access Journals (Sweden)

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.

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.

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 ...

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...

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...

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.

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.

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

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

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).

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)

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

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.

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

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.

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.

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.

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.

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...

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

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

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...

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...

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

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.

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

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...

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.

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.

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.)

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…

A generalized business cycle model with delays in gross product and capital stock

International Nuclear Information System (INIS)

Hattaf, Khalid; Riad, Driss; Yousfi, Noura

2017-01-01

Highlights: • A generalized business cycle model is proposed and rigorously analyzed. • Well-posedness of the model and local stability of the economic equilibrium are investigated. • Direction of the Hopf bifurcation and stability of the bifurcating periodic solutions are determined. • A special case and some numerical simulations are presented. - Abstract: In this work, we propose a delayed business cycle model with general investment function. The time delays are introduced into gross product and capital stock, respectively. We first prove that the model is mathematically and economically well posed. In addition, the stability of the economic equilibrium and the existence of Hopf bifurcation are investigated. Our main results show that both time delays can cause the macro-economic system to fluctuate and the economic equilibrium to lose or gain its stability. Moreover, the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions are determined by means of the normal form method and center manifold theory. Furthermore, the models and results presented in many previous studies are improved and generalized.

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

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)

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

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.

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...

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).

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.

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

Parameter identification in a generalized time-harmonic Rayleigh damping model for elastography.

Directory of Open Access Journals (Sweden)

Elijah E W Van Houten

Full Text Available The identifiability of the two damping components of a Generalized Rayleigh Damping model is investigated through analysis of the continuum equilibrium equations as well as a simple spring-mass system. Generalized Rayleigh Damping provides a more diversified attenuation model than pure Viscoelasticity, with two parameters to describe attenuation effects and account for the complex damping behavior found in biological tissue. For heterogeneous Rayleigh Damped materials, there is no equivalent Viscoelastic system to describe the observed motions. For homogeneous systems, the inverse problem to determine the two Rayleigh Damping components is seen to be uniquely posed, in the sense that the inverse matrix for parameter identification is full rank, with certain conditions: when either multi-frequency data is available or when both shear and dilatational wave propagation is taken into account. For the multi-frequency case, the frequency dependency of the elastic parameters adds a level of complexity to the reconstruction problem that must be addressed for reasonable solutions. For the dilatational wave case, the accuracy of compressional wave measurement in fluid saturated soft tissues becomes an issue for qualitative parameter identification. These issues can be addressed with reasonable assumptions on the negligible damping levels of dilatational waves in soft tissue. In general, the parameters of a Generalized Rayleigh Damping model are identifiable for the elastography inverse problem, although with more complex conditions than the simpler Viscoelastic damping model. The value of this approach is the additional structural information provided by the Generalized Rayleigh Damping model, which can be linked to tissue composition as well as rheological interpretations.

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.

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+...

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

Generalized enthalpy model of a high-pressure shift freezing process

KAUST Repository

Smith, N. A. S.

2012-05-02

High-pressure freezing processes are a novel emerging technology in food processing, offering significant improvements to the quality of frozen foods. To be able to simulate plateau times and thermal history under different conditions, in this work, we present a generalized enthalpy model of the high-pressure shift freezing process. The model includes the effects of pressure on conservation of enthalpy and incorporates the freezing point depression of non-dilute food samples. In addition, the significant heat-transfer effects of convection in the pressurizing medium are accounted for by solving the two-dimensional Navier-Stokes equations. We run the model for several numerical tests where the food sample is agar gel, and find good agreement with experimental data from the literature. © 2012 The Royal Society.

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

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.

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

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.

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.

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.

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

Directory of Open Access Journals (Sweden)

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

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

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.

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.

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…

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.

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.

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

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

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

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.

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)

Log-normal frailty models fitted as Poisson generalized linear mixed models.

Science.gov (United States)

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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...

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

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

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

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.

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.

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....

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...

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.

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.

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...

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

Science.gov (United States)

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

2015-01-01

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

A general science-based framework for dynamical spatio-temporal models

Science.gov (United States)

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

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.

An Asset Pricing Approach to Testing General Term Structure Models including Heath-Jarrow-Morton Specifications and Affine Subclasses

DEFF Research Database (Denmark)

Christensen, Bent Jesper; van der Wel, Michel

of the risk premium is associated with the slope factor, and individual risk prices depend on own past values, factor realizations, and past values of other risk prices, and are significantly related to the output gap, consumption, and the equity risk price. The absence of arbitrage opportunities is strongly...... is tested, but in addition to the standard bilinear term in factor loadings and market prices of risk, the relevant mean restriction in the term structure case involves an additional nonlinear (quadratic) term in factor loadings. We estimate our general model using likelihood-based dynamic factor model...... techniques for a variety of volatility factors, and implement the relevant likelihood ratio tests. Our factor model estimates are similar across a general state space implementation and an alternative robust two-step principal components approach. The evidence favors time-varying market prices of risk. Most...

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.

Generalized Tensor Analysis Model for Multi-Subcarrier Analog Optical Systems

DEFF Research Database (Denmark)

Zhao, Ying; Yu, Xianbin; Zheng, Xiaoping

2011-01-01

We propose and develop a general tensor analysis framework for a subcarrier multiplex analog optical fiber link for applications in microwave photonics. The goal of this work is to construct an uniform method to address nonlinear distortions of a discrete frequency transmission system. We employ....... In addition, it is demonstrated that each corresponding tensor is formally determined by device structures, which allows for a synthesized study of device combinations more systematically. For implementing numerical methods, the practical significance of the tensor model is it simplifies the derivation...... details compared with series-based approaches by hiding the underlying multi-fold summation and index operation. The integrity of the proposed methodology is validated by investigating the classical intensity modulated system. Furthermore, to give an application model of the tensor formalism, we make...

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…

On the stability of soliton solution in NLS-type general field model

International Nuclear Information System (INIS)

Chakrabarti, S.; Nayyar, A.H.

1982-08-01

A model incorporating the nonlinear Schroedinger equation and its generalizations is considered and the stability of its periodic-in-time solutions under the restriction of a fixed charge Q is analysed. It is shown that the necessary condition for the stability is given by the inequality deltaQ/deltaν<0, where ν is the parameter of periodicity of the solution in time. In particular, one specific class of Lagrangians is considered and, in addition, the sufficient conditions for the stability of the soliton solutions are also determined. This study thus examines both the necessary and the sufficient conditions for the stability of the solutions of nonlinear Schroedinger equation and some of its generalizations. (author)

The Generalized Hill Model: A Kinematic Approach Towards Active Muscle Contraction

Science.gov (United States)

Menzel, Andreas; Kuhl, Ellen

2014-01-01

Excitation-contraction coupling is the physiological process of converting an electrical stimulus into a mechanical response. In muscle, the electrical stimulus is an action potential and the mechanical response is active contraction. The classical Hill model characterizes muscle contraction though one contractile element, activated by electrical excitation, and two non-linear springs, one in series and one in parallel. This rheology translates into an additive decomposition of the total stress into a passive and an active part. Here we supplement this additive decomposition of the stress by a multiplicative decomposition of the deformation gradient into a passive and an active part. We generalize the one-dimensional Hill model to the three-dimensional setting and constitutively define the passive stress as a function of the total deformation gradient and the active stress as a function of both the total deformation gradient and its active part. We show that this novel approach combines the features of both the classical stress-based Hill model and the recent active-strain models. While the notion of active stress is rather phenomenological in nature, active strain is micro-structurally motivated, physically measurable, and straightforward to calibrate. We demonstrate that our model is capable of simulating excitation-contraction coupling in cardiac muscle with its characteristic features of wall thickening, apical lift, and ventricular torsion. PMID:25221354

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.

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.

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...

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.

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.

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...

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.

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

Science.gov (United States)

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

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.

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…

Generalized Heine–Stieltjes and Van Vleck polynomials associated with two-level, integrable BCS models

International Nuclear Information System (INIS)

Marquette, Ian; Links, Jon

2012-01-01

We study the Bethe ansatz/ordinary differential equation (BA/ODE) correspondence for Bethe ansatz equations that belong to a certain class of coupled, nonlinear, algebraic equations. Through this approach we numerically obtain the generalized Heine–Stieltjes and Van Vleck polynomials in the degenerate, two-level limit for four cases of integrable Bardeen–Cooper–Schrieffer (BCS) pairing models. These are the s-wave pairing model, the p + ip-wave pairing model, the p + ip pairing model coupled to a bosonic molecular pair degree of freedom, and a newly introduced extended d + id-wave pairing model with additional interactions. The zeros of the generalized Heine–Stieltjes polynomials provide solutions of the corresponding Bethe ansatz equations. We compare the roots of the ground states with curves obtained from the solution of a singular integral equation approximation, which allows for a characterization of ground-state phases in these systems. Our techniques also permit the computation of the roots of the excited states. These results illustrate how the BA/ODE correspondence can be used to provide new numerical methods to study a variety of integrable systems. (paper)

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.

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

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

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…

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.

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.)

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.

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.

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)

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.

Fractional Generalizations of Maxwell and Kelvin-Voigt Models for Biopolymer Characterization.

Directory of Open Access Journals (Sweden)

Bertrand Jóźwiak

Full Text Available The paper proposes a fractional generalization of the Maxwell and Kelvin-Voigt rheological models for a description of dynamic behavior of biopolymer materials. It was found that the rheological models of Maxwell-type do not work in the case of modeling of viscoelastic solids, and the model which significantly better describes the nature of changes in rheological properties of such media is the modified fractional Kelvin-Voigt model with two built-in springpots (MFKVM2. The proposed model was used to describe the experimental data from the oscillatory and creep tests of 3% (w/v kuzu starch pastes, and to determine the values of their rheological parameters as a function of pasting time. These parameters provide a lot of additional information about structure and viscoelastic properties of the medium in comparison to the classical analysis of dynamic curves G' and G" and shear creep compliance J(t. It allowed for a comprehensive description of a wide range of properties of kuzu starch pastes, depending on the conditions of pasting process.

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...

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.

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...

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.

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.

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

Generalized versus non-generalized neural network model for multi-lead inflow forecasting at Aswan High Dam

Directory of Open Access Journals (Sweden)

A. El-Shafie

2011-03-01

Full Text Available Artificial neural networks (ANN have been found efficient, particularly in problems where characteristics of the processes are stochastic and difficult to describe using explicit mathematical models. However, time series prediction based on ANN algorithms is fundamentally difficult and faces problems. One of the major shortcomings is the search for the optimal input pattern in order to enhance the forecasting capabilities for the output. The second challenge is the over-fitting problem during the training procedure and this occurs when ANN loses its generalization. In this research, autocorrelation and cross correlation analyses are suggested as a method for searching the optimal input pattern. On the other hand, two generalized methods namely, Regularized Neural Network (RNN and Ensemble Neural Network (ENN models are developed to overcome the drawbacks of classical ANN models. Using Generalized Neural Network (GNN helped avoid over-fitting of training data which was observed as a limitation of classical ANN models. Real inflow data collected over the last 130 years at Lake Nasser was used to train, test and validate the proposed model. Results show that the proposed GNN model outperforms non-generalized neural network and conventional auto-regressive models and it could provide accurate inflow forecasting.

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...

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.

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.

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.

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...

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.

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

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...

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…

Generalized viscothermoelasticity theory of dual-phase-lagging model for damping analysis in circular micro-plate resonators

Science.gov (United States)

Grover, D.; Seth, R. K.

2018-05-01

Analysis and numerical results are presented for the thermoelastic dissipation of a homogeneous isotropic, thermally conducting, Kelvin-Voigt type circular micro-plate based on Kirchhoff's Love plate theory utilizing generalized viscothermoelasticity theory of dual-phase-lagging model. The analytical expressions for thermoelastic damping of vibration and frequency shift are obtained for generalized dual-phase-lagging model and coupled viscothermoelastic plates. The scaled thermoelastic damping has been illustrated in case of circular plate and axisymmetric circular plate for fixed aspect ratio for clamped and simply supported boundary conditions. It is observed that the damping of vibrations significantly depend on time delay and mechanical relaxation times in addition to thermo-mechanical coupling in circular plate under resonance conditions and plate dimensions.

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.

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,

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...

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.

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....

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

DEFF Research Database (Denmark)

Holst, René; Jørgensen, Bent

2015-01-01

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

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

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.

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...

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.

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.

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...

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.

Modelling uncertainty with generalized credal sets: application to conjunction and decision

Science.gov (United States)

Bronevich, Andrey G.; Rozenberg, Igor N.

2018-01-01

To model conflict, non-specificity and contradiction in information, upper and lower generalized credal sets are introduced. Any upper generalized credal set is a convex subset of plausibility measures interpreted as lower probabilities whose bodies of evidence consist of singletons and a certain event. Analogously, contradiction is modelled in the theory of evidence by a belief function that is greater than zero at empty set. Based on generalized credal sets, we extend the conjunctive rule for contradictory sources of information, introduce constructions like natural extension in the theory of imprecise probabilities and show that the model of generalized credal sets coincides with the model of imprecise probabilities if the profile of a generalized credal set consists of probability measures. We give ways how the introduced model can be applied to decision problems.

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.

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...

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

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

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.)

Escaping the snare of chronological growth and launching a free curve alternative: general deviance as latent growth model.

Science.gov (United States)

Wood, Phillip Karl; Jackson, Kristina M

2013-08-01

model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the "snares" alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control.

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 ...

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 ...

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.

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.

Impact of an improved shortwave radiation scheme in the MAECHAM5 General Circulation Model

Directory of Open Access Journals (Sweden)

J. J. Morcrette

2007-05-01

increased downward (upward circulation in the winter (summer hemisphere. In addition, the comparison of the two simulations performed with the general circulation model shows that the increase in the spectral resolution of the shortwave radiation and the associated changes in the cloud optical properties result in a warming (0.5–1 K and moistening (3%–12% of the upper tropical troposphere. By comparing these modeled differences with previous works, it appears that the reported changes in the solar radiation scheme contribute to improve the model mean temperature also in the troposphere.

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.

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.

Comparison of body composition between fashion models and women in general.

Science.gov (United States)

Park, Sunhee

2017-12-31

The present study compared the physical characteristics and body composition of professional fashion models and women in general, utilizing the skinfold test. The research sample consisted of 90 professional fashion models presently active in Korea and 100 females in the general population, all selected through convenience sampling. Measurement was done following standardized methods and procedures set by the International Society for the Advancement of Kinanthropometry. Body density (mg/ mm) and body fat (%) were measured at the biceps, triceps, subscapular, and suprailiac areas. The results showed that the biceps, triceps, subscapular, and suprailiac areas of professional fashion models were significantly thinner than those of women in general (pfashion models were significantly lower than those in women in general (pfashion models was significantly greater (pfashion models is higher, due to taller stature, than in women in general. Moreover, there is an effort on the part of fashion models to lose weight in order to maintain a thin body and a low weight for occupational reasons. ©2017 The Korean Society for Exercise Nutrition

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

A Generalized Minimum Cost Flow Model for Multiple Emergency Flow Routing

Directory of Open Access Journals (Sweden)

Jianxun Cui

2014-01-01

Full Text Available During real-life disasters, that is, earthquakes, floods, terrorist attacks, and other unexpected events, emergency evacuation and rescue are two primary operations that can save the lives and property of the affected population. It is unavoidable that evacuation flow and rescue flow will conflict with each other on the same spatial road network and within the same time window. Therefore, we propose a novel generalized minimum cost flow model to optimize the distribution pattern of these two types of flow on the same network by introducing the conflict cost. The travel time on each link is assumed to be subject to a bureau of public road (BPR function rather than a fixed cost. Additionally, we integrate contraflow operations into this model to redesign the network shared by those two types of flow. A nonconvex mixed-integer nonlinear programming model with bilinear, fractional, and power components is constructed, and GAMS/BARON is used to solve this programming model. A case study is conducted in the downtown area of Harbin city in China to verify the efficiency of proposed model, and several helpful findings and managerial insights are also presented.

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...

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....

Modeling age-specific mortality for countries with generalized HIV epidemics.

Directory of Open Access Journals (Sweden)

David J Sharrow

Full Text Available In a given population the age pattern of mortality is an important determinant of total number of deaths, age structure, and through effects on age structure, the number of births and thereby growth. Good mortality models exist for most populations except those experiencing generalized HIV epidemics and some developing country populations. The large number of deaths concentrated at very young and adult ages in HIV-affected populations produce a unique 'humped' age pattern of mortality that is not reproduced by any existing mortality models. Both burden of disease reporting and population projection methods require age-specific mortality rates to estimate numbers of deaths and produce plausible age structures. For countries with generalized HIV epidemics these estimates should take into account the future trajectory of HIV prevalence and its effects on age-specific mortality. In this paper we present a parsimonious model of age-specific mortality for countries with generalized HIV/AIDS epidemics.The model represents a vector of age-specific mortality rates as the weighted sum of three independent age-varying components. We derive the age-varying components from a Singular Value Decomposition of the matrix of age-specific mortality rate schedules. The weights are modeled as a function of HIV prevalence and one of three possible sets of inputs: life expectancy at birth, a measure of child mortality, or child mortality with a measure of adult mortality. We calibrate the model with 320 five-year life tables for each sex from the World Population Prospects 2010 revision that come from the 40 countries of the world that have and are experiencing a generalized HIV epidemic. Cross validation shows that the model is able to outperform several existing model life table systems.We present a flexible, parsimonious model of age-specific mortality for countries with generalized HIV epidemics. Combined with the outputs of existing epidemiological and

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.

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.

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.

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.)

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.

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...

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.

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

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.].

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)

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...

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.

General MACOS Interface for Modeling and Analysis for Controlled Optical Systems

Science.gov (United States)

Sigrist, Norbert; Basinger, Scott A.; Redding, David C.

2012-01-01

The General MACOS Interface (GMI) for Modeling and Analysis for Controlled Optical Systems (MACOS) enables the use of MATLAB as a front-end for JPL s critical optical modeling package, MACOS. MACOS is JPL s in-house optical modeling software, which has proven to be a superb tool for advanced systems engineering of optical systems. GMI, coupled with MACOS, allows for seamless interfacing with modeling tools from other disciplines to make possible integration of dynamics, structures, and thermal models with the addition of control systems for deformable optics and other actuated optics. This software package is designed as a tool for analysts to quickly and easily use MACOS without needing to be an expert at programming MACOS. The strength of MACOS is its ability to interface with various modeling/development platforms, allowing evaluation of system performance with thermal, mechanical, and optical modeling parameter variations. GMI provides an improved means for accessing selected key MACOS functionalities. The main objective of GMI is to marry the vast mathematical and graphical capabilities of MATLAB with the powerful optical analysis engine of MACOS, thereby providing a useful tool to anyone who can program in MATLAB. GMI also improves modeling efficiency by eliminating the need to write an interface function for each task/project, reducing error sources, speeding up user/modeling tasks, and making MACOS well suited for fast prototyping.

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.

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

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

Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging

Directory of Open Access Journals (Sweden)

Naoya Sueishi

2013-07-01

Full Text Available This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.

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..

Models of clinical reasoning with a focus on general practice: A critical review.

Science.gov (United States)

Yazdani, Shahram; Hosseinzadeh, Mohammad; Hosseini, Fakhrolsadat

2017-10-01

Diagnosis lies at the heart of general practice. Every day general practitioners (GPs) visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings. A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized. Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties of clinical reasoning in this setting is needed.

Models of clinical reasoning with a focus on general practice: a critical review

Directory of Open Access Journals (Sweden)

SHAHRAM YAZDANI

2017-10-01

Full Text Available Introduction: Diagnosis lies at the heart of general practice. Every day general practitioners (GPs visit patients with a wide variety of complaints and concerns, with often minor but sometimes serious symptoms. General practice has many features which differentiate it from specialty care setting, but during the last four decades little attention was paid to clinical reasoning in general practice. Therefore, we aimed to critically review the clinical reasoning models with a focus on the clinical reasoning in general practice or clinical reasoning of general practitioners to find out to what extent the existing models explain the clinical reasoning specially in primary care and also identity the gaps of the model for use in primary care settings Methods: A systematic search to find models of clinical reasoning were performed. To have more precision, we excluded the studies that focused on neurobiological aspects of reasoning, reasoning in disciplines other than medicine decision making or decision analysis on treatment or management plan. All the articles and documents were first scanned to see whether they include important relevant contents or any models. The selected studies which described a model of clinical reasoning in general practitioners or with a focus on general practice were then reviewed and appraisal or critics of other authors on these models were included. The reviewed documents on the model were synthesized Results: Six models of clinical reasoning were identified including hypothetic-deductive model, pattern recognition, a dual process diagnostic reasoning model, pathway for clinical reasoning, an integrative model of clinical reasoning, and model of diagnostic reasoning strategies in primary care. Only one model had specifically focused on general practitioners reasoning. Conclusion: A Model of clinical reasoning that included specific features of general practice to better help the general practitioners with the difficulties

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

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.

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.

A Generalized Yang-Mills Model and Dynamical Breaking of Gauge Symmetry

International Nuclear Information System (INIS)

Wang Dianfu; Song Heshan

2005-01-01

A generalized Yang-Mills model, which contains, besides the vector part V μ , also a scalar part S, is constructed and the dynamical breaking of gauge symmetry in the model is also discussed. It is shown, in terms of Nambu-Jona-Lasinio (NJL) mechanism, that the gauge symmetry breaking can be realized dynamically in the generalized Yang-Mills model. The combination of the generalized Yang-Mills model and the NJL mechanism provides a way to overcome the difficulties related to the Higgs field and the Higgs mechanism in the usual spontaneous symmetry breaking theory.

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...

Genetic parameters for racing records in trotters using linear and generalized linear models.

Science.gov (United States)

Suontama, M; van der Werf, J H J; Juga, J; Ojala, M

2012-09-01

Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success.

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)

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.

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.

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.

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

Testing the Beta-Lognormal Model in Amazonian Rainfall Fields Using the Generalized Space q-Entropy

Directory of Open Access Journals (Sweden)

Hernán D. Salas

2017-12-01

Full Text Available We study spatial scaling and complexity properties of Amazonian radar rainfall fields using the Beta-Lognormal Model (BL-Model with the aim to characterize and model the process at a broad range of spatial scales. The Generalized Space q-Entropy Function (GSEF, an entropic measure defined as a continuous set of power laws covering a broad range of spatial scales, S q ( λ ∼ λ Ω ( q , is used as a tool to check the ability of the BL-Model to represent observed 2-D radar rainfall fields. In addition, we evaluate the effect of the amount of zeros, the variability of rainfall intensity, the number of bins used to estimate the probability mass function, and the record length on the GSFE estimation. Our results show that: (i the BL-Model adequately represents the scaling properties of the q-entropy, S q, for Amazonian rainfall fields across a range of spatial scales λ from 2 km to 64 km; (ii the q-entropy in rainfall fields can be characterized by a non-additivity value, q s a t, at which rainfall reaches a maximum scaling exponent, Ω s a t; (iii the maximum scaling exponent Ω s a t is directly related to the amount of zeros in rainfall fields and is not sensitive to either the number of bins to estimate the probability mass function or the variability of rainfall intensity; and (iv for small-samples, the GSEF of rainfall fields may incur in considerable bias. Finally, for synthetic 2-D rainfall fields from the BL-Model, we look for a connection between intermittency using a metric based on generalized Hurst exponents, M ( q 1 , q 2 , and the non-extensive order (q-order of a system, Θ q, which relates to the GSEF. Our results do not exhibit evidence of such relationship.

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...

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.

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.

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...

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...

A generalized multi-dimensional mathematical model for charging and discharging processes in a supercapacitor

Energy Technology Data Exchange (ETDEWEB)

Allu, Srikanth [ORNL; Velamur Asokan, Badri [Exxon Mobil Research and Engineering; Shelton, William A [Louisiana State University; Philip, Bobby [ORNL; Pannala, Sreekanth [ORNL

2014-01-01

A generalized three dimensional computational model based on unied formulation of electrode- electrolyte-electrode system of a electric double layer supercapacitor has been developed. The model accounts for charge transport across the solid-liquid system. This formulation based on volume averaging process is a widely used concept for the multiphase ow equations ([28] [36]) and is analogous to porous media theory typically employed for electrochemical systems [22] [39] [12]. This formulation is extended to the electrochemical equations for a supercapacitor in a consistent fashion, which allows for a single-domain approach with no need for explicit interfacial boundary conditions as previously employed ([38]). In this model it is easy to introduce the spatio-temporal variations, anisotropies of physical properties and it is also conducive for introducing any upscaled parameters from lower length{scale simulations and experiments. Due to the irregular geometric congurations including porous electrode, the charge transport and subsequent performance characteristics of the super-capacitor can be easily captured in higher dimensions. A generalized model of this nature also provides insight into the applicability of 1D models ([38]) and where multidimensional eects need to be considered. In addition, simple sensitivity analysis on key input parameters is performed in order to ascertain the dependence of the charge and discharge processes on these parameters. Finally, we demonstarted how this new formulation can be applied to non-planar supercapacitors

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.

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)

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 ...

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

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....

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....

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.

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...

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.

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

Science.gov (United States)

Tijmstra, Jesper; Bolsinova, Maria; Jeon, Minjeong

2018-01-10

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

Generalized network modeling of capillary-dominated two-phase flow.

Science.gov (United States)

Raeini, Ali Q; Bijeljic, Branko; Blunt, Martin J

2018-02-01

We present a generalized network model for simulating capillary-dominated two-phase flow through porous media at the pore scale. Three-dimensional images of the pore space are discretized using a generalized network-described in a companion paper [A. Q. Raeini, B. Bijeljic, and M. J. Blunt, Phys. Rev. E 96, 013312 (2017)2470-004510.1103/PhysRevE.96.013312]-which comprises pores that are divided into smaller elements called half-throats and subsequently into corners. Half-throats define the connectivity of the network at the coarsest level, connecting each pore to half-throats of its neighboring pores from their narrower ends, while corners define the connectivity of pore crevices. The corners are discretized at different levels for accurate calculation of entry pressures, fluid volumes, and flow conductivities that are obtained using direct simulation of flow on the underlying image. This paper discusses the two-phase flow model that is used to compute the averaged flow properties of the generalized network, including relative permeability and capillary pressure. We validate the model using direct finite-volume two-phase flow simulations on synthetic geometries, and then present a comparison of the model predictions with a conventional pore-network model and experimental measurements of relative permeability in the literature.

Generalized network modeling of capillary-dominated two-phase flow

Science.gov (United States)

Raeini, Ali Q.; Bijeljic, Branko; Blunt, Martin J.

2018-02-01

We present a generalized network model for simulating capillary-dominated two-phase flow through porous media at the pore scale. Three-dimensional images of the pore space are discretized using a generalized network—described in a companion paper [A. Q. Raeini, B. Bijeljic, and M. J. Blunt, Phys. Rev. E 96, 013312 (2017), 10.1103/PhysRevE.96.013312]—which comprises pores that are divided into smaller elements called half-throats and subsequently into corners. Half-throats define the connectivity of the network at the coarsest level, connecting each pore to half-throats of its neighboring pores from their narrower ends, while corners define the connectivity of pore crevices. The corners are discretized at different levels for accurate calculation of entry pressures, fluid volumes, and flow conductivities that are obtained using direct simulation of flow on the underlying image. This paper discusses the two-phase flow model that is used to compute the averaged flow properties of the generalized network, including relative permeability and capillary pressure. We validate the model using direct finite-volume two-phase flow simulations on synthetic geometries, and then present a comparison of the model predictions with a conventional pore-network model and experimental measurements of relative permeability in the literature.

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.

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.

Generalized modeling of the fractional-order memcapacitor and its character analysis

Science.gov (United States)

Guo, Zhang; Si, Gangquan; Diao, Lijie; Jia, Lixin; Zhang, Yanbin

2018-06-01

Memcapacitor is a new type of memory device generalized from the memristor. This paper proposes a generalized fractional-order memcapacitor model by introducing the fractional calculus into the model. The generalized formulas are studied and the two fractional-order parameter α, β are introduced where α mostly affects the fractional calculus value of charge q within the generalized Ohm's law and β generalizes the state equation which simulates the physical mechanism of a memcapacitor into the fractional sense. This model will be reduced to the conventional memcapacitor as α = 1 , β = 0 and to the conventional memristor as α = 0 , β = 1 . Then the numerical analysis of the fractional-order memcapacitor is studied. And the characteristics and output behaviors of the fractional-order memcapacitor applied with sinusoidal charge are derived. The analysis results have shown that there are four basic v - q and v - i curve patterns when the fractional order α, β respectively equal to 0 or 1, moreover all v - q and v - i curves of the other fractional-order models are transition curves between the four basic patterns.

Retrofitting Non-Cognitive-Diagnostic Reading Assessment under the Generalized DINA Model Framework

Science.gov (United States)

Chen, Huilin; Chen, Jinsong

2016-01-01

Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees' specific strengths and weaknesses in a set of skills or attributes within a domain. By adopting the Generalized-DINA model framework, the recently developed general modeling framework, we attempted to retrofit the PISA reading assessments, a…

Tilted Bianchi type I dust fluid cosmological model in general relativity

Indian Academy of Sciences (India)

Tilted Bianchi type I dust fluid cosmological model in general relativity ... In this paper, we have investigated a tilted Bianchi type I cosmological model filled with dust of perfect fluid in general relativity. ... Pramana – Journal of Physics | News ...

Combining a popularity-productivity stochastic block model with a discriminative-content model for general structure detection.

Science.gov (United States)

Chai, Bian-fang; Yu, Jian; Jia, Cai-Yan; Yang, Tian-bao; Jiang, Ya-wen

2013-07-01

Latent community discovery that combines links and contents of a text-associated network has drawn more attention with the advance of social media. Most of the previous studies aim at detecting densely connected communities and are not able to identify general structures, e.g., bipartite structure. Several variants based on the stochastic block model are more flexible for exploring general structures by introducing link probabilities between communities. However, these variants cannot identify the degree distributions of real networks due to a lack of modeling of the differences among nodes, and they are not suitable for discovering communities in text-associated networks because they ignore the contents of nodes. In this paper, we propose a popularity-productivity stochastic block (PPSB) model by introducing two random variables, popularity and productivity, to model the differences among nodes in receiving links and producing links, respectively. This model has the flexibility of existing stochastic block models in discovering general community structures and inherits the richness of previous models that also exploit popularity and productivity in modeling the real scale-free networks with power law degree distributions. To incorporate the contents in text-associated networks, we propose a combined model which combines the PPSB model with a discriminative model that models the community memberships of nodes by their contents. We then develop expectation-maximization (EM) algorithms to infer the parameters in the two models. Experiments on synthetic and real networks have demonstrated that the proposed models can yield better performances than previous models, especially on networks with general structures.

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.

Maximally Generalized Yang-Mills Model and Dynamical Breaking of Gauge Symmetry

International Nuclear Information System (INIS)

Wang Dianfu; Song Heshan

2006-01-01

A maximally generalized Yang-Mills model, which contains, besides the vector part V μ , also an axial-vector part A μ , a scalar part S, a pseudoscalar part P, and a tensor part T μν , is constructed and the dynamical breaking of gauge symmetry in the model is also discussed. It is shown, in terms of the Nambu-Jona-Lasinio mechanism, that the gauge symmetry breaking can be realized dynamically in the maximally generalized Yang-Mills model. The combination of the maximally generalized Yang-Mills model and the NJL mechanism provides a way to overcome the difficulties related to the Higgs field and the Higgs mechanism in the usual spontaneous symmetry breaking theory.

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.

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

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

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 ...

Right-handed quark mixings in minimal left-right symmetric model with general CP violation

International Nuclear Information System (INIS)

Zhang Yue; Ji Xiangdong; An Haipeng; Mohapatra, R. N.

2007-01-01

We solve systematically for the right-handed quark mixings in the minimal left-right symmetric model which generally has both explicit and spontaneous CP violations. The leading-order result has the same hierarchical structure as the left-handed Cabibbo-Kobayashi-Maskawa mixing, but with additional CP phases originating from a spontaneous CP-violating phase in the Higgs vacuum expectation values. We explore the phenomenology entailed by the new right-handed mixing matrix, particularly the bounds on the mass of W R and the CP phase of the Higgs vacuum expectation values

Generalized outcome-based strategy classification: comparing deterministic and probabilistic choice models.

Science.gov (United States)

Hilbig, Benjamin E; Moshagen, Morten

2014-12-01

Model comparisons are a vital tool for disentangling which of several strategies a decision maker may have used--that is, which cognitive processes may have governed observable choice behavior. However, previous methodological approaches have been limited to models (i.e., decision strategies) with deterministic choice rules. As such, psychologically plausible choice models--such as evidence-accumulation and connectionist models--that entail probabilistic choice predictions could not be considered appropriately. To overcome this limitation, we propose a generalization of Bröder and Schiffer's (Journal of Behavioral Decision Making, 19, 361-380, 2003) choice-based classification method, relying on (1) parametric order constraints in the multinomial processing tree framework to implement probabilistic models and (2) minimum description length for model comparison. The advantages of the generalized approach are demonstrated through recovery simulations and an experiment. In explaining previous methods and our generalization, we maintain a nontechnical focus--so as to provide a practical guide for comparing both deterministic and probabilistic choice models.

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.

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

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…

A Generalized Nonlocal Calculus with Application to the Peridynamics Model for Solid Mechanics

OpenAIRE

Alali, Bacim; Liu, Kuo; Gunzburger, Max

2014-01-01

A nonlocal vector calculus was introduced in [2] that has proved useful for the analysis of the peridynamics model of nonlocal mechanics and nonlocal diffusion models. A generalization is developed that provides a more general setting for the nonlocal vector calculus that is independent of particular nonlocal models. It is shown that general nonlocal calculus operators are integral operators with specific integral kernels. General nonlocal calculus properties are developed, including nonlocal...

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…

An Object-oriented Knowledge Link Model for General Knowledge Management

OpenAIRE

Xiao-hong, CHEN; Bang-chuan, LAI

2005-01-01

The knowledge link is the basic on knowledge share and the indispensable part in knowledge standardization management. In this paper, a object-oriented knowledge link model is proposed for general knowledge management by using objectoriented representation based on knowledge levels system. In the model, knowledge link is divided into general knowledge link and integrated knowledge with corresponding link properties and methods. What’s more, its BNF syntax is described and designed.

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…

Quasi-chemical approach for adsorption of mixtures with non-additive lateral interactions

Energy Technology Data Exchange (ETDEWEB)

Pinto, O.A. [Instituto de Bionanotecnología (INBIONATEC-CONICET), Universidad Nacional de Santiago de Estero, RN 9 Km 1125 Villa el Zanjón, Santiago del Estero G4206XCP (Argentina); Pasinetti, P.M., E-mail: pmp@unsl.edu.ar [Departamento de Física, Instituto de Física Aplicada (INFAP), Universidad Nacional de San Luis—CONICET, Ejército de los Andes 950, D5700BWS San Luis (Argentina); Ramirez-Pastor, A.J. [Departamento de Física, Instituto de Física Aplicada (INFAP), Universidad Nacional de San Luis—CONICET, Ejército de los Andes 950, D5700BWS San Luis (Argentina)

2017-01-15

Highlights: • The classical quasi-chemical approach is generalized to model non-additive mixtures. • The formalism allows to obtain the partial isotherms and the differential heat of adsorption. • A rich variety of low-temperature phases is observed in the adsorbed layer. • Theoretical results show a good agreement with Monte Carlo simulations. - Abstract: The statistical thermodynamics of binary mixtures with non-additive lateral interactions was developed on a generalization in the spirit of the lattice-gas model and the classical quasi-chemical approximation (QCA). The traditional assumption of a strictly pairwise additive nearest-neighbors interaction is replaced by a more general one, namely that the bond linking a certain atom with any of its neighbors depends considerably on how many of them are actually present (or absent) on the sites in the first coordination shell of the atom. The total and partial adsorption isotherms are given for both attractive and repulsive lateral interactions between the adsorbed species. Interesting behaviors are observed and discussed in terms of the low-temperature phases formed in the system. Comparisons with Monte Carlo simulations are performed in order to test the validity of the theoretical model.

Generalized structured component analysis a component-based approach to structural equation modeling

CERN Document Server

Hwang, Heungsun

2014-01-01

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new a...

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.

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.

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.

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.

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

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.

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.

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

FIDIC Conditions of Subcontract as a Model for General Conditions of Subcontract in Pakistan

Directory of Open Access Journals (Sweden)

Muhammad Umer Zubair

2016-12-01

Full Text Available Fair allocation of risks in conditions of contract is pivotal for coordination, unhindered execution, dispute resolution and maintenance of positive relationship among the parties executing the contract. Pakistani construction industry despite subcontracting a large percentage of construction projects lacks standard conditions of subcontract and they are primarily based on the will of the prime contractor that is onerous for the subcontractor. Therefore in order to develop a model for the general conditions of subcontract in Pakistan the conditions proposed by Associated General Contractors of California, FIDIC in 1994 and 2011, Construction Industry Development Board Malaysia, American Institute of Architects and by the Government of Hong Kong were compared to determine the similarities and differences among them. Afterwards a questionnaire based on the significant provisions of these subcontracts was conducted in the construction industry of Pakistan to determine the appropriate conditions for model subcontract. The results of the survey were further subjected to discussions with the legal experts. Out of 35 suggestions made for the general conditions of subcontract 23 originated from FIDIC in which 20 are recommended by its 2011’s version. It can therefore be implemented in Pakistan with certain amendments and additions as proposed in light of conditions of other subcontracts and the results of the survey and discussions with legal experts.

A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint.

Directory of Open Access Journals (Sweden)

Chaogui Kang

Full Text Available We generalized the recently introduced "radiation model", as an analog to the generalization of the classic "gravity model", to consolidate its nature of universality for modeling diverse mobility systems. By imposing the appropriate scaling exponent λ, normalization factor κ and system constraints including searching direction and trip OD constraint, the generalized radiation model accurately captures real human movements in various scenarios and spatial scales, including two different countries and four different cities. Our analytical results also indicated that the generalized radiation model outperformed alternative mobility models in various empirical analyses.

Generalized linear models with random effects unified analysis via H-likelihood

CERN Document Server

Lee, Youngjo; Pawitan, Yudi

2006-01-01

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of...

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

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...

PerMallows: An R Package for Mallows and Generalized Mallows Models

Directory of Open Access Journals (Sweden)

Ekhine Irurozki

2016-08-01

Full Text Available In this paper we present the R package PerMallows, which is a complete toolbox to work with permutations, distances and some of the most popular probability models for permutations: Mallows and the Generalized Mallows models. The Mallows model is an exponential location model, considered as analogous to the Gaussian distribution. It is based on the definition of a distance between permutations. The Generalized Mallows model is its best-known extension. The package includes functions for making inference, sampling and learning such distributions. The distances considered in PerMallows are Kendall's τ , Cayley, Hamming and Ulam.

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.

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

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.

Interest Rates with Long Memory: A Generalized Affine Term-Structure Model

DEFF Research Database (Denmark)

Osterrieder, Daniela

.S. government bonds, we model the time series of the state vector by means of a co-fractional vector autoregressive model. The implication is that yields of all maturities exhibit nonstationary, yet mean-reverting, long-memory behavior of the order d ≈ 0.87. The long-run dynamics of the state vector are driven......We propose a model for the term structure of interest rates that is a generalization of the discrete-time, Gaussian, affine yield-curve model. Compared to standard affine models, our model allows for general linear dynamics in the vector of state variables. In an application to real yields of U...... forecasts that outperform several benchmark models, especially at long forecasting horizons....

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)

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...

On the characterization and software implementation of general protein lattice models.

Directory of Open Access Journals (Sweden)

Alessio Bechini

Full Text Available models of proteins have been widely used as a practical means to computationally investigate general properties of the system. In lattice models any sterically feasible conformation is represented as a self-avoiding walk on a lattice, and residue types are limited in number. So far, only two- or three-dimensional lattices have been used. The inspection of the neighborhood of alpha carbons in the core of real proteins reveals that also lattices with higher coordination numbers, possibly in higher dimensional spaces, can be adopted. In this paper, a new general parametric lattice model for simplified protein conformations is proposed and investigated. It is shown how the supporting software can be consistently designed to let algorithms that operate on protein structures be implemented in a lattice-agnostic way. The necessary theoretical foundations are developed and organically presented, pinpointing the role of the concept of main directions in lattice-agnostic model handling. Subsequently, the model features across dimensions and lattice types are explored in tests performed on benchmark protein sequences, using a Python implementation. Simulations give insights on the use of square and triangular lattices in a range of dimensions. The trend of potential minimum for sequences of different lengths, varying the lattice dimension, is uncovered. Moreover, an extensive quantitative characterization of the usage of the so-called "move types" is reported for the first time. The proposed general framework for the development of lattice models is simple yet complete, and an object-oriented architecture can be proficiently employed for the supporting software, by designing ad-hoc classes. The proposed framework represents a new general viewpoint that potentially subsumes a number of solutions previously studied. The adoption of the described model pushes to look at protein structure issues from a more general and essential perspective, making

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.

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

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.

A General Framework for Portfolio Theory—Part I: Theory and Various Models

Directory of Open Access Journals (Sweden)

Stanislaus Maier-Paape

2018-05-01

Full Text Available Utility and risk are two often competing measurements on the investment success. We show that efficient trade-off between these two measurements for investment portfolios happens, in general, on a convex curve in the two-dimensional space of utility and risk. This is a rather general pattern. The modern portfolio theory of Markowitz (1959 and the capital market pricing model Sharpe (1964, are special cases of our general framework when the risk measure is taken to be the standard deviation and the utility function is the identity mapping. Using our general framework, we also recover and extend the results in Rockafellar et al. (2006, which were already an extension of the capital market pricing model to allow for the use of more general deviation measures. This generalized capital asset pricing model also applies to e.g., when an approximation of the maximum drawdown is considered as a risk measure. Furthermore, the consideration of a general utility function allows for going beyond the “additive” performance measure to a “multiplicative” one of cumulative returns by using the log utility. As a result, the growth optimal portfolio theory Lintner (1965 and the leverage space portfolio theory Vince (2009 can also be understood and enhanced under our general framework. Thus, this general framework allows a unification of several important existing portfolio theories and goes far beyond. For simplicity of presentation, we phrase all for a finite underlying probability space and a one period market model, but generalizations to more complex structures are straightforward.

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

Tilted Bianchi type I dust fluid cosmological model in general relativity

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics; Volume 58; Issue 3. Tilted Bianchi type I dust fluid cosmological model in general ... In this paper, we have investigated a tilted Bianchi type I cosmological model filled with dust of perfect fluid in general relativity. To get a determinate solution, we have assumed a condition  ...

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.

Radiation effects on cancer mortality among A-bomb survivors, 1950-72. Comparison of some statistical models and analysis based on the additive logit model

Energy Technology Data Exchange (ETDEWEB)

Otake, M [Hiroshima Univ. (Japan). Faculty of Science

1976-12-01

Various statistical models designed to determine the effects of radiation dose on mortality of atomic bomb survivors in Hiroshima and Nagasaki from specific cancers were evaluated on the basis of a basic k(age) x c(dose) x 2 contingency table. From the aspects of application and fits of different models, analysis based on the additive logit model was applied to the mortality experience of this population during the 22year period from 1 Oct. 1950 to 31 Dec. 1972. The advantages and disadvantages of the additive logit model were demonstrated. Leukemia mortality showed a sharp rise with an increase in dose. The dose response relationship suggests a possible curvature or a log linear model, particularly if the dose estimated to be more than 600 rad were set arbitrarily at 600 rad, since the average dose in the 200+ rad group would then change from 434 to 350 rad. In the 22year period from 1950 to 1972, a high mortality risk due to radiation was observed in survivors with doses of 200 rad and over for all cancers except leukemia. On the other hand, during the latest period from 1965 to 1972 a significant risk was noted also for stomach and breast cancers. Survivors who were 9 year old or less at the time of the bomb and who were exposed to high doses of 200+ rad appeared to show a high mortality risk for all cancers except leukemia, although the number of observed deaths is yet small. A number of interesting areas are discussed from the statistical and epidemiological standpoints, i.e., the numerical comparison of risks in various models, the general evaluation of cancer mortality by the additive logit model, the dose response relationship, the relative risk in the high dose group, the time period of radiation induced cancer mortality, the difference of dose response between Hiroshima and Nagasaki and the relative biological effectiveness of neutrons.

An Overview of Generalized Gamma Mittag–Leffler Model and Its Applications

Directory of Open Access Journals (Sweden)

Seema S. Nair

2015-08-01

Full Text Available Recently, probability models with thicker or thinner tails have gained more importance among statisticians and physicists because of their vast applications in random walks, Lévi flights, financial modeling, etc. In this connection, we introduce here a new family of generalized probability distributions associated with the Mittag–Leffler function. This family gives an extension to the generalized gamma family, opens up a vast area of potential applications and establishes connections to the topics of fractional calculus, nonextensive statistical mechanics, Tsallis statistics, superstatistics, the Mittag–Leffler stochastic process, the Lévi process and time series. Apart from examining the properties, the matrix-variate analogue and the connection to fractional calculus are also explained. By using the pathway model of Mathai, the model is further generalized. Connections to Mittag–Leffler distributions and corresponding autoregressive processes are also discussed.

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.

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

A Statistical Evaluation of Atmosphere-Ocean General Circulation Models: Complexity vs. Simplicity

OpenAIRE

Robert K. Kaufmann; David I. Stern

2004-01-01

The principal tools used to model future climate change are General Circulation Models which are deterministic high resolution bottom-up models of the global atmosphere-ocean system that require large amounts of supercomputer time to generate results. But are these models a cost-effective way of predicting future climate change at the global level? In this paper we use modern econometric techniques to evaluate the statistical adequacy of three general circulation models (GCMs) by testing thre...

Analysis of dental caries using generalized linear and count regression models

Directory of Open Access Journals (Sweden)

Javali M. Phil

2013-11-01

Full Text Available Generalized linear models (GLM are generalization of linear regression models, which allow fitting regression models to response data in all the sciences especially medical and dental sciences that follow a general exponential family. These are flexible and widely used class of such models that can accommodate response variables. Count data are frequently characterized by overdispersion and excess zeros. Zero-inflated count models provide a parsimonious yet powerful way to model this type of situation. Such models assume that the data are a mixture of two separate data generation processes: one generates only zeros, and the other is either a Poisson or a negative binomial data-generating process. Zero inflated count regression models such as the zero-inflated Poisson (ZIP, zero-inflated negative binomial (ZINB regression models have been used to handle dental caries count data with many zeros. We present an evaluation framework to the suitability of applying the GLM, Poisson, NB, ZIP and ZINB to dental caries data set where the count data may exhibit evidence of many zeros and over-dispersion. Estimation of the model parameters using the method of maximum likelihood is provided. Based on the Vuong test statistic and the goodness of fit measure for dental caries data, the NB and ZINB regression models perform better than other count regression models.

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

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...

Cloud-turbulence interactions: Sensitivity of a general circulation model to closure assumptions

International Nuclear Information System (INIS)

Brinkop, S.; Roeckner, E.

1993-01-01

Several approaches to parameterize the turbulent transport of momentum, heat, water vapour and cloud water for use in a general circulation model (GCM) have been tested in one-dimensional and three-dimensional model simulations. The schemes differ with respect to their closure assumptions (conventional eddy diffusivity model versus turbulent kinetic energy closure) and also regarding their treatment of cloud-turbulence interactions. The basis properties of these parameterizations are discussed first in column simulations of a stratocumulus-topped atmospheric boundary layer (ABL) under a strong subsidence inversion during the KONTROL experiment in the North Sea. It is found that the K-models tend to decouple the cloud layer from the adjacent layers because the turbulent activity is calculated from local variables. The higher-order scheme performs better in this respect because internally generated turbulence can be transported up and down through the action of turbulent diffusion. Thus, the TKE-scheme provides not only a better link between the cloud and the sub-cloud layer but also between the cloud and the inversion as a result of cloud-top entrainment. In the stratocumulus case study, where the cloud is confined by a pronounced subsidence inversion, increased entrainment favours cloud dilution through enhanced evaporation of cloud droplets. In the GCM study, however, additional cloud-top entrainment supports cloud formation because indirect cloud generating processes are promoted through efficient ventilation of the ABL, such as the enhanced moisture supply by surface evaporation and the increased depth of the ABL. As a result, tropical convection is more vigorous, the hydrological cycle is intensified, the whole troposphere becomes warmer and moister in general and the cloudiness in the upper part of the ABL is increased. (orig.)

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...

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.

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.

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.

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/).

Generalized Continuum: from Voigt to the Modeling of Quasi-Brittle Materials

Directory of Open Access Journals (Sweden)

Jamile Salim Fuina

2010-12-01

Full Text Available This article discusses the use of the generalized continuum theories to incorporate the effects of the microstructure in the nonlinear finite element analysis of quasi-brittle materials and, thus, to solve mesh dependency problems. A description of the problem called numerically induced strain localization, often found in Finite Element Method material non-linear analysis, is presented. A brief historic about the Generalized Continuum Mechanics based models is presented, since the initial work of Voigt (1887 until the more recent studies. By analyzing these models, it is observed that the Cosserat and microstretch approaches are particular cases of a general formulation that describes the micromorphic continuum. After reporting attempts to incorporate the material microstructure in Classical Continuum Mechanics based models, the article shows the recent tendency of doing it according to assumptions of the Generalized Continuum Mechanics. Finally, it presents numerical results which enable to characterize this tendency as a promising way to solve the problem.

The achievement impact of the inclusion model on the standardized test scores of general education students

Science.gov (United States)

Garrett-Rainey, Syrena

The purpose of this study was to compare the achievement of general education students within regular education classes to the achievement of general education students in inclusion/co-teach classes to determine whether there was a significant difference in the achievement between the two groups. The school district's inclusion/co-teach model included ongoing professional development support for teachers and administrators. General education teachers, special education teachers, and teacher assistants collaborated to develop instructional strategies to provide additional remediation to help students to acquire the skills needed to master course content. This quantitative study reviewed the end-of course test (EoCT) scores of Grade 10 physical science and math students within an urban school district. It is not known whether general education students in an inclusive/co-teach science or math course will demonstrate a higher achievement on the EoCT in math or science than students not in an inclusive/co-teach classroom setting. In addition, this study sought to determine if students classified as low socioeconomic status benefited from participating in co-teaching classrooms as evidenced by standardized tests. Inferential statistics were used to determine whether there was a significant difference between the achievements of the treatment group (inclusion/co-teach) and the control group (non-inclusion/co-teach). The findings can be used to provide school districts with optional instructional strategies to implement in the diverse classroom setting in the modern classroom to increase academic performance on state standardized tests.

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.

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

Science.gov (United States)

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

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

Simulation of reactive nanolaminates using reduced models: III. Ingredients for a general multidimensional formulation

Energy Technology Data Exchange (ETDEWEB)

Salloum, Maher; Knio, Omar M. [Department of Mechanical Engineering, The Johns Hopkins University, Baltimore, MD 21218-2686 (United States)

2010-06-15

A transient multidimensional reduced model is constructed for the simulation of reaction fronts in Ni/Al multilayers. The formulation is based on the generalization of earlier methodologies developed for quasi-1D axial and normal propagation, specifically by adapting the reduced formalism for atomic mixing and heat release. This approach enables us to focus on resolving the thermal front structure, whose evolution is governed by thermal diffusion and heat release. A mixed integration scheme is used for this purpose, combining an extended-stability, Runge-Kutta-Chebychev (RKC) integration of the diffusion term with exact treatment of the chemical source term. Thus, a detailed description of atomic mixing within individual layers is avoided, which enables transient modeling of the reduced equations of motion in multiple dimensions. Two-dimensional simulations are first conducted of front propagation in composites combining two bilayer periods. Results are compared with the experimental measurements of Knepper et al., which reveal that the reaction velocity can depend significantly on layering frequency. The comparison indicates that, using a concentration-dependent conductivity model, the transient 2D computations can reasonably reproduce the experimental behavior. Additional tests are performed based on 3D computations of surface initiated reactions. Comparison of computed predictions with laser ignition measurements indicates that the computations provide reasonable estimates of ignition thresholds. A detailed discussion is finally provided of potential generalizations and associated hurdles. (author)

Modeling and Simulation of Multi-scale Environmental Systems with Generalized Hybrid Petri Nets

Directory of Open Access Journals (Sweden)

Mostafa eHerajy

2015-07-01

Full Text Available Predicting and studying the dynamics and properties of environmental systems necessitates the construction and simulation of mathematical models entailing different levels of complexities. Such type of computational experiments often require the combination of discrete and continuous variables as well as processes operating at different time scales. Furthermore, the iterative steps of constructing and analyzing environmental models might involve researchers with different background. Hybrid Petri nets may contribute in overcoming such challenges as they facilitate the implementation of systems integrating discrete and continuous dynamics. Additionally, the visual depiction of model components will inevitably help to bridge the gap between scientists with distinct expertise working on the same problem. Thus, modeling environmental systems with hybrid Petri nets enables the construction of complex processes while keeping the models comprehensible for researchers working on the same project with significantly divergent education path. In this paper we propose the utilization of a special class of hybrid Petri nets, Generalized Hybrid Petri Nets (GHPN, to model and simulate environmental systems exposing processes interacting at different time-scales. GHPN integrate stochastic and deterministic semantics as well as other types of special basic events. Moreover, a case study is presented to illustrate the use of GHPN in constructing and simulating multi-timescale environmental scenarios.

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.

On a generalized Dirac oscillator interaction for the nonrelativistic limit 3 D generalized SUSY model oscillator Hamiltonian of Celka and Hussin

International Nuclear Information System (INIS)

Jayaraman, Jambunatha; Lima Rodrigues, R. de

1994-01-01

In the context of the 3 D generalized SUSY model oscillator Hamiltonian of Celka and Hussin (CH), a generalized Dirac oscillator interaction is studied, that leads, in the non-relativistic limit considered for both signs of energy, to the CH's generalized 3 D SUSY oscillator. The relevance of this interaction to the CH's SUSY model and the SUSY breaking dependent on the Wigner parameter is brought out. (author). 6 refs

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...

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

Estimation of group means when adjusting for covariates in generalized linear models.

Science.gov (United States)

Qu, Yongming; Luo, Junxiang

2015-01-01

Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.

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

Science.gov (United States)

Molenaar, Dylan; Bolsinova, Maria

2017-05-01

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

Simulations of physics and chemistry of polar stratospheric clouds with a general circulation model

Energy Technology Data Exchange (ETDEWEB)

Buchholz, J.

2005-04-20

A polar stratospheric cloud submodel has been developed and incorporated in a general circulation model including atmospheric chemistry (ECHAM5/MESSy). The formation and sedimentation of polar stratospheric cloud (PSC) particles can thus be simulated as well as heterogeneous chemical reactions that take place on the PSC particles. For solid PSC particle sedimentation, the need for a tailor-made algorithm has been elucidated. A sedimentation scheme based on first order approximations of vertical mixing ratio profiles has been developed. It produces relatively little numerical diffusion and can deal well with divergent or convergent sedimentation velocity fields. For the determination of solid PSC particle sizes, an efficient algorithm has been adapted. It assumes a monodisperse radii distribution and thermodynamic equilibrium between the gas phase and the solid particle phase. This scheme, though relatively simple, is shown to produce particle number densities and radii within the observed range. The combined effects of the representations of sedimentation and solid PSC particles on vertical H{sub 2}O and HNO{sub 3} redistribution are investigated in a series of tests. The formation of solid PSC particles, especially of those consisting of nitric acid trihydrate, has been discussed extensively in recent years. Three particle formation schemes in accordance with the most widely used approaches have been identified and implemented. For the evaluation of PSC occurrence a new data set with unprecedented spatial and temporal coverage was available. A quantitative method for the comparison of simulation results and observations is developed and applied. It reveals that the relative PSC sighting frequency can be reproduced well with the PSC submodel whereas the detailed modelling of PSC events is beyond the scope of coarse global scale models. In addition to the development and evaluation of new PSC submodel components, parts of existing simulation programs have been

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

Infinite additional symmetries in two-dimensional conformal quantum field theory

International Nuclear Information System (INIS)

Zamolodchikov, A.B.

1986-01-01

This paper investigates additional symmetries in two-dimensional conformal field theory generated by spin s = 1/2, 1,...,3 currents. For spins s = 5/2 and s = 3, the generators of the symmetry form associative algebras with quadratic determining relations. ''Minimal models'' of conforma field theory with such additional symmetries are considered. The space of local fields occurring in a conformal field theory with additional symmetry corresponds to a certain (in general, reducible) representation of the corresponding algebra of the symmetry

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)

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.

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

Transition between extinction and blow-up in a generalized Fisher–KPP model

Energy Technology Data Exchange (ETDEWEB)

Hernández-Bermejo, Benito, E-mail: benito.hernandez@urjc.es [Departamento de Física, Universidad Rey Juan Carlos, Calle Tulipán S/N, 28933, Móstoles, Madrid (Spain); Sánchez-Valdés, Ariel [Departamento de Matemática Aplicada, Universidad Rey Juan Carlos, Calle Tulipán S/N, 28933, Móstoles, Madrid (Spain)

2014-05-01

Stationary solutions of the Fisher–KPP equation with general nonlinear diffusion and arbitrary reactional kinetic orders terms are characterized. Such stationary (separatrix-like) solutions disjoint the blow-up solutions from those showing extinction. In addition a criterion for general parameter values is presented, which allows determining the blow-up or vanishing character of the solutions.

Transition between extinction and blow-up in a generalized Fisher–KPP model

International Nuclear Information System (INIS)

Hernández-Bermejo, Benito; Sánchez-Valdés, Ariel

2014-01-01

Stationary solutions of the Fisher–KPP equation with general nonlinear diffusion and arbitrary reactional kinetic orders terms are characterized. Such stationary (separatrix-like) solutions disjoint the blow-up solutions from those showing extinction. In addition a criterion for general parameter values is presented, which allows determining the blow-up or vanishing character of the solutions.

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

A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

Science.gov (United States)

Quilodrán, Claudio S; Currat, Mathias; Montoya-Burgos, Juan I

2014-01-01

Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

A General Model of Distant Hybridization Reveals the Conditions for Extinction in Atlantic Salmon and Brown Trout

Science.gov (United States)

Quilodrán, Claudio S.; Currat, Mathias; Montoya-Burgos, Juan I.

2014-01-01

Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as “distant hybridization,” the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action. PMID:25003336

A general model of distant hybridization reveals the conditions for extinction in Atlantic salmon and brown trout.

Directory of Open Access Journals (Sweden)

Claudio S Quilodrán

Full Text Available Interspecific hybridization is common in nature but can be increased in frequency or even originated by human actions, such as species introduction or habitat modification, which may threaten species persistence. When hybridization occurs between distantly related species, referred to as "distant hybridization," the resulting hybrids are generally infertile or fertile but do not undergo chromosomal recombination during gametogenesis. Here, we present a model describing this frequent but poorly studied interspecific hybridization to assess its consequences on parental species and to anticipate the conditions under which they can reach extinction. Our general model fully incorporates three important processes: density-dependent competition, dominance/recessivity inheritance of traits and assortative mating. We demonstrate its use and flexibility by assessing population extinction risk between Atlantic salmon and brown trout in Norway, whose interbreeding has recently increased due to farmed fish releases into the wild. We identified the set of conditions under which hybridization may threaten salmonid species. Thanks to the flexibility of our model, we evaluated the effect of an additional risk factor, a parasitic disease, and showed that the cumulative effects dramatically increase the extinction risk. The consequences of distant hybridization are not genetically, but demographically mediated. Our general model is useful to better comprehend the evolution of such hybrid systems and we demonstrated its importance in the field of conservation biology to set up management recommendations when this increasingly frequent type of hybridization is in action.

Comparison of body composition between fashion models and women in general

OpenAIRE

Park, Sunhee

2017-01-01

[Purpose] The present study compared the physical characteristics and body composition of professional fashion models and women in general, utilizing the skinfold test. [Methods] The research sample consisted of 90 professional fashion models presently active in Korea and 100 females in the general population, all selected through convenience sampling. Measurement was done following standardized methods and procedures set by the International Society for the Advancement of Kinanthropometry. B...

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.

The algebra of the general Markov model on phylogenetic trees and networks.

Science.gov (United States)

Sumner, J G; Holland, B R; Jarvis, P D

2012-04-01

It is known that the Kimura 3ST model of sequence evolution on phylogenetic trees can be extended quite naturally to arbitrary split systems. However, this extension relies heavily on mathematical peculiarities of the associated Hadamard transformation, and providing an analogous augmentation of the general Markov model has thus far been elusive. In this paper, we rectify this shortcoming by showing how to extend the general Markov model on trees to include incompatible edges; and even further to more general network models. This is achieved by exploring the algebra of the generators of the continuous-time Markov chain together with the “splitting” operator that generates the branching process on phylogenetic trees. For simplicity, we proceed by discussing the two state case and then show that our results are easily extended to more states with little complication. Intriguingly, upon restriction of the two state general Markov model to the parameter space of the binary symmetric model, our extension is indistinguishable from the Hadamard approach only on trees; as soon as any incompatible splits are introduced the two approaches give rise to differing probability distributions with disparate structure. Through exploration of a simple example, we give an argument that our extension to more general networks has desirable properties that the previous approaches do not share. In particular, our construction allows for convergent evolution of previously divergent lineages; a property that is of significant interest for biological applications.

A generalized Fellner-Schall method for smoothing parameter optimization with application to Tweedie location, scale and shape models.

Science.gov (United States)

Wood, Simon N; Fasiolo, Matteo

2017-12-01

We consider the optimization of smoothing parameters and variance components in models with a regular log likelihood subject to quadratic penalization of the model coefficients, via a generalization of the method of Fellner (1986) and Schall (1991). In particular: (i) we generalize the original method to the case of penalties that are linear in several smoothing parameters, thereby covering the important cases of tensor product and adaptive smoothers; (ii) we show why the method's steps increase the restricted marginal likelihood of the model, that it tends to converge faster than the EM algorithm, or obvious accelerations of this, and investigate its relation to Newton optimization; (iii) we generalize the method to any Fisher regular likelihood. The method represents a considerable simplification over existing methods of estimating smoothing parameters in the context of regular likelihoods, without sacrificing generality: for example, it is only necessary to compute with the same first and second derivatives of the log-likelihood required for coefficient estimation, and not with the third or fourth order derivatives required by alternative approaches. Examples are provided which would have been impossible or impractical with pre-existing Fellner-Schall methods, along with an example of a Tweedie location, scale and shape model which would be a challenge for alternative methods, and a sparse additive modeling example where the method facilitates computational efficiency gains of several orders of magnitude. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017, The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Comparison of prosthetic models produced by traditional and additive manufacturing methods.

Science.gov (United States)

Park, Jin-Young; Kim, Hae-Young; Kim, Ji-Hwan; Kim, Jae-Hong; Kim, Woong-Chul

2015-08-01

The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (α=.05). The mean marginal gaps and internal gaps showed significant differences according to tooth type (Pmanufacturing method (Pmanufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing.

A general 3-D nonlinear magnetostrictive constitutive model for soft ferromagnetic materials

International Nuclear Information System (INIS)

Zhou Haomiao; Zhou Youhe; Zheng Xiaojing; Ye Qiang; Wei Jing

2009-01-01

In this paper, a new general nonlinear magnetostrictive constitutive model is proposed for soft ferromagnetic materials, and it can predict magnetostrictive strain and magnetization curves under various pre-stresses. From the viewpoint of magnetic domain, it is based on the important physical fact that a nonlinear part of the elastic strain produced by magnetic domain wall motion under a pre-stress is responsible for the change of the maximum magnetostrictive strain in accordance with the pre-stress. Then the reduction of magnetostrictive strain from the maximum is caused by the domain rotation. Meanwhile, the magnetization under various pre-stresses in this model is introduced by magnetostrictive effect under the same pre-stress. A simplified 3-D model is put forward by means of linearizing the nonlinear function, i.e. the nonlinear part of the elastic strain produced by domain wall motion, and by using the quartic of magnetization to describe domain rotation. Besides, for the convenience of engineering applications, two-dimensional (plate or film) and one-dimensional (rod) models are also given for isotropic materials and their application ranges are discussed too. In comparison with the experimental data of Kuruzar and Jiles, it is found that this model can predict magnetostrictive strain and magnetization curves under various pre-stresses. The numerical simulation further illustrates that the new model can effectively describe the effects of the pre-stress or residual stress on the magnetization and magnetostrictive strain curves. Additionally, this model can be degenerated to the existing magnetostrictive constitutive model for giant magnetostrictive materials (GMM), i.e. a special soft ferromagnetic material

Explained variation and predictive accuracy in general parametric statistical models: the role of model misspecification

DEFF Research Database (Denmark)

Rosthøj, Susanne; Keiding, Niels

2004-01-01

When studying a regression model measures of explained variation are used to assess the degree to which the covariates determine the outcome of interest. Measures of predictive accuracy are used to assess the accuracy of the predictions based on the covariates and the regression model. We give a ...... a detailed and general introduction to the two measures and the estimation procedures. The framework we set up allows for a study of the effect of misspecification on the quantities estimated. We also introduce a generalization to survival analysis....

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

Setting a generalized functional linear model (GFLM for the classification of different types of cancer

Directory of Open Access Journals (Sweden)

Miguel Flores

2016-11-01

Full Text Available This work aims to classify the DNA sequences of healthy and malignant cancer respectively. For this, supervised and unsupervised classification methods from a functional context are used; i.e. each strand of DNA is an observation. The observations are discretized, for that reason different ways to represent these observations with functions are evaluated. In addition, an exploratory study is done: estimating the mean and variance of each functional type of cancer. For the unsupervised classification method, hierarchical clustering with different measures of functional distance is used. On the other hand, for the supervised classification method, a functional generalized linear model is used. For this model the first and second derivatives are used which are included as discriminating variables. It has been verified that one of the advantages of working in the functional context is to obtain a model to correctly classify cancers by 100%. For the implementation of the methods it has been used the fda.usc R package that includes all the techniques of functional data analysis used in this work. In addition, some that have been developed in recent decades. For more details of these techniques can be consulted Ramsay, J. O. and Silverman (2005 and Ferraty et al. (2006.

Fine-mapping additive and dominant SNP effects using group-LASSO and Fractional Resample Model Averaging

Science.gov (United States)

Sabourin, Jeremy; Nobel, Andrew B.; Valdar, William

2014-01-01

Genomewide association studies sometimes identify loci at which both the number and identities of the underlying causal variants are ambiguous. In such cases, statistical methods that model effects of multiple SNPs simultaneously can help disentangle the observed patterns of association and provide information about how those SNPs could be prioritized for follow-up studies. Current multi-SNP methods, however, tend to assume that SNP effects are well captured by additive genetics; yet when genetic dominance is present, this assumption translates to reduced power and faulty prioritizations. We describe a statistical procedure for prioritizing SNPs at GWAS loci that efficiently models both additive and dominance effects. Our method, LLARRMA-dawg, combines a group LASSO procedure for sparse modeling of multiple SNP effects with a resampling procedure based on fractional observation weights; it estimates for each SNP the robustness of association with the phenotype both to sampling variation and to competing explanations from other SNPs. In producing a SNP prioritization that best identifies underlying true signals, we show that: our method easily outperforms a single marker analysis; when additive-only signals are present, our joint model for additive and dominance is equivalent to or only slightly less powerful than modeling additive-only effects; and, when dominance signals are present, even in combination with substantial additive effects, our joint model is unequivocally more powerful than a model assuming additivity. We also describe how performance can be improved through calibrated randomized penalization, and discuss how dominance in ungenotyped SNPs can be incorporated through either heterozygote dosage or multiple imputation. PMID:25417853

[A competency model of rural general practitioners: theory construction and empirical study].

Science.gov (United States)

Yang, Xiu-Mu; Qi, Yu-Long; Shne, Zheng-Fu; Han, Bu-Xin; Meng, Bei

2015-04-01

To perform theory construction and empirical study of the competency model of rural general practitioners. Through literature study, job analysis, interviews, and expert team discussion, the questionnaire of rural general practitioners competency was constructed. A total of 1458 rural general practitioners were surveyed by the questionnaire in 6 central provinces. The common factors were constructed using the principal component method of exploratory factor analysis and confirmatory factor analysis. The influence of the competency characteristics on the working performance was analyzed using regression equation analysis. The Cronbach 's alpha coefficient of the questionnaire was 0.974. The model consisted of 9 dimensions and 59 items. The 9 competency dimensions included basic public health service ability, basic clinical skills, system analysis capability, information management capability, communication and cooperation ability, occupational moral ability, non-medical professional knowledge, personal traits and psychological adaptability. The rate of explained cumulative total variance was 76.855%. The model fitting index were Χ(2)/df 1.88, GFI=0.94, NFI=0.96, NNFI=0.98, PNFI=0.91, RMSEA=0.068, CFI=0.97, IFI=0.97, RFI=0.96, suggesting good model fitting. Regression analysis showed that the competency characteristics had a significant effect on job performance. The rural general practitioners competency model provides reference for rural doctor training, rural order directional cultivation of medical students, and competency performance management of the rural general practitioners.

Davidson's generalization of the Fenyes-Nelson stochastic model of quantum mechanics

International Nuclear Information System (INIS)

Shucker, D.S.

1980-01-01

Davidson's generalization of the Fenyes-Nelson stochastic model of quantum mechanics is discussed. It is shown that this author's previous results concerning the Fenyes-Nelson process extend to the more general theory of Davidson. (orig.)

Generalized Whittle-Matern random field as a model of correlated fluctuations

International Nuclear Information System (INIS)

Lim, S C; Teo, L P

2009-01-01

This paper considers a generalization of the Gaussian random field with covariance function of the Whittle-Matern family. Such a random field can be obtained as the solution to the fractional stochastic differential equation with two fractional orders. Asymptotic properties of the covariance functions belonging to this generalized Whittle-Matern family are studied, which are used to deduce the sample path properties of the random field. The Whittle-Matern field has been widely used in modeling geostatistical data such as sea beam data, wind speed, field temperature and soil data. In this paper we show that the generalized Whittle-Matern field provides a more flexible model for wind speed data

Using video modeling for generalizing toy play in children with autism.

Science.gov (United States)

Paterson, Claire R; Arco, Lucius

2007-09-01

The present study examined effects of video modeling on generalized independent toy play of two boys with autism. Appropriate and repetitive verbal and motor play were measured, and intermeasure relationships were examined. Two single-participant experiments with multiple baselines and withdrawals across toy play were used. One boy was presented with three physically unrelated toys, whereas the other was presented with three related toys. Video modeling produced increases in appropriate play and decreases in repetitive play, but generalized play was observed only with the related toys. Generalization may have resulted from variables including the toys' common physical characteristics and natural reinforcing properties and the increased correspondence between verbal and motor play.

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...

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.

Verification and Validation of a Three-Dimensional Generalized Composite Material Model

Science.gov (United States)

Hoffarth, Canio; Harrington, Joseph; Rajan, Subramaniam D.; Goldberg, Robert K.; Carney, Kelly S.; DuBois, Paul; Blankenhorn, Gunther

2015-01-01

A general purpose orthotropic elasto-plastic computational constitutive material model has been developed to improve predictions of the response of composites subjected to high velocity impact. The three-dimensional orthotropic elasto-plastic composite material model is being implemented initially for solid elements in LS-DYNA as MAT213. In order to accurately represent the response of a composite, experimental stress-strain curves are utilized as input, allowing for a more general material model that can be used on a variety of composite applications. The theoretical details are discussed in a companion paper. This paper documents the implementation, verification and qualitative validation of the material model using the T800-F3900 fiber/resin composite material

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

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.

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 ...

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 ...

Generalized free-space diffuse photon transport model based on the influence analysis of a camera lens diaphragm.

Science.gov (United States)

Chen, Xueli; Gao, Xinbo; Qu, Xiaochao; Chen, Duofang; Ma, Xiaopeng; Liang, Jimin; Tian, Jie

2010-10-10

The camera lens diaphragm is an important component in a noncontact optical imaging system and has a crucial influence on the images registered on the CCD camera. However, this influence has not been taken into account in the existing free-space photon transport models. To model the photon transport process more accurately, a generalized free-space photon transport model is proposed. It combines Lambertian source theory with analysis of the influence of the camera lens diaphragm to simulate photon transport process in free space. In addition, the radiance theorem is also adopted to establish the energy relationship between the virtual detector and the CCD camera. The accuracy and feasibility of the proposed model is validated with a Monte-Carlo-based free-space photon transport model and physical phantom experiment. A comparison study with our previous hybrid radiosity-radiance theorem based model demonstrates the improvement performance and potential of the proposed model for simulating photon transport process in free space.

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

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.

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.

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.

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.

Computable General Equilibrium Model Fiscal Year 2013 Capability Development Report - April 2014

Energy Technology Data Exchange (ETDEWEB)

Edwards, Brian Keith [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). National Infrastructure Simulation and Analysis Center (NISAC); Rivera, Michael K. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). National Infrastructure Simulation and Analysis Center (NISAC); Boero, Riccardo [Los Alamos National Lab. (LANL), Los Alamos, NM (United States). National Infrastructure Simulation and Analysis Center (NISAC)

2014-04-01

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.

A general tank test of a model of the hull of the Pem-1 flying boat including a special working chart for the determination of hull performance

Science.gov (United States)

Dawson, John R

1938-01-01

The results of a general tank test of a 1/6 full-size model of the hull of the Pem-1 flying boat (N.A.C.A. model 18) are given in non-dimensional form. In addition to the usual curves, the results are presented in a new form that makes it possible to apply them more conveniently than in the forms previously used. The resistance was compared with that of N.A.C.A. models 11-C and 26(Sikorsky S-40) and was found to be generally less than the resistance of either.

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...

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.

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

General extrapolation model for an important chemical dose-rate effect

International Nuclear Information System (INIS)

Gillen, K.T.; Clough, R.L.

1984-12-01

In order to extrapolate material accelerated aging data, methodologies must be developed based on sufficient understanding of the processes leading to material degradation. One of the most important mechanisms leading to chemical dose-rate effects in polymers involves the breakdown of intermediate hydroperoxide species. A general model for this mechanism is derived based on the underlying chemical steps. The results lead to a general formalism for understanding dose rate and sequential aging effects when hydroperoxide breakdown is important. We apply the model to combined radiation/temperature aging data for a PVC material and show that this data is consistent with the model and that model extrapolations are in excellent agreement with 12-year real-time aging results from an actual nuclear plant. This model and other techniques discussed in this report can aid in the selection of appropriate accelerated aging methods and can also be used to compare and select materials for use in safety-related components. This will result in increased assurance that equipment qualification procedures are adequate

Orographic effects on tropical climate in a coupled ocean-atmosphere general circulation model

Science.gov (United States)

Okajima, Hideki

Large-scale mountain modifies the atmospheric circulation directly through dynamic and thermodynamic process, and also indirectly through the interaction with the ocean. To investigate orographic impacts on tropical climate, a fully coupled general circulation model (CGCM) is developed by coupling a state-of-the-art atmospheric general circulation model and an ocean general circulation model. With realistic boundary conditions, the CGCM produces a reasonable climatology of sea surface temperature (SST), surface winds, and precipitation. When global mountains are removed, the model climatology displays substantial changes in both the mean-state and the seasonal cycle. The equatorial eastern Pacific SST acquires a semi-annual component as inter-tropical convergence zone (ITCZ) flips and flops across the equator following the seasonal migration of the sun. Without the Andes, wet air flows into the southeastern tropical Pacific from the humid Amazon, which weakens the meridional asymmetry during the Peruvian warm season (February-April). In addition, the northeasterly trade winds are enhanced north of the equator without the orographic blocking of Central American mountains and cools SST. Triggered by the SST cooling north and moistening south of the equator, the wind-evaporation-SST (WES) feedback further weakens the meridional asymmetry and prolongs the southern ITCZ. In the Atlantic Ocean, the equatorial cold tongue is substantially strengthened and develops a pronounced annual cycle in the absence of mountains. The easterly winds are overall enhanced over the equatorial Atlantic without orographic heating over the African highlands, developing a zonal asymmetry strengthened by the Bjerknes feedback. In the Indian Ocean, the thermocline shoals eastward and an equatorial cold tongue appears twice a year. During boreal summer, the Findlater jet is greatly weakened off Somalia and SST warms in the western Indian Ocean, forcing the equatorial easterly winds amplified

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

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.

A General Model for Thermal, Hydraulic and Electric Analysis of Superconducting Cables

CERN Document Server

Bottura, L; Rosso, C

2000-01-01

In this paper we describe a generic, multi-component and multi-channel model for the analysis of superconducting cables. The aim of the model is to treat in a general and consistent manner simultaneous thermal, electric and hydraulic transients in cables. The model is devised for most general situations, but reduces in limiting cases to most common approximations without loss of efficiency. We discuss here the governing equations, and we write them in a matrix form that is well adapted to numerical treatment. We finally demonstrate the model capability by comparison with published experimental data on current distribution in a two-strand cable.

Multiple-event probability in general-relativistic quantum mechanics. II. A discrete model

International Nuclear Information System (INIS)

Mondragon, Mauricio; Perez, Alejandro; Rovelli, Carlo

2007-01-01

We introduce a simple quantum mechanical model in which time and space are discrete and periodic. These features avoid the complications related to continuous-spectrum operators and infinite-norm states. The model provides a tool for discussing the probabilistic interpretation of generally covariant quantum systems, without the confusion generated by spurious infinities. We use the model to illustrate the formalism of general-relativistic quantum mechanics, and to test the definition of multiple-event probability introduced in a companion paper [Phys. Rev. D 75, 084033 (2007)]. We consider a version of the model with unitary time evolution and a version without unitary time evolution

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

Testing a generalized cubic Galileon gravity model with the Coma Cluster

Energy Technology Data Exchange (ETDEWEB)

Terukina, Ayumu; Yamamoto, Kazuhiro; Okabe, Nobuhiro [Department of Physical Sciences, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8526 (Japan); Matsushita, Kyoko; Sasaki, Toru, E-mail: telkina@theo.phys.sci.hiroshima-u.ac.jp, E-mail: kazuhiro@hiroshima-u.ac.jp, E-mail: okabe@hiroshima-u.ac.jp, E-mail: matusita@rs.kagu.tus.ac.jp, E-mail: j1213703@ed.tus.ac.jp [Department of Physics, Tokyo University of Science, 1-3 Kagurazaka, Shinjuku-ku, Tokyo 162-8601 (Japan)

2015-10-01

We obtain a constraint on the parameters of a generalized cubic Galileon gravity model exhibiting the Vainshtein mechanism by using multi-wavelength observations of the Coma Cluster. The generalized cubic Galileon model is characterized by three parameters of the turning scale associated with the Vainshtein mechanism, and the amplitude of modifying a gravitational potential and a lensing potential. X-ray and Sunyaev-Zel'dovich (SZ) observations of the intra-cluster medium are sensitive to the gravitational potential, while the weak-lensing (WL) measurement is specified by the lensing potential. A joint fit of a complementary multi-wavelength dataset of X-ray, SZ and WL measurements enables us to simultaneously constrain these three parameters of the generalized cubic Galileon model for the first time. We also find a degeneracy between the cluster mass parameters and the gravitational modification parameters, which is influential in the limit of the weak screening of the fifth force.

A NEW GENERAL 3DOF QUASI-STEADY AERODYNAMIC INSTABILITY MODEL

DEFF Research Database (Denmark)

Gjelstrup, Henrik; Larsen, Allan; Georgakis, Christos

2008-01-01

but can generally be applied for aerodynamic instability prediction for prismatic bluff bodies. The 3DOF, which make up the movement of the model, are the displacements in the XY-plane and the rotation around the bluff body’s rotational axis. The proposed model incorporates inertia coupling between...

The microcomputer scientific software series 2: general linear model--regression.

Science.gov (United States)

Harold M. Rauscher

1983-01-01

The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...

Particles and holes equivalence for generalized seniority and the interacting boson model

International Nuclear Information System (INIS)

Talmi, I.

1982-01-01

An apparent ambiguity was recently reported in coupling either pairs of identical fermions or hole pairs. This is explained here as due to a Hamiltonian whose lowest eigenstates do not have the structure prescribed by generalized seniority. It is shown that generalized seniority eigenstates can be equivalently constructed from correlated J = 0 and J = 2 pair states of either particles or holes. The interacting boson model parameters calculated can be unambiguously interpreted and then are of real interest to the shell model basis of interacting boson model

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

A nested Atlantic-Mediterranean Sea general circulation model for operational forecasting

Directory of Open Access Journals (Sweden)

P. Oddo

2009-10-01

Full Text Available A new numerical general circulation ocean model for the Mediterranean Sea has been implemented nested within an Atlantic general circulation model within the framework of the Marine Environment and Security for the European Area project (MERSEA, Desaubies, 2006. A 4-year twin experiment was carried out from January 2004 to December 2007 with two different models to evaluate the impact on the Mediterranean Sea circulation of open lateral boundary conditions in the Atlantic Ocean. One model considers a closed lateral boundary in a large Atlantic box and the other is nested in the same box in a global ocean circulation model. Impact was observed comparing the two simulations with independent observations: ARGO for temperature and salinity profiles and tide gauges and along-track satellite observations for the sea surface height. The improvement in the nested Atlantic-Mediterranean model with respect to the closed one is particularly evident in the salinity characteristics of the Modified Atlantic Water and in the Mediterranean sea level seasonal variability.