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

DOT National Transportation Integrated Search

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...

Online Statistical Modeling (Regression Analysis) for Independent Responses

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

A Generalized Information Theoretical Model for Quantum Secret Sharing

NASA Astrophysics Data System (ADS)

Bai, Chen-Ming; Li, Zhi-Hui; Xu, Ting-Ting; Li, Yong-Ming

2016-11-01

An information theoretical model for quantum secret sharing was introduced by H. Imai et al. (Quantum Inf. Comput. 5(1), 69-80 2005), which was analyzed by quantum information theory. In this paper, we analyze this information theoretical model using the properties of the quantum access structure. By the analysis we propose a generalized model definition for the quantum secret sharing schemes. In our model, there are more quantum access structures which can be realized by our generalized quantum secret sharing schemes than those of the previous one. In addition, we also analyse two kinds of important quantum access structures to illustrate the existence and rationality for the generalized quantum secret sharing schemes and consider the security of the scheme by simple examples.

Differential effects of adding and removing components of a context on the generalization of conditional freezing.

PubMed

González, Felisa; Quinn, Jennifer J; Fanselow, Michael S

2003-01-01

Rats were conditioned across 2 consecutive days where a single unsignaled footshock was presented in the presence of specific contextual cues. Rats were tested with contexts that had additional stimulus components either added or subtracted. Using freezing as a measure of conditioning, removal but not addition of a cue from the training context produced significant generalization decrement. The results are discussed in relation to the R. A. Rescorla and A. R. Wagner (1972), J. M. Pearce (1994), and A. R. Wagner and S. E. Brandon (2001) accounts of generalization. Although the present data are most consistent with elemental models such as Rescorla and Wagner, a slight modification of the Wagner-Brandon replaced-elements model that can account for differences in the pattern of generalization obtained with contexts and discrete conditional stimuli is proposed.

The stay/switch model describes choice among magnitudes of reinforcers.

PubMed

MacDonall, James S

2008-06-01

The stay/switch model is an alternative to the generalized matching law for describing choice in concurrent procedures. The purpose of the present experiment was to extend this model to choice among magnitudes of reinforcers. Rats were exposed to conditions in which the magnitude of reinforcers (number of food pellets) varied for staying at alternative 1, switching from alternative 1, staying at alternative 2 and switching from alternative 2. A changeover delay was not used. The results showed that the stay/switch model provided a good account of the data overall, and deviations from fits of the generalized matching law to response allocation data were in the direction predicted by the stay/switch model. In addition, comparisons among specific conditions suggested that varying the ratio of obtained reinforcers, as in the generalized matching law, was not necessary to change the response and time allocations. Other comparisons suggested that varying the ratio of obtained reinforcers was not sufficient to change response allocation. Taken together these results provide additional support for the stay/switch model of concurrent choice.

Integrability and superintegrability of the generalized n-level many-mode Jaynes-Cummings and Dicke models

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

Skrypnyk, T.

2009-10-15

We analyze symmetries of the integrable generalizations of Jaynes-Cummings and Dicke models associated with simple Lie algebras g and their reductive subalgebras g{sub K}[T. Skrypnyk, 'Generalized n-level Jaynes-Cummings and Dicke models, classical rational r-matrices and nested Bethe ansatz', J. Phys. A: Math. Theor. 41, 475202 (2008)]. We show that their symmetry algebras contain commutative subalgebras isomorphic to the Cartan subalgebras of g, which can be added to the commutative algebras of quantum integrals generated with the help of the quantum Lax operators. We diagonalize additional commuting integrals and constructed with their help the most general integrable quantum Hamiltonian of themore » generalized n-level many-mode Jaynes-Cummings and Dicke-type models using nested algebraic Bethe ansatz.« less

A general diagnostic model applied to language testing data.

PubMed

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.

Variable Complexity Structural Optimization of Shells

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Venkataraman, Satchi

1999-01-01

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-2110 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition, several modeling issues for the design of shells of revolution were studied.

Variable Complexity Structural Optimization of Shells

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Venkataraman, Satchi

1998-01-01

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-1808 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition several modeling issues for the design of shells of revolution were studied.

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

ERIC Educational Resources Information Center

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 virial theorem for massless electrons in graphene and other Dirac materials

NASA Astrophysics Data System (ADS)

Sokolik, A. A.; Zabolotskiy, A. D.; Lozovik, Yu. E.

2016-05-01

The virial theorem for a system of interacting electrons in a crystal, which is described within the framework of the tight-binding model, is derived. We show that, in the particular case of interacting massless electrons in graphene and other Dirac materials, the conventional virial theorem is violated. Starting from the tight-binding model, we derive the generalized virial theorem for Dirac electron systems, which contains an additional term associated with a momentum cutoff at the bottom of the energy band. Additionally, we derive the generalized virial theorem within the Dirac model using the minimization of the variational energy. The obtained theorem is illustrated by many-body calculations of the ground-state energy of an electron gas in graphene carried out in Hartree-Fock and self-consistent random-phase approximations. Experimental verification of the theorem in the case of graphene is discussed.

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

PubMed

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.

The Topp-Leone generalized Rayleigh cure rate model and its application

NASA Astrophysics Data System (ADS)

Nanthaprut, Pimwarat; Bodhisuwan, Winai; Patummasut, Mena

2017-11-01

Cure rate model is one of the survival analysis when model consider a proportion of the censored data. In clinical trials, the data represent time to recurrence of event or death of patients are used to improve the efficiency of treatments. Each dataset can be separated into two groups: censored and uncensored data. In this work, the new mixture cure rate model is introduced based on the Topp-Leone generalized Rayleigh distribution. The Bayesian approach is employed to estimate its parameters. In addition, a breast cancer dataset is analyzed for model illustration purpose. According to the deviance information criterion, the Topp-Leone generalized Rayleigh cure rate model shows better result than the Weibull and exponential cure rate models.

General linear methods and friends: Toward efficient solutions of multiphysics problems

NASA Astrophysics Data System (ADS)

Sandu, Adrian

2017-07-01

Time dependent multiphysics partial differential equations are of great practical importance as they model diverse phenomena that appear in mechanical and chemical engineering, aeronautics, astrophysics, meteorology and oceanography, financial modeling, environmental sciences, etc. There is no single best time discretization for the complex multiphysics systems of practical interest. We discuss "multimethod" approaches that combine different time steps and discretizations using the rigourous frameworks provided by Partitioned General Linear Methods and Generalize-structure Additive Runge Kutta Methods..

Modeling Magnetic Flux-Ropes Structures

NASA Astrophysics Data System (ADS)

Nieves-Chinchilla, T.; Linton, M.; Hidalgo, M. A. U.; Vourlidas, A.; Savani, N.; Szabo, A.; Farrugia, C. J.; Yu, W.

2015-12-01

Flux-ropes are usually associated with magnetic structures embedded in the interplanetary Coronal Mass Ejections (ICMEs) with a depressed proton temperature (called Magnetic Clouds, MCs). However, small-scale flux-ropes in the solar wind are also identified with different formation, evolution, and dynamic involved. We present an analytical model to describe magnetic flux-rope topologies. The model is generalized to different grades of complexity. It extends the circular-cylindrical concept of Hidalgo et al. (2002) by introducing a general form for the radial dependence of the current density. This generalization provides information on the force distribution inside the flux rope in addition to the usual parameters of flux-rope geometrical information and orientation. The generalized model provides flexibility for implementation in 3-D MHD simulations.

A General Definition of the Heritable Variation That Determines the Potential of a Population to Respond to Selection

PubMed Central

Bijma, Piter

2011-01-01

Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population’s intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection. PMID:21926298

A general definition of the heritable variation that determines the potential of a population to respond to selection.

PubMed

Bijma, Piter

2011-12-01

Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population's intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection.

Applying multibeam sonar and mathematical modeling for mapping seabed substrate and biota of offshore shallows

NASA Astrophysics Data System (ADS)

Herkül, Kristjan; Peterson, Anneliis; Paekivi, Sander

2017-06-01

Both basic science and marine spatial planning are in a need of high resolution spatially continuous data on seabed habitats and biota. As conventional point-wise sampling is unable to cover large spatial extents in high detail, it must be supplemented with remote sensing and modeling in order to fulfill the scientific and management needs. The combined use of in situ sampling, sonar scanning, and mathematical modeling is becoming the main method for mapping both abiotic and biotic seabed features. Further development and testing of the methods in varying locations and environmental settings is essential for moving towards unified and generally accepted methodology. To fill the relevant research gap in the Baltic Sea, we used multibeam sonar and mathematical modeling methods - generalized additive models (GAM) and random forest (RF) - together with underwater video to map seabed substrate and epibenthos of offshore shallows. In addition to testing the general applicability of the proposed complex of techniques, the predictive power of different sonar-based variables and modeling algorithms were tested. Mean depth, followed by mean backscatter, were the most influential variables in most of the models. Generally, mean values of sonar-based variables had higher predictive power than their standard deviations. The predictive accuracy of RF was higher than that of GAM. To conclude, we found the method to be feasible and with predictive accuracy similar to previous studies of sonar-based mapping.

Modeling Gas Exchange in a Closed Plant Growth Chamber

NASA Technical Reports Server (NTRS)

Cornett, J. D.; Hendrix, J. E.; Wheeler, R. M.; Ross, C. W.; Sadeh, W. Z.

1994-01-01

Fluid transport models for fluxes of water vapor and CO2 have been developed for one crop of wheat and three crops of soybean grown in a closed plant a growth chamber. Correspondence among these fluxes is discussed. Maximum fluxes of gases are provided for engineering design requirements of fluid recycling equipment in growth chambers. Furthermore, to investigate the feasibility of generalized crop models, dimensionless representations of water vapor fluxes are presented. The feasibility of such generalized models and the need for additional data are discussed.

Modeling gas exchange in a closed plant growth chamber

NASA Technical Reports Server (NTRS)

Cornett, J. D.; Hendrix, J. E.; Wheeler, R. M.; Ross, C. W.; Sadeh, W. Z.

1994-01-01

Fluid transport models for fluxes of water vapor and CO2 have been developed for one crop of wheat and three crops of soybean grown in a closed plant growth chamber. Correspondence among these fluxes is discussed. Maximum fluxes of gases are provided for engineering design requirements of fluid recycling equipment in growth chambers. Furthermore, to investigate the feasibility of generalized crop models, dimensionless representations of water vapor fluxes are presented. The feasibility of such generalized models and the need for additional data are discussed.

One Factor or Two Parallel Processes? Comorbidity and Development of Adolescent Anxiety and Depressive Disorder Symptoms

ERIC Educational Resources Information Center

Hale, William W., III; Raaijmakers, Quinten A. W.; Muris, Peter; van Hoof, Anne; Meeus, Wim H. J.

2009-01-01

Background: This study investigates whether anxiety and depressive disorder symptoms of adolescents from the general community are best described by a model that assumes they are indicative of one general factor or by a model that assumes they are two distinct disorders with parallel growth processes. Additional analyses were conducted to explore…

A Generalized Model of E-trading for GSR Fair Exchange Protocol

NASA Astrophysics Data System (ADS)

Konar, Debajyoti; Mazumdar, Chandan

In this paper we propose a generalized model of E-trading for the development of GSR Fair Exchange Protocols. Based on the model, a method is narrated to implement E-trading protocols that ensure fairness in true sense without using an additional trusted third party for which either party has to pay. The model provides the scope to include the correctness of the product, money atomicity and customer's anonymity properties within E-trading protocol. We conclude this paper by indicating the area of applicability for our model.

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

NASA Astrophysics Data System (ADS)

Made Tirta, I.; Anggraeni, Dian

2018-04-01

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

Explanation of non-additive effects in mixtures of similar mode of action chemicals.

PubMed

Kamo, Masashi; Yokomizo, Hiroyuki

2015-09-01

Many models have been developed to predict the combined effect of drugs and chemicals. Most models are classified into two additive models: independent action (IA) and concentration addition (CA). It is generally considered if the modes of action of chemicals are similar then the combined effect obeys CA; however, many empirical studies report nonlinear effects deviating from the predictions by CA. Such deviations are termed synergism and antagonism. Synergism, which leads to a stronger toxicity, requires more careful management, and hence it is important to understand how and which combinations of chemicals lead to synergism. In this paper, three types of chemical reactions are mathematically modeled and the cause of the nonlinear effects among chemicals with similar modes of action was investigated. Our results show that combined effects obey CA only when the modes of action are exactly the same. Contrary to existing knowledge, combined effects are generally nonlinear even if the modes of action of the chemicals are similar. Our results further show that the nonlinear effects vanish out when the chemical concentrations are low, suggesting that the current management procedure of assuming CA is rarely inappropriate because environmental concentrations of chemicals are generally low. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Addition of equilibrium air to an upwind Navier-Stokes code and other first steps toward a more generalized flow solver

NASA Technical Reports Server (NTRS)

Rosen, Bruce S.

1991-01-01

An upwind three-dimensional volume Navier-Stokes code is modified to facilitate modeling of complex geometries and flow fields represented by proposed National Aerospace Plane concepts. Code enhancements include an equilibrium air model, a generalized equilibrium gas model and several schemes to simplify treatment of complex geometric configurations. The code is also restructured for inclusion of an arbitrary number of independent and dependent variables. This latter capability is intended for eventual use to incorporate nonequilibrium/chemistry gas models, more sophisticated turbulence and transition models, or other physical phenomena which will require inclusion of additional variables and/or governing equations. Comparisons of computed results with experimental data and results obtained using other methods are presented for code validation purposes. Good correlation is obtained for all of the test cases considered, indicating the success of the current effort.

Spatial Assessment of Model Errors from Four Regression Techniques

Treesearch

Lianjun Zhang; Jeffrey H. Gove; Jeffrey H. Gove

2005-01-01

Fomst modelers have attempted to account for the spatial autocorrelations among trees in growth and yield models by applying alternative regression techniques such as linear mixed models (LMM), generalized additive models (GAM), and geographicalIy weighted regression (GWR). However, the model errors are commonly assessed using average errors across the entire study...

Selected translated abstracts of Russian-language climate-change publications. 4: General circulation models (in English;Russian)

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

Burtis, M.D.; Razuvaev, V.N.; Sivachok, S.G.

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.

Bifactor latent structure of attention-deficit/hyperactivity disorder (ADHD)/oppositional defiant disorder (ODD) symptoms and first-order latent structure of sluggish cognitive tempo symptoms.

PubMed

Lee, SoYean; Burns, G Leonard; Beauchaine, Theodore P; Becker, Stephen P

2016-08-01

The objective was to determine if the latent structure of attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms is best explained by a general disruptive behavior factor along with specific inattention (IN), hyperactivity/impulsivity (HI), and ODD factors (a bifactor model) whereas the latent structure of sluggish cognitive tempo (SCT) symptoms is best explained by a first-order factor independent of the bifactor model of ADHD/ODD. Parents' (n = 703) and teachers' (n = 366) ratings of SCT, ADHD-IN, ADHD-HI, and ODD symptoms on the Child and Adolescent Disruptive Behavior Inventory (CADBI) in a community sample of children (ages 5-13; 55% girls) were used to evaluate 4 models of symptom organization. Results indicated that a bifactor model of ADHD/ODD symptoms, in conjunction with a separate first-order SCT factor, was the best model for both parent and teacher ratings. The first-order SCT factor showed discriminant validity with the general disruptive behavior and specific IN factors in the bifactor model. In addition, higher scores on the SCT factor predicted greater academic and social impairment, even after controlling for the general disruptive behavior and 3 specific factors. Consistent with predictions from the trait-impulsivity etiological model of externalizing liability, a single, general disruptive behavior factor accounted for nearly all common variance in ADHD/ODD symptoms, whereas SCT symptoms represented a factor different from the general disruptive behavior and specific IN factor. These results provide additional support for distinguishing between SCT and ADHD-IN. The study also demonstrates how etiological models can be used to predict specific latent structures of symptom organization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Applying additive modeling and gradient boosting to assess the effects of watershed and reach characteristics on riverine assemblages

USGS Publications Warehouse

Maloney, Kelly O.; Schmid, Matthias; Weller, Donald E.

2012-01-01

Issues with ecological data (e.g. non-normality of errors, nonlinear relationships and autocorrelation of variables) and modelling (e.g. overfitting, variable selection and prediction) complicate regression analyses in ecology. Flexible models, such as generalized additive models (GAMs), can address data issues, and machine learning techniques (e.g. gradient boosting) can help resolve modelling issues. Gradient boosted GAMs do both. Here, we illustrate the advantages of this technique using data on benthic macroinvertebrates and fish from 1573 small streams in Maryland, USA.

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

NASA Technical Reports Server (NTRS)

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.

Relating Factor Models for Longitudinal Data to Quasi-Simplex and NARMA Models

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

2005-01-01

In this article we show the one-factor model can be rewritten as a quasi-simplex model. Using this result along with addition theorems from time series analysis, we describe a common general model, the nonstationary autoregressive moving average (NARMA) model, that includes as a special case, any latent variable model with continuous indicators…

A family of triaxial modified Hubble mass models: Effects of the additional radial functions

NASA Astrophysics Data System (ADS)

Das, Mousumi; Thakur, Parijat; Ann, H. B.

2005-03-01

The projected properties of triaxial generalization of the modified Hubble mass models are studied. These models are constructed by adding the additional radial functions, each multiplied by a low-order spherical harmonic, to the models of [Chakraborty, D.K., Thakur, P., 2000. MNRAS 318, 1273]. The projected surface density of mass models can be calculated analytically which allows us to derive the analytic expressions of axial ratio and position angle of major axis of constant density elliptical contours at asymptotic radii. The models are more general than those studied earlier in the sense that the inclusions of additional terms in density distribution, allow one to produce varieties of the radial profile of axial ratio and position angle, in particular, their small scale variations at inner radii. Strong correlations are found to exist between the observed axial ratio evaluated at 0.25Re and at 4Re which occupy well-separated regions in the parameter space for different choices of the intrinsic axial ratios. These correlations can be exploited to predict the intrinsic shape of the mass model, independent of the viewing angles. Using Bayesian statistics, the result of a test case launched for an estimation of the shape of a model galaxy is found to be satisfactory.

Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables

ERIC Educational Resources Information Center

Henson, Robert A.; Templin, Jonathan L.; Willse, John T.

2009-01-01

This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for…

Interfacing the Generalized Fluid System Simulation Program with the SINDA/G Thermal Program

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Palmiter, Christopher; Farmer, Jeffery; Lycans, Randall; Tiller, Bruce

2000-01-01

A general purpose, one dimensional fluid flow code has been interfaced with the thermal analysis program SINDA/G. The flow code, GFSSP, is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development was conducted in two phases. This paper describes the first (which allows for steady and quasi-steady - unsteady solid, steady fluid - conjugate heat transfer modeling). The second (full transient conjugate heat transfer modeling) phase of the interface development will be addressed in a later paper. Phase 1 development has been benchmarked to an analytical solution with excellent agreement. Additional test cases for each development phase demonstrate desired features of the interface. The results of the benchmark case, three additional test cases and a practical application are presented herein.

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.

PubMed

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.

Numerical and Qualitative Contrasts of Two Statistical Models for Water Quality Change in Tidal Waters

EPA Science Inventory

Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and...

Significance Testing in Confirmatory Factor Analytic Models.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; Hocevar, Dennis

Traditionally, confirmatory factor analytic models are tested against a null model of total independence. Using randomly generated factors in a matrix of 46 aptitude tests, this approach is shown to be unlikely to reject even random factors. An alternative null model, based on a single general factor, is suggested. In addition, an index of model…

Sample sizes and model comparison metrics for species distribution models

Treesearch

B.B. Hanberry; H.S. He; D.C. Dey

2012-01-01

Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....

Habitat of calling blue and fin whales in the Southern California Bight

NASA Astrophysics Data System (ADS)

Sirovic, A.; Chou, E.; Roch, M. A.

2016-02-01

Northeast Pacific blue whale B calls and fin whale 20 Hz calls were detected from passive acoustic data collected over seven years at 16 sites in the Southern California Bight (SCB). Calling blue whales were most common in the coastal areas, during the summer and fall months. Fin whales began calling in fall and continued through winter, in the southcentral SCB. These data were used to develop habitat models of calling blue and fin whales in areas of high and low abundance in the SCB, using remotely sensed variables such as sea surface temperature, sea surface height, chlorophyll a, and primary productivity as model covariates. A random forest framework was used for variable selection and generalized additive models were developed to explain functional relationships, evaluate relative contribution of each significant variable, and investigate predictive abilities of models of calling whales. Seasonal component was an important feature of all models. Additionally, areas of high calling blue and fin whale abundance both had a positive relationship with the sea surface temperature. In areas of lower abundance, chlorophyll a concentration and primary productivity were important variables for blue whale models and sea surface height and primary productivity were significant covariates in fin whale models. Predictive models were generally better for predicting general trends than absolute values, but there was a large degree of variation in year-to-year predictability across different sites.

Spatial modelling of disease using data- and knowledge-driven approaches.

PubMed

Stevens, Kim B; Pfeiffer, Dirk U

2011-09-01

The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution. Copyright © 2011. Published by Elsevier Ltd.

A generalized target theory and its applications.

PubMed

Zhao, Lei; Mi, Dong; Hu, Bei; Sun, Yeqing

2015-09-28

Different radiobiological models have been proposed to estimate the cell-killing effects, which are very important in radiotherapy and radiation risk assessment. However, most applied models have their own scopes of application. In this work, by generalizing the relationship between "hit" and "survival" in traditional target theory with Yager negation operator in Fuzzy mathematics, we propose a generalized target model of radiation-induced cell inactivation that takes into account both cellular repair effects and indirect effects of radiation. The simulation results of the model and the rethinking of "the number of targets in a cell" and "the number of hits per target" suggest that it is only necessary to investigate the generalized single-hit single-target (GSHST) in the present theoretical frame. Analysis shows that the GSHST model can be reduced to the linear quadratic model and multitarget model in the low-dose and high-dose regions, respectively. The fitting results show that the GSHST model agrees well with the usual experimental observations. In addition, the present model can be used to effectively predict cellular repair capacity, radiosensitivity, target size, especially the biologically effective dose for the treatment planning in clinical applications.

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

PubMed

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.

Operator priming and generalization of practice in adults' simple arithmetic.

PubMed

Chen, Yalin; Campbell, Jamie I D

2016-04-01

There is a renewed debate about whether educated adults solve simple addition problems (e.g., 2 + 3) by direct fact retrieval or by fast, automatic counting-based procedures. Recent research testing adults' simple addition and multiplication showed that a 150-ms preview of the operator (+ or ×) facilitated addition, but not multiplication, suggesting that a general addition procedure was primed by the + sign. In Experiment 1 (n = 36), we applied this operator-priming paradigm to rule-based problems (0 + N = N, 1 × N = N, 0 × N = 0) and 1 + N problems with N ranging from 0 to 9. For the rule-based problems, we found both operator-preview facilitation and generalization of practice (e.g., practicing 0 + 3 sped up unpracticed 0 + 8), the latter being a signature of procedure use; however, we also found operator-preview facilitation for 1 + N in the absence of generalization, which implies the 1 + N problems were solved by fact retrieval but nonetheless were facilitated by an operator preview. Thus, the operator preview effect does not discriminate procedure use from fact retrieval. Experiment 2 (n = 36) investigated whether a population with advanced mathematical training-engineering and computer science students-would show generalization of practice for nonrule-based simple addition problems (e.g., 1 + 4, 4 + 7). The 0 + N problems again presented generalization, whereas no nonzero problem type did; but all nonzero problems sped up when the identical problems were retested, as predicted by item-specific fact retrieval. The results pose a strong challenge to the generality of the proposal that skilled adults' simple addition is based on fast procedural algorithms, and instead support a fact-retrieval model of fast addition performance. (c) 2016 APA, all rights reserved).

Responses to GM food content in context with food integrity issues: results from Australian population surveys.

PubMed

Mohr, Philip; Golley, Sinéad

2016-01-25

This study examined community responses to use of genetically modified (GM) content in food in the context of responses to familiar food additives by testing an empirically and theoretically derived model of the predictors of responses to both GM content and food integrity issues generally. A nationwide sample of 849 adults, selected at random from the Australian Electoral Roll, responded to a postal Food and Health Survey. Structural equation modelling analyses confirmed that ratings of general concern about food integrity (related to the presence of preservatives and other additives) strongly predicted negativity towards GM content. Concern about food integrity was, in turn, predicted by environmental concern and health engagement. In addition, both concern about food integrity generally and responses to GM content specifically were weakly predicted by attitudes to benefits of science and an intuitive (i.e., emotionally-based) reasoning style. Data from a follow-up survey conducted under the same conditions (N=1184) revealed that ratings of concern were significantly lower for use of genetic engineering in food than for four other common food integrity issues examined. Whereas the question of community responses to GM is often treated as a special issue, these findings support the conclusion that responses to the concept of GM content in food in Australia are substantially a specific instance of a general sensitivity towards the integrity of the food supply. They indicate that the origins of responses to GM content may be largely indistinguishable from those of general responses to preservatives and other common food additives. Copyright © 2015 Elsevier B.V. All rights reserved.

Models for nearly every occasion: Part I - One box models.

PubMed

Hewett, Paul; Ganser, Gary H

2017-01-01

The standard "well mixed room," "one box" model cannot be used to predict occupational exposures whenever the scenario involves the use of local controls. New "constant emission" one box models are proposed that permit either local exhaust or local exhaust with filtered return, coupled with general room ventilation or the recirculation of a portion of the general room exhaust. New "two box" models are presented in Part II of this series. Both steady state and transient models were developed. The steady state equation for each model, including the standard one box steady state model, is augmented with an additional factor reflecting the fraction of time the substance was generated during each task. This addition allows the easy calculation of the average exposure for cyclic and irregular emission patterns, provided the starting and ending concentrations are zero or near zero, or the cumulative time across all tasks is long (e.g., several tasks to a full shift). The new models introduce additional variables, such as the efficiency of the local exhaust to immediately capture freshly generated contaminant and the filtration efficiency whenever filtered exhaust is returned to the workspace. Many of the model variables are knowable (e.g., room volume and ventilation rate). A structured procedure for calibrating a model to a work scenario is introduced that can be applied to both continuous and cyclic processes. The "calibration" procedure generates estimates of the generation rate and all of remaining unknown model variables.

A confirmatory factor analysis of the Impact of Event Scale using a sample of World War II and Korean War veterans.

PubMed

Shevlin, M; Hunt, N; Robbins, I

2000-12-01

This study assessed the factor structure of the Impact of Event Scale (IES), a measure of intrusion and avoidance, using a sample of World War II and Korean War veterans who had experienced combat 40-50 years earlier. A series of 3 confirmatory factor analytic models were specified and estimated using LISREL 8.3. Model 1 specified a 1-factor model. Model 2 specified a correlated 2-factor model. Model 3 specified a 2-factor model with additional cross-factor loadings for Items 2 and 12. Model 3 was found to fit the data. In addition, this model was found to be a better explanation of the data than the other models. Also in addition, the correlations between the Intrusion and Avoidance factors and the 4 subscales of the 28-item General Health Questionnaire were examined to determine the distinctiveness of the two IES factors.

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

PubMed Central

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 assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables. PMID:29713298

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.

PubMed

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 assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables.

Einstein’s gravity from a polynomial affine model

NASA Astrophysics Data System (ADS)

Castillo-Felisola, Oscar; Skirzewski, Aureliano

2018-03-01

We show that the effective field equations for a recently formulated polynomial affine model of gravity, in the sector of a torsion-free connection, accept general Einstein manifolds—with or without cosmological constant—as solutions. Moreover, the effective field equations are partially those obtained from a gravitational Yang–Mills theory known as Stephenson–Kilmister–Yang theory. Additionally, we find a generalization of a minimally coupled massless scalar field in General Relativity within a ‘minimally’ coupled scalar field in this affine model. Finally, we present a brief (perturbative) analysis of the propagators of the gravitational theory, and count the degrees of freedom. For completeness, we prove that a Birkhoff-like theorem is valid for the analyzed sector.

Nonlinear Unsteady Aerodynamic Modeling Using Wind Tunnel and Computational Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Klein, Vladislav; Frink, Neal T.

2016-01-01

Extensions to conventional aircraft aerodynamic models are required to adequately predict responses when nonlinear unsteady flight regimes are encountered, especially at high incidence angles and under maneuvering conditions. For a number of reasons, such as loss of control, both military and civilian aircraft may extend beyond normal and benign aerodynamic flight conditions. In addition, military applications may require controlled flight beyond the normal envelope, and civilian flight may require adequate recovery or prevention methods from these adverse conditions. These requirements have led to the development of more general aerodynamic modeling methods and provided impetus for researchers to improve both techniques and the degree of collaboration between analytical and experimental research efforts. In addition to more general mathematical model structures, dynamic test methods have been designed to provide sufficient information to allow model identification. This paper summarizes research to develop a modeling methodology appropriate for modeling aircraft aerodynamics that include nonlinear unsteady behaviors using both experimental and computational test methods. This work was done at Langley Research Center, primarily under the NASA Aviation Safety Program, to address aircraft loss of control, prevention, and recovery aerodynamics.

Estimating net rainfall, evaporation and water storage of a bare soil from sequential L-band emissivities

NASA Technical Reports Server (NTRS)

Stroosnijder, L.; Lascano, R. J.; Newton, R. W.; Vanbavel, C. H. M.

1984-01-01

A general method to use a time series of L-band emissivities as an input to a hydrological model for continuously monitoring the net rainfall and evaporation as well as the water content over the entire soil profile is proposed. The model requires a sufficiently accurate and general relation between soil emissivity and surface moisture content. A model which requires the soil hydraulic properties as an additional input, but does not need any weather data was developed. The method is shown to be numerically consistent.

General form of a cooperative gradual maximal covering location problem

NASA Astrophysics Data System (ADS)

Bagherinejad, Jafar; Bashiri, Mahdi; Nikzad, Hamideh

2018-07-01

Cooperative and gradual covering are two new methods for developing covering location models. In this paper, a cooperative maximal covering location-allocation model is developed (CMCLAP). In addition, both cooperative and gradual covering concepts are applied to the maximal covering location simultaneously (CGMCLP). Then, we develop an integrated form of a cooperative gradual maximal covering location problem, which is called a general CGMCLP. By setting the model parameters, the proposed general model can easily be transformed into other existing models, facilitating general comparisons. The proposed models are developed without allocation for physical signals and with allocation for non-physical signals in discrete location space. Comparison of the previously introduced gradual maximal covering location problem (GMCLP) and cooperative maximal covering location problem (CMCLP) models with our proposed CGMCLP model in similar data sets shows that the proposed model can cover more demands and acts more efficiently. Sensitivity analyses are performed to show the effect of related parameters and the model's validity. Simulated annealing (SA) and a tabu search (TS) are proposed as solution algorithms for the developed models for large-sized instances. The results show that the proposed algorithms are efficient solution approaches, considering solution quality and running time.

Game analysis and benefit allocation in international projects among owner, supervisor and contractor

NASA Astrophysics Data System (ADS)

Ding, Hao; Wang, Yong; Guo, Sini; Xu, Xiaofeng; Che, Cheng

2016-04-01

International projects are different from general domestic ones. In order to analyse the differences, a tripartite game model is built up to describe the relationship among owner, supervisor and general contractor, and some measures are given for the owner to more effectively complete the project. In addition, a project schedule selection model is formulated and a new benefit allocation method is proposed by introducing a new modified Shapley value with weighted factor.

Difference-based ridge-type estimator of parameters in restricted partial linear model with correlated errors.

PubMed

Wu, Jibo

2016-01-01

In this article, a generalized difference-based ridge estimator is proposed for the vector parameter in a partial linear model when the errors are dependent. It is supposed that some additional linear constraints may hold to the whole parameter space. Its mean-squared error matrix is compared with the generalized restricted difference-based estimator. Finally, the performance of the new estimator is explained by a simulation study and a numerical example.

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

PubMed

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

2017-08-01

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

Reductions in finite-dimensional integrable systems and special points of classical r-matrices

NASA Astrophysics Data System (ADS)

Skrypnyk, T.

2016-12-01

For a given 𝔤 ⊗ 𝔤-valued non-skew-symmetric non-dynamical classical r-matrices r(u, v) with spectral parameters, we construct the general form of 𝔤-valued Lax matrices of finite-dimensional integrable systems satisfying linear r-matrix algebra. We show that the reduction in the corresponding finite-dimensional integrable systems is connected with "the special points" of the classical r-matrices in which they become degenerated. We also propose a systematic way of the construction of additional integrals of the Lax-integrable systems associated with the symmetries of the corresponding r-matrices. We consider examples of the Lax matrices and integrable systems that are obtained in the framework of the general scheme. Among them there are such physically important systems as generalized Gaudin systems in an external magnetic field, ultimate integrable generalization of Toda-type chains (including "modified" or "deformed" Toda chains), generalized integrable Jaynes-Cummings-Dicke models, integrable boson models generalizing Bose-Hubbard dimer models, etc.

Distinguishing Continuous and Discrete Approaches to Multilevel Mixture IRT Models: A Model Comparison Perspective

ERIC Educational Resources Information Center

Zhu, Xiaoshu

2013-01-01

The current study introduced a general modeling framework, multilevel mixture IRT (MMIRT) which detects and describes characteristics of population heterogeneity, while accommodating the hierarchical data structure. In addition to introducing both continuous and discrete approaches to MMIRT, the main focus of the current study was to distinguish…

Methodical Approaches to Teaching of Computer Modeling in Computer Science Course

ERIC Educational Resources Information Center

Rakhimzhanova, B. Lyazzat; Issabayeva, N. Darazha; Khakimova, Tiyshtik; Bolyskhanova, J. Madina

2015-01-01

The purpose of this study was to justify of the formation technique of representation of modeling methodology at computer science lessons. The necessity of studying computer modeling is that the current trends of strengthening of general education and worldview functions of computer science define the necessity of additional research of the…

Replication of a gene-environment interaction Via Multimodel inference: additive-genetic variance in adolescents' general cognitive ability increases with family-of-origin socioeconomic status.

PubMed

Kirkpatrick, Robert M; McGue, Matt; Iacono, William G

2015-03-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES-an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research.

Replication of a Gene-Environment Interaction via Multimodel Inference: Additive-Genetic Variance in Adolescents’ General Cognitive Ability Increases with Family-of-Origin Socioeconomic Status

PubMed Central

Kirkpatrick, Robert M.; McGue, Matt; Iacono, William G.

2015-01-01

The present study of general cognitive ability attempts to replicate and extend previous investigations of a biometric moderator, family-of-origin socioeconomic status (SES), in a sample of 2,494 pairs of adolescent twins, non-twin biological siblings, and adoptive siblings assessed with individually administered IQ tests. We hypothesized that SES would covary positively with additive-genetic variance and negatively with shared-environmental variance. Important potential confounds unaddressed in some past studies, such as twin-specific effects, assortative mating, and differential heritability by trait level, were found to be negligible. In our main analysis, we compared models by their sample-size corrected AIC, and base our statistical inference on model-averaged point estimates and standard errors. Additive-genetic variance increased with SES—an effect that was statistically significant and robust to model specification. We found no evidence that SES moderated shared-environmental influence. We attempt to explain the inconsistent replication record of these effects, and provide suggestions for future research. PMID:25539975

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

PubMed

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.

Concentration Addition, Independent Action and Generalized Concentration Addition Models for Mixture Effect Prediction of Sex Hormone Synthesis In Vitro

PubMed Central

Hadrup, Niels; Taxvig, Camilla; Pedersen, Mikael; Nellemann, Christine; Hass, Ulla; Vinggaard, Anne Marie

2013-01-01

Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals. PMID:23990906

A Nakanishi-based model illustrating the covariant extension of the pion GPD overlap representation and its ambiguities

NASA Astrophysics Data System (ADS)

Chouika, N.; Mezrag, C.; Moutarde, H.; Rodríguez-Quintero, J.

2018-05-01

A systematic approach for the model building of Generalized Parton Distributions (GPDs), based on their overlap representation within the DGLAP kinematic region and a further covariant extension to the ERBL one, is applied to the valence-quark pion's case, using light-front wave functions inspired by the Nakanishi representation of the pion Bethe-Salpeter amplitudes (BSA). This simple but fruitful pion GPD model illustrates the general model building technique and, in addition, allows for the ambiguities related to the covariant extension, grounded on the Double Distribution (DD) representation, to be constrained by requiring a soft-pion theorem to be properly observed.

Impersonating the Standard Model Higgs boson: Alignment without decoupling

DOE PAGES

Carena, Marcela; Low, Ian; Shah, Nausheen R.; ...

2014-04-03

In models with an extended Higgs sector there exists an alignment limit, in which the lightest CP-even Higgs boson mimics the Standard Model Higgs. The alignment limit is commonly associated with the decoupling limit, where all non-standard scalars are significantly heavier than the Z boson. However, alignment can occur irrespective of the mass scale of the rest of the Higgs sector. In this work we discuss the general conditions that lead to “alignment without decoupling”, therefore allowing for the existence of additional non-standard Higgs bosons at the weak scale. The values of tan β for which this happens are derivedmore » in terms of the effective Higgs quartic couplings in general two-Higgs-doublet models as well as in supersymmetric theories, including the MSSM and the NMSSM. In addition, we study the information encoded in the variations of the SM Higgs-fermion couplings to explore regions in the m A – tan β parameter space.« less

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

NASA Astrophysics Data System (ADS)

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.

Strategic trade between two regions with partial local consumer protection - General setup and nash equilibria

NASA Astrophysics Data System (ADS)

Iordanov, Iordan V.; Vassilev, Andrey A.

2017-12-01

We construct a model of the trade relations between two regions for the case when the trading entities (consumers) compete for a scarce good and there is an element of strategic interdependence in the trading process. Additionally, local consumers enjoy partial protection in the form of guaranteed access to a part of the locally-supplied quantity of the good. The model is formulated for the general asymmetric case, where the two regions differ in terms of parameters such as income, size of the local market supply, degree of protection and transportation costs. For this general model we establish the existence of Nash equilibria and obtain their form as a function of the model parameters, producing a typology of the equilibria. This is a required step in order to rigorously study various types of price dynamics for the model.

Minimal state-dependent proof of measurement contextuality for a qubit

NASA Astrophysics Data System (ADS)

Kunjwal, Ravi; Ghosh, Sibasish

2014-04-01

We show that three unsharp binary qubit measurements are enough to violate a generalized noncontextuality inequality, the Liang-Spekkens-Wiseman inequality, in a state-dependent manner. For the case of trine spin axes we calculate the optimal quantum violation of this inequality. In addition, we show that unsharp qubit measurements do not allow a state-independent violation of this inequality. We thus provide a minimal state-dependent proof of measurement contextuality requiring one qubit and three unsharp measurements. Our result rules out generalized noncontextual models of these measurements which were previously conjectured to exist. More importantly, this class of generalized noncontextual models includes the traditional Kochen-Specker (KS) noncontextual models as a proper subset, so our result rules out a larger class of models than those ruled out by a violation of the corresponding KS inequality in this scenario.

Clarifying the Dynamics of the General Circulation: Phillips's 1956 Experiment.

NASA Astrophysics Data System (ADS)

Lewis, John M.

1998-01-01

In the mid-1950s, amid heated debate over the physical mechanisms that controlled the known features of the atmosphere's general circulation, Norman Phillips simulated hemispheric motion on the high-speed computer at the Institute for Advanced Study. A simple energetically consistent model was integrated for a simulated time of approximately 1 month. Analysis of the model results clarified the respective roles of the synoptic-scale eddies (cyclones-anticyclones) and mean meridional circulation in the maintenance of the upper-level westerlies and the surface wind regimes. Furthermore, the modeled cyclones clearly linked surface frontogenesis with the upper-level Charney-Eady wave. In addition to discussing the model results in light of the controversy and ferment that surrounded general circulation theory in the 1940s-1950s, an effort is made to follow Phillips's scientific path to the experiment.

Using Generalized Additive Models to Analyze Single-Case Designs

ERIC Educational Resources Information Center

Shadish, William; Sullivan, Kristynn

2013-01-01

Many analyses for single-case designs (SCDs)--including nearly all the effect size indicators-- currently assume no trend in the data. Regression and multilevel models allow for trend, but usually test only linear trend and have no principled way of knowing if higher order trends should be represented in the model. This paper shows how Generalized…

Modeling Longitudinal Data with Generalized Additive Models: Applications to Single-Case Designs

ERIC Educational Resources Information Center

Sullivan, Kristynn J.; Shadish, William R.

2013-01-01

Single case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time both in the presence and absence of treatment. For a variety of reasons, interest in the statistical analysis and meta-analysis of these designs has been growing in recent years. This paper proposes modeling SCD data with…

Stochastic Analysis and Probabilistic Downscaling of Soil Moisture

NASA Astrophysics Data System (ADS)

Deshon, J. P.; Niemann, J. D.; Green, T. R.; Jones, A. S.

2017-12-01

Soil moisture is a key variable for rainfall-runoff response estimation, ecological and biogeochemical flux estimation, and biodiversity characterization, each of which is useful for watershed condition assessment. These applications require not only accurate, fine-resolution soil-moisture estimates but also confidence limits on those estimates and soil-moisture patterns that exhibit realistic statistical properties (e.g., variance and spatial correlation structure). The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution (9-40 km) soil moisture from satellite remote sensing or land-surface models to produce fine-resolution (10-30 m) estimates. The model was designed to produce accurate deterministic soil-moisture estimates at multiple points, but the resulting patterns do not reproduce the variance or spatial correlation of observed soil-moisture patterns. The primary objective of this research is to generalize the EMT+VS model to produce a probability density function (pdf) for soil moisture at each fine-resolution location and time. Each pdf has a mean that is equal to the deterministic soil-moisture estimate, and the pdf can be used to quantify the uncertainty in the soil-moisture estimates and to simulate soil-moisture patterns. Different versions of the generalized model are hypothesized based on how uncertainty enters the model, whether the uncertainty is additive or multiplicative, and which distributions describe the uncertainty. These versions are then tested by application to four catchments with detailed soil-moisture observations (Tarrawarra, Satellite Station, Cache la Poudre, and Nerrigundah). The performance of the generalized models is evaluated by comparing the statistical properties of the simulated soil-moisture patterns to those of the observations and the deterministic EMT+VS model. The versions of the generalized EMT+VS model with normally distributed stochastic components produce soil-moisture patterns with more realistic statistical properties than the deterministic model. Additionally, the results suggest that the variance and spatial correlation of the stochastic soil-moisture variations do not vary consistently with the spatial-average soil moisture.

The economic impact of drag in general aviation

NASA Technical Reports Server (NTRS)

Neal, R. D.

1975-01-01

General aviation aircraft fuel consumption and operating costs are closely linked to drag reduction methods. Improvements in airplane drag are envisioned for new models; their effects will be in the 5 to 10% range. Major improvements in fuel consumption over existing turbofan airplanes will be the combined results of improved aerodynamics plus additional effects from advanced turbofan engine designs.

The Benefits of Implementing Disability Sports in Physical Education: A Model for Success

ERIC Educational Resources Information Center

Grenier, Michelle; Kearns, Catherine

2012-01-01

The growing appeal and acceptance of disability sports within the general population makes them an attractive addition for any physical education program. When included in a general physical education program, these sports provide complementary skills to students while delivering a powerful message about what it means to be an athlete with a…

Distribution of lod scores in oligogenic linkage analysis.

PubMed

Williams, J T; North, K E; Martin, L J; Comuzzie, A G; Göring, H H; Blangero, J

2001-01-01

In variance component oligogenic linkage analysis it can happen that the residual additive genetic variance bounds to zero when estimating the effect of the ith quantitative trait locus. Using quantitative trait Q1 from the Genetic Analysis Workshop 12 simulated general population data, we compare the observed lod scores from oligogenic linkage analysis with the empirical lod score distribution under a null model of no linkage. We find that zero residual additive genetic variance in the null model alters the usual distribution of the likelihood-ratio statistic.

Modeling in Ceramic Clay

ERIC Educational Resources Information Center

Miller, Louis J.

1976-01-01

Modeling is an additive process of building up a sculpture with some plastic material like clay. It affords the student an opportunity to work in three dimensions, a creative relief from the general two-dimensional drawing and design activities that occupy a large segment of time in the art curriculum. (Author/RK)

INTERANNUAL VARIATION IN METEOROLOGICALLY ADJUSTED OZONE LEVELS IN THE EASTERN UNITED STATES: A COMPARISON OF TWO APPROACHED

EPA Science Inventory

Assessing the influence of abatement efforts and other human activities on ozone levels is complicated by the atmosphere's changeable nature. Two statistical methods, the dynamic linear model(DLM) and the generalized additive model (GAM), are used to estimate ozone trends in the...

Straddling Interdisciplinary Seams: Working Safely in the Field, Living Dangerously With a Model

NASA Astrophysics Data System (ADS)

Light, B.; Roberts, A.

2016-12-01

Many excellent proposals for observational work have included language detailing how the proposers will appropriately archive their data and publish their results in peer-reviewed literature so that they may be readily available to the modeling community for parameterization development. While such division of labor may be both practical and inevitable, the assimilation of observational results and the development of observationally-based parameterizations of physical processes require care and feeding. Key questions include: (1) Is an existing parameterization accurate, consistent, and general? If not, it may be ripe for additional physics. (2) Do there exist functional working relationships between human modeler and human observationalist? If not, one or more may need to be initiated and cultivated. (3) If empirical observation and model development are a chicken/egg problem, how, given our lack of prescience and foreknowledge, can we better design observational science plans to meet the eventual demands of model parameterization? (4) Will the addition of new physics "break" the model? If so, then the addition may be imperative. In the context of these questions, we will make retrospective and forward-looking assessments of a now-decade-old numerical parameterization to treat the partitioning of solar energy at the Earth's surface where sea ice is present. While this so called "Delta-Eddington Albedo Parameterization" is currently employed in the widely-used Los Alamos Sea Ice Model (CICE) and appears to be standing the tests of accuracy, consistency, and generality, we will highlight some ideas for its ongoing development and improvement.

One factor or two parallel processes? Comorbidity and development of adolescent anxiety and depressive disorder symptoms.

PubMed

Hale, William W; Raaijmakers, Quinten A W; Muris, Peter; van Hoof, Anne; Meeus, Wim H J

2009-10-01

This study investigates whether anxiety and depressive disorder symptoms of adolescents from the general community are best described by a model that assumes they are indicative of one general factor or by a model that assumes they are two distinct disorders with parallel growth processes. Additional analyses were conducted to explore the comorbidity of adolescent anxiety and depressive disorder symptoms and the effects that adolescent anxiety and depressive disorder symptoms have on each other's symptom severity growth. Two cohorts of early (N = 923; Age range 10-15 years; Mean age = 12.4, SD = .59; Girls = 49%) and middle adolescent (N = 390; Age range 16-20 years; Mean age = 16.7, SD = .80; Girls = 57%) boys and girls from the general community were prospectively studied annually for five years. These two adolescent cohorts were divided into five groups: one group at-risk for developing a specific anxiety disorder and four additional groups of healthy adolescents that differed in age and sex. Self-reported anxiety and depressive disorder symptoms were analyzed with latent growth modeling. Comparison of the fit statistics of the two models clearly demonstrates the superiority of the distinct disorders with parallel growth processes model above the one factor model. It was also demonstrated that the initial symptom severity of either anxiety or depression is predictive of the development of the other, though in different ways for the at-risk and healthy adolescent groups. The results of this study established that the development of anxiety and depressive disorder symptoms of adolescents from the general community occurs as two distinct disorders with parallel growth processes, each with their own unique growth characteristics.

Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Popok, Daniel

1999-01-01

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.

Stratospheric wind errors, initial states and forecast skill in the GLAS general circulation model

NASA Technical Reports Server (NTRS)

Tenenbaum, J.

1983-01-01

Relations between stratospheric wind errors, initial states and 500 mb skill are investigated using the GLAS general circulation model initialized with FGGE data. Erroneous stratospheric winds are seen in all current general circulation models, appearing also as weak shear above the subtropical jet and as cold polar stratospheres. In this study it is shown that the more anticyclonic large-scale flows are correlated with large forecast stratospheric winds. In addition, it is found that for North America the resulting errors are correlated with initial state jet stream accelerations while for East Asia the forecast winds are correlated with initial state jet strength. Using 500 mb skill scores over Europe at day 5 to measure forecast performance, it is found that both poor forecast skill and excessive stratospheric winds are correlated with more anticyclonic large-scale flows over North America. It is hypothesized that the resulting erroneous kinetic energy contributes to the poor forecast skill, and that the problem is caused by a failure in the modeling of the stratospheric energy cycle in current general circulation models independent of vertical resolution.

Exponentiated power Lindley distribution.

PubMed

Ashour, Samir K; Eltehiwy, Mahmoud A

2015-11-01

A new generalization of the Lindley distribution is recently proposed by Ghitany et al. [1], called as the power Lindley distribution. Another generalization of the Lindley distribution was introduced by Nadarajah et al. [2], named as the generalized Lindley distribution. This paper proposes a more generalization of the Lindley distribution which generalizes the two. We refer to this new generalization as the exponentiated power Lindley distribution. The new distribution is important since it contains as special sub-models some widely well-known distributions in addition to the above two models, such as the Lindley distribution among many others. It also provides more flexibility to analyze complex real data sets. We study some statistical properties for the new distribution. We discuss maximum likelihood estimation of the distribution parameters. Least square estimation is used to evaluate the parameters. Three algorithms are proposed for generating random data from the proposed distribution. An application of the model to a real data set is analyzed using the new distribution, which shows that the exponentiated power Lindley distribution can be used quite effectively in analyzing real lifetime data.

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: constraining modified gravity

NASA Astrophysics Data System (ADS)

Mueller, Eva-Maria; Percival, Will; Linder, Eric; Alam, Shadab; Zhao, Gong-Bo; Sánchez, Ariel G.; Beutler, Florian; Brinkmann, Jon

2018-04-01

We use baryon acoustic oscillation and redshift space distortion from the completed Baryon Oscillation Spectroscopic Survey, corresponding to Data Release 12 of the Sloan Digital Sky Survey, combined sample analysis in combination with cosmic microwave background, supernova, and redshift space distortion measurements from additional spectroscopic surveys to test deviations from general relativity. We present constraints on several phenomenological models of modified gravity: First, we parametrize the growth of structure using the growth index γ, finding γ = 0.566 ± 0.058 (68 per cent C.L.). Secondly, we modify the relation of the two Newtonian potentials by introducing two additional parameters, GM and GL. In this approach, GM refers to modifications of the growth of structure whereas GL to modification of the lensing potential. We consider a power law to model the redshift dependence of GM and GL as well as binning in redshift space, introducing four additional degrees of freedom, GM(z < 0.5), GM(z > 0.5), GL(z < 0.5), and GL(z > 0.5). At 68 per cent C.L., we measure GM = 0.980 ± 0.096 and GL = 1.082 ± 0.060 for a linear model, GM = 1.01 ± 0.36 and GL = 1.31 ± 0.19 for a cubic model as well as GM(z < 0.5) = 1.26 ± 0.32, GM(z > 0.5) = 0.986 ± 0.022, GL(z < 0.5) = 1.067 ± 0.058, and GL(z > 0.5) = 1.037 ± 0.029. Thirdly, we investigate general scalar tensor theories of gravity, finding the model to be mostly unconstrained by current data. Assuming a one-parameter f(R) model, we can constrain B0 < 7.7 × 10-5 (95 per cent C.L). For all models we considered, we find good agreement with general relativity.

Building out a Measurement Model to Incorporate Complexities of Testing in the Language Domain

ERIC Educational Resources Information Center

Wilson, Mark; Moore, Stephen

2011-01-01

This paper provides a summary of a novel and integrated way to think about the item response models (most often used in measurement applications in social science areas such as psychology, education, and especially testing of various kinds) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. In addition,…

Towards community-driven paleogeographic reconstructions: integrating open-access paleogeographic and paleobiology data with plate tectonics

NASA Astrophysics Data System (ADS)

Wright, N.; Zahirovic, S.; Müller, R. D.; Seton, M.

2013-03-01

A variety of paleogeographic reconstructions have been published, with applications ranging from paleoclimate, ocean circulation and faunal radiation models to resource exploration; yet their uncertainties remain difficult to assess as they are generally presented as low-resolution static maps. We present a methodology for ground-truthing the digital Palaeogeographic Atlas of Australia by linking the GPlates plate reconstruction tool to the global Paleobiology Database and a Phanerozoic plate motion model. We develop a spatio-temporal data mining workflow to validate the Phanerozoic Palaeogeographic Atlas of Australia with paleoenvironments derived from fossil data. While there is general agreement between fossil data and the paleogeographic model, the methodology highlights key inconsistencies. The Early Devonian paleogeographic model of southeastern Australia insufficiently describes the Emsian inundation that may be refined using biofacies distributions. Additionally, the paleogeographic model and fossil data can be used to strengthen numerical models, such as the dynamic topography and the associated inundation of eastern Australia during the Cretaceous. Although paleobiology data provide constraints only for paleoenvironments with high preservation potential of organisms, our approach enables the use of additional proxy data to generate improved paleogeographic reconstructions.

Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process

NASA Astrophysics Data System (ADS)

Turner, Douglas C.; Ladde, Gangaram S.

2018-03-01

Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.

Comment on ``Metric-affine approach to teleparallel gravity''

NASA Astrophysics Data System (ADS)

Formiga, J. B.

2013-09-01

It is well known that the teleparallel equivalent of general relativity yields the same vacuum solutions as general relativity does, which ensures that this particular teleparallel model is in good agreement with experiments. A lesser known result concerns the existence of a wider class of teleparallel models which also admits these solutions when the spacetime is diagonalizable by means of a coordinate change. However, it is stated by Obukhov and Pereira [Phys. Rev. D 67, 044016 (2003)] that the teleparallel equivalent of general relativity is the only teleparallel model which admits black holes. To show that this statement is not true, I present the result of Hayashi and Shirafuji [Phys. Rev. D 19, 3524 (1979)], which proves the existence of this wider class by showing the equivalence between two Lagrangians. It turns out that this equivalence also holds for plane-wave metrics. In addition, I update the constraints on the parameters of the teleparallel models.

Maximum profile likelihood estimation of differential equation parameters through model based smoothing state estimates.

PubMed

Campbell, D A; Chkrebtii, O

2013-12-01

Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

Comparison of modeling methods to predict the spatial distribution of deep-sea coral and sponge in the Gulf of Alaska

NASA Astrophysics Data System (ADS)

Rooper, Christopher N.; Zimmermann, Mark; Prescott, Megan M.

2017-08-01

Deep-sea coral and sponge ecosystems are widespread throughout most of Alaska's marine waters, and are associated with many different species of fishes and invertebrates. These ecosystems are vulnerable to the effects of commercial fishing activities and climate change. We compared four commonly used species distribution models (general linear models, generalized additive models, boosted regression trees and random forest models) and an ensemble model to predict the presence or absence and abundance of six groups of benthic invertebrate taxa in the Gulf of Alaska. All four model types performed adequately on training data for predicting presence and absence, with regression forest models having the best overall performance measured by the area under the receiver-operating-curve (AUC). The models also performed well on the test data for presence and absence with average AUCs ranging from 0.66 to 0.82. For the test data, ensemble models performed the best. For abundance data, there was an obvious demarcation in performance between the two regression-based methods (general linear models and generalized additive models), and the tree-based models. The boosted regression tree and random forest models out-performed the other models by a wide margin on both the training and testing data. However, there was a significant drop-off in performance for all models of invertebrate abundance ( 50%) when moving from the training data to the testing data. Ensemble model performance was between the tree-based and regression-based methods. The maps of predictions from the models for both presence and abundance agreed very well across model types, with an increase in variability in predictions for the abundance data. We conclude that where data conforms well to the modeled distribution (such as the presence-absence data and binomial distribution in this study), the four types of models will provide similar results, although the regression-type models may be more consistent with biological theory. For data with highly zero-inflated distributions and non-normal distributions such as the abundance data from this study, the tree-based methods performed better. Ensemble models that averaged predictions across the four model types, performed better than the GLM or GAM models but slightly poorer than the tree-based methods, suggesting ensemble models might be more robust to overfitting than tree methods, while mitigating some of the disadvantages in predictive performance of regression methods.

Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors

PubMed Central

Bellali, Hedia; Ben-Alaya, Nissaf; Saez, Marc; Malouche, Dhafer; Chahed, Mohamed Kouni

2017-01-01

Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009–2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia. PMID:28841642

Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors.

PubMed

Talmoudi, Khouloud; Bellali, Hedia; Ben-Alaya, Nissaf; Saez, Marc; Malouche, Dhafer; Chahed, Mohamed Kouni

2017-08-01

Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009-2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia.

A generalized linear factor model approach to the hierarchical framework for responses and response times.

PubMed

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.

A Randomized Controlled Trial of Cognitive-Behavioral Therapy for Generalized Anxiety Disorder with Integrated Techniques from Emotion-Focused and Interpersonal Therapies

ERIC Educational Resources Information Center

Newman, Michelle G.; Castonguay, Louis G.; Borkovec, Thomas D.; Fisher, Aaron J.; Boswell, James F.; Szkodny, Lauren E.; Nordberg, Samuel S.

2011-01-01

Objective: Recent models suggest that generalized anxiety disorder (GAD) symptoms may be maintained by emotional processing avoidance and interpersonal problems. Method: This is the first randomized controlled trial to test directly whether cognitive-behavioral therapy (CBT) could be augmented with the addition of a module targeting interpersonal…

Empirical validation of landscape resistance models: insights from the Greater Sage-Grouse (Centrocercus urophasianus)

Treesearch

Andrew J. Shirk; Michael A. Schroeder; Leslie A. Robb; Samuel A. Cushman

2015-01-01

The ability of landscapes to impede species’ movement or gene flow may be quantified by resistance models. Few studies have assessed the performance of resistance models parameterized by expert opinion. In addition, resistance models differ in terms of spatial and thematic resolution as well as their focus on the ecology of a particular species or more generally on the...

Analysis of a kinetic multi-segment foot model. Part I: Model repeatability and kinematic validity.

PubMed

Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L

2012-04-01

Kinematic multi-segment foot models are still evolving, but have seen increased use in clinical and research settings. The addition of kinetics may increase knowledge of foot and ankle function as well as influence multi-segment foot model evolution; however, previous kinetic models are too complex for clinical use. In this study we present a three-segment kinetic foot model and thorough evaluation of model performance during normal gait. In this first of two companion papers, model reference frames and joint centers are analyzed for repeatability, joint translations are measured, segment rigidity characterized, and sample joint angles presented. Within-tester and between-tester repeatability were first assessed using 10 healthy pediatric participants, while kinematic parameters were subsequently measured on 17 additional healthy pediatric participants. Repeatability errors were generally low for all sagittal plane measures as well as transverse plane Hindfoot and Forefoot segments (median<3°), while the least repeatable orientations were the Hindfoot coronal plane and Hallux transverse plane. Joint translations were generally less than 2mm in any one direction, while segment rigidity analysis suggested rigid body behavior for the Shank and Hindfoot, with the Forefoot violating the rigid body assumptions in terminal stance/pre-swing. Joint excursions were consistent with previously published studies. Copyright © 2012 Elsevier B.V. All rights reserved.

Additive Partial Least Squares for efficient modelling of independent variance sources demonstrated on practical case studies.

PubMed

Luoma, Pekka; Natschläger, Thomas; Malli, Birgit; Pawliczek, Marcin; Brandstetter, Markus

2018-05-12

A model recalibration method based on additive Partial Least Squares (PLS) regression is generalized for multi-adjustment scenarios of independent variance sources (referred to as additive PLS - aPLS). aPLS allows for effortless model readjustment under changing measurement conditions and the combination of independent variance sources with the initial model by means of additive modelling. We demonstrate these distinguishing features on two NIR spectroscopic case-studies. In case study 1 aPLS was used as a readjustment method for an emerging offset. The achieved RMS error of prediction (1.91 a.u.) was of similar level as before the offset occurred (2.11 a.u.). In case-study 2 a calibration combining different variance sources was conducted. The achieved performance was of sufficient level with an absolute error being better than 0.8% of the mean concentration, therefore being able to compensate negative effects of two independent variance sources. The presented results show the applicability of the aPLS approach. The main advantages of the method are that the original model stays unadjusted and that the modelling is conducted on concrete changes in the spectra thus supporting efficient (in most cases straightforward) modelling. Additionally, the method is put into context of existing machine learning algorithms. Copyright © 2018 Elsevier B.V. All rights reserved.

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

PubMed

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

2013-05-01

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

Modeling the flux of metabolites in the juvenile hormone biosynthesis pathway using generalized additive models and ordinary differential equations.

PubMed

Martínez-Rincón, Raúl O; Rivera-Pérez, Crisalejandra; Diambra, Luis; Noriega, Fernando G

2017-01-01

Juvenile hormone (JH) regulates development and reproductive maturation in insects. The corpora allata (CA) from female adult mosquitoes synthesize fluctuating levels of JH, which have been linked to the ovarian development and are influenced by nutritional signals. The rate of JH biosynthesis is controlled by the rate of flux of isoprenoids in the pathway, which is the outcome of a complex interplay of changes in precursor pools and enzyme levels. A comprehensive study of the changes in enzymatic activities and precursor pool sizes have been previously reported for the mosquito Aedes aegypti JH biosynthesis pathway. In the present studies, we used two different quantitative approaches to describe and predict how changes in the individual metabolic reactions in the pathway affect JH synthesis. First, we constructed generalized additive models (GAMs) that described the association between changes in specific metabolite concentrations with changes in enzymatic activities and substrate concentrations. Changes in substrate concentrations explained 50% or more of the model deviances in 7 of the 13 metabolic steps analyzed. Addition of information on enzymatic activities almost always improved the fitness of GAMs built solely based on substrate concentrations. GAMs were validated using experimental data that were not included when the model was built. In addition, a system of ordinary differential equations (ODE) was developed to describe the instantaneous changes in metabolites as a function of the levels of enzymatic catalytic activities. The results demonstrated the ability of the models to predict changes in the flux of metabolites in the JH pathway, and can be used in the future to design and validate experimental manipulations of JH synthesis.

Model-assisted estimation of forest resources with generalized additive models

Treesearch

Jean D. Opsomer; F. Jay Breidt; Gretchen G. Moisen; Goran Kauermann

2007-01-01

Multiphase surveys are often conducted in forest inventories, with the goal of estimating forested area and tree characteristics over large regions. This article describes how design-based estimation of such quantities, based on information gathered during ground visits of sampled plots, can be made more precise by incorporating auxiliary information available from...

City Planning Unit: Grade 6.

ERIC Educational Resources Information Center

Dalton, William Edward

Described is a project designed to make government lessons and economics more appealing to sixth-grade students by having them set up and run a model city. General preparation procedures and set-up of the project, specific lesson plans, additional activities, and project evaluation are examined. An actual 3-dimensional model city was set up on…

Conceptualizations of Personality Disorders with the Five Factor Model-Count and Empathy Traits

ERIC Educational Resources Information Center

Kajonius, Petri J.; Dåderman, Anna M.

2017-01-01

Previous research has long advocated that emotional and behavioral disorders are related to general personality traits, such as the Five Factor Model (FFM). The addition of section III in the latest "Diagnostic and Statistical Manual of Mental Disorders" (DSM) recommends that extremity in personality traits together with maladaptive…

A Review of Research on Universal Design Educational Models

ERIC Educational Resources Information Center

Rao, Kavita; Ok, Min Wook; Bryant, Brian R.

2014-01-01

Universal design for learning (UDL) has gained considerable attention in the field of special education, acclaimed for its promise to promote inclusion by supporting access to the general curriculum. In addition to UDL, there are two other universal design (UD) educational models referenced in the literature, universal design of instruction (UDI)…

Additive-dominance genetic model analyses for late-maturity alpha-amylase activity in a bread wheat factorial crossing population.

PubMed

Rasul, Golam; Glover, Karl D; Krishnan, Padmanaban G; Wu, Jixiang; Berzonsky, William A; Ibrahim, Amir M H

2015-12-01

Elevated level of late maturity α-amylase activity (LMAA) can result in low falling number scores, reduced grain quality, and downgrade of wheat (Triticum aestivum L.) class. A mating population was developed by crossing parents with different levels of LMAA. The F2 and F3 hybrids and their parents were evaluated for LMAA, and data were analyzed using the R software package 'qgtools' integrated with an additive-dominance genetic model and a mixed linear model approach. Simulated results showed high testing powers for additive and additive × environment variances, and comparatively low powers for dominance and dominance × environment variances. All variance components and their proportions to the phenotypic variance for the parents and hybrids were significant except for the dominance × environment variance. The estimated narrow-sense heritability and broad-sense heritability for LMAA were 14 and 54%, respectively. High significant negative additive effects for parents suggest that spring wheat cultivars 'Lancer' and 'Chester' can serve as good general combiners, and that 'Kinsman' and 'Seri-82' had negative specific combining ability in some hybrids despite of their own significant positive additive effects, suggesting they can be used as parents to reduce LMAA levels. Seri-82 showed very good general combining ability effect when used as a male parent, indicating the importance of reciprocal effects. High significant negative dominance effects and high-parent heterosis for hybrids demonstrated that the specific hybrid combinations; Chester × Kinsman, 'Lerma52' × Lancer, Lerma52 × 'LoSprout' and 'Janz' × Seri-82 could be generated to produce cultivars with significantly reduced LMAA level.

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

PubMed

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.

Translational Animal Models of Atopic Dermatitis for Preclinical Studies



PubMed Central

Martel, Britta C.; Lovato, Paola; Bäumer, Wolfgang; Olivry, Thierry

2017-01-01

There is a medical need to develop new treatments for patients suffering from atopic dermatitis (AD). To improve the discovery and testing of novel treatments, relevant animal models for AD are needed. Generally, these animal models mimic different aspects of the pathophysiology of human AD, such as skin barrier defects and Th2 immune bias with additional Th1 and Th22, and in some populations Th17, activation. However, the pathomechanistic characterization and pharmacological validation of these animal models are generally incomplete. In this paper, we review animal models of AD in the context of preclinical use and their possible translation to the human disease. Most of these models use mice, but we will also critically evaluate dog models of AD, as increasing information on disease mechanism show their likely relevance for the human disease. PMID:28955179

Generalized gas-solid adsorption modeling: Single-component equilibria

DOE PAGES

Ladshaw, Austin; Yiacoumi, Sotira; Tsouris, Costas; ...

2015-01-07

Over the last several decades, modeling of gas–solid adsorption at equilibrium has generally been accomplished through the use of isotherms such as the Freundlich, Langmuir, Tóth, and other similar models. While these models are relatively easy to adapt for describing experimental data, their simplicity limits their generality to be used with many different sets of data. This limitation forces engineers and scientists to test each different model in order to evaluate which one can best describe their data. Additionally, the parameters of these models all have a different physical interpretation, which may have an effect on how they can bemore » further extended into kinetic, thermodynamic, and/or mass transfer models for engineering applications. Therefore, it is paramount to adopt not only a more general isotherm model, but also a concise methodology to reliably optimize for and obtain the parameters of that model. A model of particular interest is the Generalized Statistical Thermodynamic Adsorption (GSTA) isotherm. The GSTA isotherm has enormous flexibility, which could potentially be used to describe a variety of different adsorption systems, but utilizing this model can be fairly difficult due to that flexibility. To circumvent this complication, a comprehensive methodology and computer code has been developed that can perform a full equilibrium analysis of adsorption data for any gas-solid system using the GSTA model. The code has been developed in C/C++ and utilizes a Levenberg–Marquardt’s algorithm to handle the non-linear optimization of the model parameters. Since the GSTA model has an adjustable number of parameters, the code iteratively goes through all number of plausible parameters for each data set and then returns the best solution based on a set of scrutiny criteria. Data sets at different temperatures are analyzed serially and then linear correlations with temperature are made for the parameters of the model. The end result is a full set of optimal GSTA parameters, both dimensional and non-dimensional, as well as the corresponding thermodynamic parameters necessary to predict the behavior of the system at temperatures for which data were not available. It will be shown that this code, utilizing the GSTA model, was able to describe a wide variety of gas-solid adsorption systems at equilibrium.In addition, a physical interpretation of these results will be provided, as well as an alternate derivation of the GSTA model, which intends to reaffirm the physical meaning.« less

Observational viability and stability of nonlocal cosmology

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

Deser, S.; Woodard, R.P., E-mail: deser@brandeis.edu, E-mail: woodard@phys.ufl.edu

2013-11-01

We show that the nonlocal gravity models, proposed to explain current cosmic acceleration without dark energy, pass two essential tests: first, they can be defined so as not to alter the, observationally correct, general relativity predictions for gravitationally bound systems. Second, they are stable, ghost-free, with no additional excitations beyond those of general relativity. In this they differ from their, ghostful, localized versions. The systems' initial value constraints are the same as in general relativity, and our nonlocal modifications never convert the original gravitons into ghosts.

Modeling statistics and kinetics of the natural aggregation structures and processes with the solution of generalized logistic equation

NASA Astrophysics Data System (ADS)

Maslov, Lev A.; Chebotarev, Vladimir I.

2017-02-01

The generalized logistic equation is proposed to model kinetics and statistics of natural processes such as earthquakes, forest fires, floods, landslides, and many others. This equation has the form dN(A)/dA = s dot (1-N(A)) dot N(A)q dot A-α, q>0q>0 and A>0A>0 is the size of an element of a structure, and α≥0. The equation contains two exponents α and q taking into account two important properties of elements of a system: their fractal geometry, and their ability to interact either to enhance or to damp the process of aggregation. The function N(A)N(A) can be understood as an approximation to the number of elements the size of which is less than AA. The function dN(A)/dAdN(A)/dA where N(A)N(A) is the general solution of this equation for q=1 is a product of an increasing bounded function and power-law function with stretched exponential cut-off. The relation with Tsallis non-extensive statistics is demonstrated by solving the generalized logistic equation for q>0q>0. In the case 01q>1 it models sub-additive structures. The Gutenberg-Richter (G-R) formula results from interpretation of empirical data as a straight line in the area of stretched exponent with small α. The solution is applied for modeling distribution of foreshocks and aftershocks in the regions of Napa Valley 2014, and Sumatra 2004 earthquakes fitting the observed data well, both qualitatively and quantitatively.

Use of Forest Inventory and Analysis information in wildlife habitat modeling: a process for linking multiple scales

Treesearch

Thomas C. Edwards; Gretchen G. Moisen; Tracey S. Frescino; Joshua L. Lawler

2002-01-01

We describe our collective efforts to develop and apply methods for using FIA data to model forest resources and wildlife habitat. Our work demonstrates how flexible regression techniques, such as generalized additive models, can be linked with spatially explicit environmental information for the mapping of forest type and structure. We illustrate how these maps of...

Air-water analogy and the study of hydraulic models

NASA Technical Reports Server (NTRS)

Supino, Giulio

1953-01-01

The author first sets forth some observations about the theory of models. Then he established certain general criteria for the construction of dynamically similar models in water and in air, through reference to the perfect fluid equations and to the ones pertaining to viscous flow. It is, in addition, pointed out that there are more cases in which the analogy is possible than is commonly supposed.

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

PubMed

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 quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data.

Additional Research Needs to Support the GENII Biosphere Models

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

Napier, Bruce A.; Snyder, Sandra F.; Arimescu, Carmen

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.

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

River catchment rainfall series analysis using additive Holt-Winters method

NASA Astrophysics Data System (ADS)

Puah, Yan Jun; Huang, Yuk Feng; Chua, Kuan Chin; Lee, Teang Shui

2016-03-01

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable.

Search for photonic signatures of gauge-mediated supersymmetry in 13 TeV p p collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Afik, Y.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Alderweireldt, S.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allaire, C.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Ambroz, L.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amoroso, S.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Annovi, A.; Antel, C.; Anthony, M. T.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Araujo Pereira, R.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkin, R. J.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Avramidou, R.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Bagnaia, P.; Bahmani, M.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Bakker, P. J.; Bakshi Gupta, D.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Bandyopadhyay, A.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnea, R.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bauer, K. T.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Beck, H. C.; Becker, K.; Becker, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behera, A.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Bergsten, L. J.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertram, I. A.; Bertsche, C.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Bethani, A.; Bethke, S.; Betti, A.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Bierwagen, K.; Biesuz, N. V.; Biglietti, M.; Billoud, T. R. V.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blumenschein, U.; Blunier, Dr.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Bonilla, J. S.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bozson, A. J.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Braren, F.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Bruno, S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Büscher, D.; Büscher, V.; Buschmann, E.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabras, G.; Cabrera Urbán, S.; Caforio, D.; Cai, H.; Cairo, V. M. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Calvetti, M.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Cao, Y.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Casadei, D.; Casado, M. P.; Casha, A. F.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, C.; Chen, H.; Chen, J.; Chen, J.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, I.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, Y. S.; Christodoulou, V.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Cinca, D.; Cindro, V.; Cioarǎ, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Clark, A.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corrigan, E. E.; Corriveau, F.; Cortes-Gonzalez, A.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czekierda, S.; Czodrowski, P.; D'Amen, G.; D'Auria, S.; D'Eramo, L.; D'Onofrio, M.; da Cunha Sargedas de Sousa, M. J.; da Via, C.; Dabrowski, W.; Dado, T.; Dahbi, S.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dartsi, O.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; de, K.; de Asmundis, R.; de Benedetti, A.; de Castro, S.; de Cecco, S.; de Groot, N.; de Jong, P.; de la Torre, H.; de Lorenzi, F.; de Maria, A.; de Pedis, D.; de Salvo, A.; de Sanctis, U.; de Santo, A.; de Vasconcelos Corga, K.; de Vivie de Regie, J. B.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; Della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; Demarco, D. A.; Demers, S.; Demichev, M.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; di Bello, F. A.; di Ciaccio, A.; di Ciaccio, L.; di Clemente, W. K.; di Donato, C.; di Girolamo, A.; di Micco, B.; di Nardo, R.; di Petrillo, K. F.; di Simone, A.; di Sipio, R.; di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Dias Do Vale, T.; Diaz, M. A.; Dickinson, J.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; Do Vale, M. A. 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T.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Merlassino, C.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Millar, D. A.; Miller, D. W.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Minegishi, Y.; Ming, Y.; Mir, L. M.; Mirto, A.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mizukami, A.; Mjörnmark, J. U.; Mkrtchyan, T.; Mlynarikova, M.; Moa, T.; Mochizuki, K.; Mogg, P.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. 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E.; Nemecek, S.; Nemethy, P.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Newman, P. R.; Ng, T. Y.; Ng, Y. S.; Nguyen, H. D. N.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforou, N.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nishu, N.; Nisius, R.; Nitsche, I.; Nitta, T.; Nobe, T.; Noguchi, Y.; Nomachi, M.; Nomidis, I.; Nomura, M. A.; Nooney, T.; Nordberg, M.; Norjoharuddeen, N.; Novak, T.; Novgorodova, O.; Novotny, R.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'Connor, K.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Oliver, J. L.; Olsson, M. J. R.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oppen, H.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orgill, E. C.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero Y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Pacheco Rodriguez, L.; Padilla Aranda, C.; Pagan Griso, S.; Paganini, M.; Paige, F.; Palacino, G.; Palazzo, S.; Palestini, S.; Palka, M.; Pallin, D.; Panagiotopoulou, E. St.; Panagoulias, I.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parida, B.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasner, J. M.; Pasqualucci, E.; Passaggio, S.; Pastore, Fr.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearson, B.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Pereira Peixoto, A. P.; Perepelitsa, D. V.; Peri, F.; Perini, L.; Pernegger, H.; Perrella, S.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Pham, T.; Phillips, F. H.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pinamonti, M.; Pinfold, J. L.; Pitt, M.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Pluth, D.; Podberezko, P.; Poettgen, R.; Poggi, R.; Poggioli, L.; Pogrebnyak, I.; Pohl, D.; Pokharel, I.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Ponomarenko, D.; Pontecorvo, L.; Popeneciu, G. A.; Portillo Quintero, D. M.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potti, H.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. 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Y.; Shen, Y.; Sherafati, N.; Sherman, A. D.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silva, M.; Silverstein, S. B.; Simic, L.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffa, A. M.; Soffer, A.; Søgaard, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, W.; Sopczak, A.; Sopkova, F.; Sosa, D.; Sotiropoulou, C. L.; Sottocornola, S.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Stegler, M.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stevenson, T. J.; Stewart, G. A.; Stockton, M. C.; Stoicea, G.; Stolte, P.; Stonjek, S.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, Dms; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sydorenko, A.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Tahirovic, E.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeda, K.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarek Abouelfadl Mohamed, A. T.; Tarem, S.; Tarna, G.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, A. J.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Thais, S. J.; Theveneaux-Pelzer, T.; Thiele, F.; Thomas, J. P.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tian, Y.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Uno, K.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vadla, K. O. H.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valente, M.; Valentinetti, S.; Valero, A.; Valéry, L.; Vallier, A.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Furelos, D.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von Buddenbrock, S. E.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Wakamiya, K.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, A. M.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.-J.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. M.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Weston, T. D.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, A.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Woods, N. L.; Worm, S. D.; Wosiek, B. K.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, H.; Xu, L.; Xu, T.; Xu, W.; Yabsley, B.; Yacoob, S.; Yajima, K.; Yallup, D. P.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamanaka, T.; Yamane, F.; Yamatani, M.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, S.; Yang, Y.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhou, Y.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zhulanov, V.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zorbas, T. G.; Zou, R.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2018-05-01

A search is presented for photonic signatures, motivated by generalized models of gauge-mediated supersymmetry breaking. This search makes use of proton-proton collision data at √{s }=13 TeV corresponding to an integrated luminosity of 36.1 fb-1 recorded by the ATLAS detector at the LHC, and it explores models dominated by both strong and electroweak production of supersymmetric partner states. Experimental signatures incorporating an isolated photon and significant missing transverse momentum are explored. These signatures include events with an additional photon or additional jet activity not associated with any specific underlying quark flavor. No significant excess of events is observed above the Standard Model prediction, and 95% confidence-level upper limits of between 0.083 and 0.32 fb are set on the visible cross section of contributions from physics beyond the Standard Model. These results are interpreted in terms of lower limits on the masses of gluinos, squarks, and gauginos in the context of generalized models of gauge-mediated supersymmetry, which reach as high as 2.3 TeV for strongly produced and 1.3 TeV for weakly produced supersymmetric partner pairs.

Effects of Anisotropy on Scalar Field Ghost Dark Energy and the Non-Equilibrium Thermodynamics in Fractal Cosmology

NASA Astrophysics Data System (ADS)

Najafi, A.; Hossienkhani, H.

2017-10-01

Since the fractal cosmology has been created in early universe, therefore their models were mostly isotropic. The majority of previous studies had been based on FRW universe, while in the early universe, the best model for describing fractal cosmology is actually the anisotropic universe. Therefore in this work, by assuming the anisotropic universe, the cosmological implications of ghost and generalized ghost dark energy models with dark matter in fractal cosmology has been discussed. Moreover, the different kinds of dark energy models such as quintessence and tachyon field, with the generalized ghost dark energy in fractal universe has been investigated. In addition, we have reconstructed the Hubble parameter, H, the energy density, ρ, the deceleration parameter, q, the equations of state parameter, {ω }{{}D}, for both ghost and generalized ghost dark energy models. This correspondence allows us to reconstruct the potential and the dynamics of a fractal canonical scalar field according to the evolution of generalized ghost dark energy density. Eventually, thermodynamics of the cosmological apparent horizon in fractal cosmology was investigated and the validity of the Generalized second law of thermodynamics (GSLT) have been examined in an anisotropic universe. The results show the influence of the anisotropy on the GSLT of thermodynamics in a fractal cosmology.

A tale of twin Higgs: natural twin two Higgs doublet models

DOE PAGES

Yu, Jiang-Hao

2016-12-28

In original twin Higgs model, vacuum misalignment between electroweak and new physics scales is realized by adding explicit Z 2 breaking term. Introducing additional twin Higgs could accommodate spontaneous Z 2 breaking, which explains origin of this misalignment. We introduce a class of twin two Higgs doublet models with most general scalar potential, and discuss general conditions which trigger electroweak and Z 2 symmetry breaking. Various scenarios on realising the vacuum misalignment are systematically discussed in a natural composite two Higgs double model framework: explicit Z 2 breaking, radiative Z 2 breaking, tadpole-induced Z 2 breaking, and quartic-induced Z 2more » breaking. Finally, we investigate the Higgs mass spectra and Higgs phenomenology in these scenarios.« less

Interpretation of snow-climate feedback as produced by 17 general circulation models

NASA Technical Reports Server (NTRS)

Cess, R. D.; Zhang, M.-H.; Potter, G. L.; Blanchet, J.-P.; Chalita, S.; Colman, R.; Dazlich, D. A.; Del Genio, A. D.; Lacis, A. A.; Dymnikov, V.

1991-01-01

Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

Planetary Moon Cycler Trajectories

NASA Technical Reports Server (NTRS)

Russell, Ryan P.; Strange, Nathan J.

2007-01-01

Free-return cycler trajectories repeatedly shuttle a spacecraft between two bodies using little or no fuel. Here, the cycler architecture is proposed as a complementary and alternative method for designing planetary moon tours. Previously applied enumerative cycler search and optimization techniques are generalized and specifically implemented in the Jovian and Saturnian moon systems. In addition, the algorithms are tested for general use to find non-Earth heliocentric cyclers. Overall, hundreds of ideal model ballistic cycler geometries are found and several representative cases are documented and discussed. Many of the ideal model solutions are found to remain ballistic in a zero radius sphere of influence patched conic ephemeris model, and preliminary work in a high-fidelity fully integrated model demonstrates near-ballistic cycles for several example cases.

Don't soil your chances with solar energy: Experiments of natural dust accumulation on solar modules and the effect on light transmission

NASA Astrophysics Data System (ADS)

Boyle, Liza

Dust accumulation, or soiling, on solar energy harvesting systems can cause significant losses that reduce the power output of the system, increase pay-back time of the system, and reduce confidence in solar energy overall. Developing a method of estimating soiling losses could greatly improve estimates of solar energy system outputs, greatly improve operation and maintenance of solar systems, and improve siting of solar energy systems. This dissertation aims to develop a soiling model by collecting ambient soiling data as well as other environmental data and fitting a model to these data. In general a process-level approach is taken to estimating soiling. First a comparison is made between mass of deposited particulates and transmission loss. Transmission loss is the reduction in light that a solar system would see due to soiling, and mass accumulation represents the level of soiling in the system. This experiment is first conducted at two sites in the Front Range of Colorado and then expanded to three additional sites. Second mass accumulation is examined as a function of airborne particulate matter (PM) concentrations, airborne size distributions, and meteorological data. In depth analysis of this process step is done at the first two sites in Colorado, and a more general analysis is done at the three additional sites. This step is identified as less understood step, but with results still allowing for a general soiling model to be developed. Third these two process steps are combined, and spatial variability of these steps are examined. The three additional sites (an additional site in the Front Range of Colorado, a site in Albuquerque New Mexico, and a site in Cocoa Florida) represent a much more spatially and climatically diverse set of locations than the original two sites and provide a much broader sample space in which to develop the combined soiling model. Finally a few additional parameters, precipitation, micro-meteorology, and some sampling artifacts, are cursorily examined. This is to provide a broader context for these results and to help future researchers in understanding the strengths and weaknesses of this dissertation and the results presented within.

Modelling water hammer in viscoelastic pipelines: short brief

NASA Astrophysics Data System (ADS)

Urbanowicz, K.; Firkowski, M.; Zarzycki, Z.

2016-10-01

The model of water hammer in viscoelastic pipelines is analyzed. An appropriate mathematical model of water hammer in polymer pipelines is presented. An additional term has been added to continuity equation to describe the retarded deformation of the pipe wall. The mechanical behavior of viscoelastic material is described by generalized Kelvin-Voigt model. The comparison of numerical simulation and experimental data from well known papers is presented. Short discussion about obtained results are given.

Numerical simulation of groundwater flow for the Yakima River basin aquifer system, Washington

USGS Publications Warehouse

Ely, D.M.; Bachmann, M.P.; Vaccaro, J.J.

2011-01-01

Five applications (scenarios) of the model were completed to obtain a better understanding of the relation between pumpage and surface-water resources and groundwater levels. For the first three scenarios, the calibrated transient model was used to simulate conditions without: (1) pumpage from all hydrogeologic units, (2) pumpage from basalt hydrogeologic units, and (3) exempt-well pumpage. The simulation results indicated potential streamflow capture by the existing pumpage from 1960 through 2001. The quantity of streamflow capture generally was inversely related to the total quantity of pumpage eliminated in the model scenarios. For the fourth scenario, the model simulated 1994 through 2001 under existing conditions with additional pumpage estimated for pending groundwater applications. The differences between the calibrated model streamflow and this scenario indicated additional decreases in streamflow of 91 cubic feet per second in the model domain. Existing conditions representing 1994 through 2001 were projected through 2025 for the fifth scenario and indicated additional streamflow decreases of 38 cubic feet per second and groundwater-level declines.

Structural validation of the Self-Compassion Scale with a German general population sample

PubMed Central

Kwakkenbos, Linda; Moran, Chelsea; Thombs, Brett; Albani, Cornelia; Bourkas, Sophia; Zenger, Markus; Brahler, Elmar; Körner, Annett

2018-01-01

Background Published validation studies have reported different factor structures for the Self-Compassion Scale (SCS). The objective of this study was to assess the factor structure of the SCS in a large general population sample representative of the German population. Methods A German population sample completed the SCS and other self-report measures. Confirmatory factor analysis (CFA) in MPlus was used to test six models previously found in factor analytic studies (unifactorial model, two-factor model, three-factor model, six-factor model, a hierarchical (second order) model with six first-order factors and two second-order factors, and a model with arbitrarily assigned items to six factors). In addition, three bifactor models were also tested: bifactor model #1 with two group factors (SCS positive items, called SCS positive) and SCS negative items, called SCS negative) and one general factor (overall SCS); bifactor model #2, which is a two-tier model with six group factors, three (SCS positive subscales) corresponding to one general dimension (SCS positive) and three (SCS negative subscales) corresponding to the second general dimension (SCS negative); bifactor model #3 with six group factors (six SCS subscales) and one general factor (overall SCS). Results The two-factor model, the six-factor model, and the hierarchical model showed less than ideal, but acceptable fit. The model fit indices for these models were comparable, with no apparent advantage of the six-factor model over the two-factor model. The one-factor model, the three-factor model, and bifactor model #3 showed poor fit. The other two bifactor models showed strong support for two factors: SCS positive and SCS negative. Conclusion The main results of this study are that, among the German general population, six SCS factors and two SCS factors fit the data reasonably well. While six factors can be modelled, the three negative factors and the three positive factors, respectively, did not reflect reliable or meaningful variance beyond the two summative positive and negative item factors. As such, we recommend the use of two subscale scores to capture a positive factor and a negative factor when administering the German SCS to general population samples and we strongly advise against the use of a total score across all SCS items. PMID:29408888

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

PubMed

Wood, Phillip Karl; Jackson, Kristina M

2013-08-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating "protective" or "launch" factors or as "developmental snares." These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of "general deviance" over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the "general deviance" model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of "general deviance" can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve 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.

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

PubMed Central

WOOD, PHILLIP KARL; JACKSON, KRISTINA M.

2014-01-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating “protective” or “launch” factors or as “developmental snares.” These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of “general deviance” over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the “general deviance” model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of “general deviance” can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve 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. PMID:23880389

Color generalization across hue and saturation in chicks described by a simple (Bayesian) model.

PubMed

Scholtyssek, Christine; Osorio, Daniel C; Baddeley, Roland J

2016-08-01

Color conveys important information for birds in tasks such as foraging and mate choice, but in the natural world color signals can vary substantially, so birds may benefit from generalizing responses to perceptually discriminable colors. Studying color generalization is therefore a way to understand how birds take account of suprathreshold stimulus variations in decision making. Former studies on color generalization have focused on hue variation, but natural colors often vary in saturation, which could be an additional, independent source of information. We combine behavioral experiments and statistical modeling to investigate whether color generalization by poultry chicks depends on the chromatic dimension in which colors vary. Chicks were trained to discriminate colors separated by equal distances on a hue or a saturation dimension, in a receptor-based color space. Generalization tests then compared the birds' responses to familiar and novel colors lying on the same chromatic dimension. To characterize generalization we introduce a Bayesian model that extracts a threshold color distance beyond which chicks treat novel colors as significantly different from the rewarded training color. These thresholds were the same for generalization along the hue and saturation dimensions, demonstrating that responses to novel colors depend on similarity and expected variation of color signals but are independent of the chromatic dimension.

Bayesian Models for Astrophysical Data Using R, JAGS, Python, and Stan

NASA Astrophysics Data System (ADS)

Hilbe, Joseph M.; de Souza, Rafael S.; Ishida, Emille E. O.

2017-05-01

This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally.

The effect of binary mixtures of zinc, copper, cadmium, and nickel on the growth of the freshwater diatom Navicula pelliculosa and comparison with mixture toxicity model predictions.

PubMed

Nagai, Takashi; De Schamphelaere, Karel A C

2016-11-01

The authors investigated the effect of binary mixtures of zinc (Zn), copper (Cu), cadmium (Cd), and nickel (Ni) on the growth of a freshwater diatom, Navicula pelliculosa. A 7 × 7 full factorial experimental design (49 combinations in total) was used to test each binary metal mixture. A 3-d fluorescence microplate toxicity assay was used to test each combination. Mixture effects were predicted by concentration addition and independent action models based on a single-metal concentration-response relationship between the relative growth rate and the calculated free metal ion activity. Although the concentration addition model predicted the observed mixture toxicity significantly better than the independent action model for the Zn-Cu mixture, the independent action model predicted the observed mixture toxicity significantly better than the concentration addition model for the Cd-Zn, Cd-Ni, and Cd-Cu mixtures. For the Zn-Ni and Cu-Ni mixtures, it was unclear which of the 2 models was better. Statistical analysis concerning antagonistic/synergistic interactions showed that the concentration addition model is generally conservative (with the Zn-Ni mixture being the sole exception), indicating that the concentration addition model would be useful as a method for a conservative first-tier screening-level risk analysis of metal mixtures. Environ Toxicol Chem 2016;35:2765-2773. © 2016 SETAC. © 2016 SETAC.

Postgraduate general dentistry residency: a clinical model.

PubMed

Gowan, J

1995-01-01

Dental graduates today are expected to be knowledgeable in many more areas than their predecessors. Changing technology and increased competition require entering the dental profession with more experience and skills. One approach to achieving this skill level is a postgraduate general dentistry residency in a clinical setting during the year following dental school graduation (PGY1). The clinical residency provides new dentists with additional hands-on training and reinforces classroom learning. HealthPartners was selected as a clinical rotation for residents in the advanced general dentistry program at the University of Minnesota Dental School. The program provides dental graduates in PGY1 training in all areas of practice. The HealthPartners rotation is highly unique. It is a staff model HMO with a clinical, multi-specialty setting. Today, HealthPartners--a Minnesota-based healthcare organization--has 116,000 members with prepaid dental benefits. Residents trained in the program develop increased skills in all areas of dental practice. In addition, they develop a good working knowledge in the basic sciences. Methods of instruction include didactic training in the form of seminars, lectures, and clinical training in HealthPartners' dental clinics.

Structural equation models of VMT growth in US urbanised areas.

USGS Publications Warehouse

Ewing, Reid; Hamidi, Shima; Gallivan, Frank; Nelson, Arthur C.; Grace, James B.

2014-01-01

Vehicle miles travelled (VMT) is a primary performance indicator for land use and transportation, bringing with it both positive and negative externalities. This study updates and refines previous work on VMT in urbanised areas, using recent data, additional metrics and structural equation modelling (SEM). In a cross-sectional model for 2010, population, income and freeway capacity are positively related to VMT, while gasoline prices, development density and transit service levels are negatively related. Findings of the cross-sectional model are generally confirmed in a more tightly controlled longitudinal study of changes in VMT between 2000 and 2010, the first model of its kind. The cross-sectional and longitudinal models together, plus the transportation literature generally, give us a basis for generalising across studies to arrive at elasticity values of VMT with respect to different urban variables.

Ultimate strength performance of tankers associated with industry corrosion addition practices

NASA Astrophysics Data System (ADS)

Kim, Do Kyun; Kim, Han Byul; Zhang, Xiaoming; Li, Chen Guang; Paik, Jeom Kee

2014-09-01

In the ship and offshore structure design, age-related problems such as corrosion damage, local denting, and fatigue damage are important factors to be considered in building a reliable structure as they have a significant influence on the residual structural capacity. In shipping, corrosion addition methods are widely adopted in structural design to prevent structural capacity degradation. The present study focuses on the historical trend of corrosion addition rules for ship structural design and investigates their effects on the ultimate strength performance such as hull girder and stiffened panel of double hull oil tankers. Three types of rules based on corrosion addition models, namely historic corrosion rules (pre-CSR), Common Structural Rules (CSR), and harmonised Common Structural Rules (CSRH) are considered and compared with two other corrosion models namely UGS model, suggested by the Union of Greek Shipowners (UGS), and Time-Dependent Corrosion Wastage Model (TDCWM). To identify the general trend in the effects of corrosion damage on the ultimate longitudinal strength performance, the corrosion addition rules are applied to four representative sizes of double hull oil tankers namely Panamax, Aframax, Suezmax, and VLCC. The results are helpful in understanding the trend of corrosion additions for tanker structures

Definition of ground test for verification of large space structure control

NASA Technical Reports Server (NTRS)

Seltzer, S. M.; Doane, G. B., III

1985-01-01

Directions regarding the analytical models were received. A counter balance arm with weights was added at the top of the ASTROMAST to offset the arm with the gimbals. In addition to this model, three more models were requested from MSFC: structure as in the revised model with the addition of lumped masses at bays 46 and 91 of the ASTROMAST; cantilevered cruciform structure with lumped masses at bays 46 and 91, and an all up cruciform structure with lumped masses at bays 46 and 91. Figures for each model and their corresponding natural frequencies and general mode shapes associated with these frequencies are included. The drawbar in use in the cruciform models must be incorporated into the antenna and ASTROMAST models. The total tensile load carrying capability of the ASTROMAST is approximately 840 pounds.

Effects of hydrokinetic turbine sound on the behavior of four species of fish within an experimental mesocosm

DOE PAGES

Schramm, Michael P.; Bevelhimer, Mark; Scherelis, Constantin

2017-02-04

The development of hydrokinetic energy technologies (e.g., tidal turbines) has raised concern over the potential impacts of underwater sound produced by hydrokinetic turbines on fish species likely to encounter these turbines. To assess the potential for behavioral impacts, we exposed four species of fish to varying intensities of recorded hydrokinetic turbine sound in a semi-natural environment. Although we tested freshwater species (redhorse suckers [Moxostoma spp], freshwater drum [Aplondinotus grunniens], largemouth bass [Micropterus salmoides], and rainbow trout [Oncorhynchus mykiss]), these species are also representative of the hearing physiology and sensitivity of estuarine species that would be affected at tidal energy sites.more » Here, we evaluated changes in fish position relative to different intensities of turbine sound as well as trends in location over time with linear mixed-effects and generalized additive mixed models. We also evaluated changes in the proportion of near-source detections relative to sound intensity and exposure time with generalized linear mixed models and generalized additive models. Models indicated that redhorse suckers may respond to sustained turbine sound by increasing distance from the sound source. Freshwater drum models suggested a mixed response to turbine sound, and largemouth bass and rainbow trout models did not indicate any likely responses to turbine sound. Lastly, findings highlight the importance for future research to utilize accurate localization systems, different species, validated sound transmission distances, and to consider different types of behavioral responses to different turbine designs and to the cumulative sound of arrays of multiple turbines.« less

Effects of hydrokinetic turbine sound on the behavior of four species of fish within an experimental mesocosm

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

Schramm, Michael P.; Bevelhimer, Mark; Scherelis, Constantin

The development of hydrokinetic energy technologies (e.g., tidal turbines) has raised concern over the potential impacts of underwater sound produced by hydrokinetic turbines on fish species likely to encounter these turbines. To assess the potential for behavioral impacts, we exposed four species of fish to varying intensities of recorded hydrokinetic turbine sound in a semi-natural environment. Although we tested freshwater species (redhorse suckers [Moxostoma spp], freshwater drum [Aplondinotus grunniens], largemouth bass [Micropterus salmoides], and rainbow trout [Oncorhynchus mykiss]), these species are also representative of the hearing physiology and sensitivity of estuarine species that would be affected at tidal energy sites.more » Here, we evaluated changes in fish position relative to different intensities of turbine sound as well as trends in location over time with linear mixed-effects and generalized additive mixed models. We also evaluated changes in the proportion of near-source detections relative to sound intensity and exposure time with generalized linear mixed models and generalized additive models. Models indicated that redhorse suckers may respond to sustained turbine sound by increasing distance from the sound source. Freshwater drum models suggested a mixed response to turbine sound, and largemouth bass and rainbow trout models did not indicate any likely responses to turbine sound. Lastly, findings highlight the importance for future research to utilize accurate localization systems, different species, validated sound transmission distances, and to consider different types of behavioral responses to different turbine designs and to the cumulative sound of arrays of multiple turbines.« less

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

Yu, Jiang-Hao

In original twin Higgs model, vacuum misalignment between electroweak and new physics scales is realized by adding explicit Z 2 breaking term. Introducing additional twin Higgs could accommodate spontaneous Z 2 breaking, which explains origin of this misalignment. We introduce a class of twin two Higgs doublet models with most general scalar potential, and discuss general conditions which trigger electroweak and Z 2 symmetry breaking. Various scenarios on realising the vacuum misalignment are systematically discussed in a natural composite two Higgs double model framework: explicit Z 2 breaking, radiative Z 2 breaking, tadpole-induced Z 2 breaking, and quartic-induced Z 2more » breaking. Finally, we investigate the Higgs mass spectra and Higgs phenomenology in these scenarios.« less

Fuzzy set methods for object recognition in space applications

NASA Technical Reports Server (NTRS)

Keller, James M.

1991-01-01

During the reporting period, the development of the theory and application of methodologies for decision making under uncertainty was addressed. Two subreports are included; the first on properties of general hybrid operators, while the second considers some new research on generalized threshold logic units. In the first part, the properties of the additive gamma-model, where the intersection part is first considered to be the product of the input values and the union part is obtained by an extension of De Morgan's law to fuzzy sets, is explored. Then the Yager's class of union and intersection is used in the additive gamma-model. The inputs are weighted to some power that represents their importance and thus their contribution to the compensation process. In the second part, the extension of binary logic synthesis methods to multiple valued logic synthesis methods to enable the synthesis of decision networks when the input/output variables are not binary is discussed.

An alternative Biot's displacement formulation for porous materials.

PubMed

Dazel, Olivier; Brouard, Bruno; Depollier, Claude; Griffiths, Stéphane

2007-06-01

This paper proposes an alternative displacement formulation of Biot's linear model for poroelastic materials. Its advantage is a simplification of the formalism without making any additional assumptions. The main difference between the method proposed in this paper and the original one is the choice of the generalized coordinates. In the present approach, the generalized coordinates are chosen in order to simplify the expression of the strain energy, which is expressed as the sum of two decoupled terms. Hence, new equations of motion are obtained whose elastic forces are decoupled. The simplification of the formalism is extended to Biot and Willis thought experiments, and simpler expressions of the parameters of the three Biot waves are also provided. A rigorous derivation of equivalent and limp models is then proposed. It is finally shown that, for the particular case of sound-absorbing materials, additional simplifications of the formalism can be obtained.

Some problems of the calculation of three-dimensional boundary layer flows on general configurations

NASA Technical Reports Server (NTRS)

Cebeci, T.; Kaups, K.; Mosinskis, G. J.; Rehn, J. A.

1973-01-01

An accurate solution of the three-dimensional boundary layer equations over general configurations such as those encountered in aircraft and space shuttle design requires a very efficient, fast, and accurate numerical method with suitable turbulence models for the Reynolds stresses. The efficiency, speed, and accuracy of a three-dimensional numerical method together with the turbulence models for the Reynolds stresses are examined. The numerical method is the implicit two-point finite difference approach (Box Method) developed by Keller and applied to the boundary layer equations by Keller and Cebeci. In addition, a study of some of the problems that may arise in the solution of these equations for three-dimensional boundary layer flows over general configurations.

Decision Support Tool Evaluation Report for General NOAA Oil Modeling Environment(GNOME) Version 2.0

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hall, Callie; Zanoni, Vicki; Blonski, Slawomir; D'Sa, Eurico; Estep, Lee; Holland, Donald; Moore, Roxzana F.; Pagnutti, Mary; Terrie, Gregory

2004-01-01

NASA's Earth Science Applications Directorate evaluated the potential of NASA remote sensing data and modeling products to enhance the General NOAA Oil Modeling Environment (GNOME) decision support tool. NOAA's Office of Response and Restoration (OR&R) Hazardous Materials (HAZMAT) Response Division is interested in enhancing GNOME with near-realtime (NRT) NASA remote sensing products on oceanic winds and ocean circulation. The NASA SeaWinds sea surface wind and Jason-1 sea surface height NRT products have potential, as do sea surface temperature and reflectance products from the Moderate Resolution Imaging Spectroradiometer and sea surface reflectance products from Landsat and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer. HAZMAT is also interested in the Advanced Circulation model and the Ocean General Circulation Model. Certain issues must be considered, including lack of data continuity, marginal data redundancy, and data formatting problems. Spatial resolution is an issue for near-shore GNOME applications. Additional work will be needed to incorporate NASA inputs into GNOME, including verification and validation of data products, algorithms, models, and NRT data.

A Three-Component Model for Magnetization Transfer. Solution by Projection-Operator Technique, and Application to Cartilage

NASA Astrophysics Data System (ADS)

Adler, Ronald S.; Swanson, Scott D.; Yeung, Hong N.

1996-01-01

A projection-operator technique is applied to a general three-component model for magnetization transfer, extending our previous two-component model [R. S. Adler and H. N. Yeung,J. Magn. Reson. A104,321 (1993), and H. N. Yeung, R. S. Adler, and S. D. Swanson,J. Magn. Reson. A106,37 (1994)]. The PO technique provides an elegant means of deriving a simple, effective rate equation in which there is natural separation of relaxation and source terms and allows incorporation of Redfield-Provotorov theory without any additional assumptions or restrictive conditions. The PO technique is extended to incorporate more general, multicomponent models. The three-component model is used to fit experimental data from samples of human hyaline cartilage and fibrocartilage. The fits of the three-component model are compared to the fits of the two-component model.

On the stochastic dissemination of faults in an admissible network

NASA Technical Reports Server (NTRS)

Kyrala, A.

1987-01-01

The dynamic distribution of faults in a general type network is discussed. The starting point is a uniquely branched network in which each pair of nodes is connected by a single branch. Mathematical expressions for the uniquely branched network transition matrix are derived to show that sufficient stationarity exists to ensure the validity of the use of the Markov Chain model to analyze networks. In addition the conditions for the use of Semi-Markov models are discussed. General mathematical expressions are derived in an examination of branch redundancy techniques commonly used to increase reliability.

The generalized Hill model: A kinematic approach towards active muscle contraction

NASA Astrophysics Data System (ADS)

Göktepe, Serdar; Menzel, Andreas; Kuhl, Ellen

2014-12-01

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.

Probability Weighting Functions Derived from Hyperbolic Time Discounting: Psychophysical Models and Their Individual Level Testing.

PubMed

Takemura, Kazuhisa; Murakami, Hajime

2016-01-01

A probability weighting function (w(p)) is considered to be a nonlinear function of probability (p) in behavioral decision theory. This study proposes a psychophysical model of probability weighting functions derived from a hyperbolic time discounting model and a geometric distribution. The aim of the study is to show probability weighting functions from the point of view of waiting time for a decision maker. Since the expected value of a geometrically distributed random variable X is 1/p, we formulized the probability weighting function of the expected value model for hyperbolic time discounting as w(p) = (1 - k log p)(-1). Moreover, the probability weighting function is derived from Loewenstein and Prelec's (1992) generalized hyperbolic time discounting model. The latter model is proved to be equivalent to the hyperbolic-logarithmic weighting function considered by Prelec (1998) and Luce (2001). In this study, we derive a model from the generalized hyperbolic time discounting model assuming Fechner's (1860) psychophysical law of time and a geometric distribution of trials. In addition, we develop median models of hyperbolic time discounting and generalized hyperbolic time discounting. To illustrate the fitness of each model, a psychological experiment was conducted to assess the probability weighting and value functions at the level of the individual participant. The participants were 50 university students. The results of individual analysis indicated that the expected value model of generalized hyperbolic discounting fitted better than previous probability weighting decision-making models. The theoretical implications of this finding are discussed.

Male Role Norms Inventory-Short Form (MRNI-SF): development, confirmatory factor analytic investigation of structure, and measurement invariance across gender.

PubMed

Levant, Ronald F; Hall, Rosalie J; Rankin, Thomas J

2013-04-01

The current study reports the development from the Male Role Norms Inventory-Revised (MRNI-R; Levant, Rankin, Williams, Hasan, & Smalley, 2010) of the 21-item MRNI-Short Form (MRNI-SF). Confirmatory factor analysis of MRNI-SF responses from a sample of 1,017 undergraduate participants (549 men, 468 women) indicated that the best fitting "bifactor" model incorporated the hypothesized 7-factor structure while explicitly modeling an additional, general traditional masculinity ideology factor. Specifically, each item-level indicator loaded on 2 factors: a general traditional masculinity ideology factor and a specific factor corresponding to 1 of the 7 hypothesized traditional masculinity ideology norms. The bifactor model was assessed for measurement invariance across gender groups, with findings of full configural invariance and partial metric invariance, such that factor loadings were equivalent across the gender groups for the 7 specific factors but not for the general traditional masculinity ideology factor. Theoretical explanations for this latter result include the potential that men's sense of self or identity may be engaged when responding to questions asking to what extent they agree or disagree with normative statements about their behavior, a possibility that could be investigated in future research by examining the associations of the general and specific factors with measures of masculine identity. Additional exploratory invariance analyses demonstrated latent mean differences between men and women on 4 of the 8 factors, and equivocal results for invariance of item intercepts, item uniquenesses, and factor variances-covariances.

Effects of methyl mercury in combination with polychlorinated biphenyls and brominated flame retardants on the uptake of glutamate in rat brain synaptosomes: a mathematical approach for the study of mixtures.

PubMed

Stavenes Andersen, Ingrid; Voie, Oyvind Albert; Fonnum, Frode; Mariussen, Espen

2009-11-01

Regulatory limit values for toxicants are in general determined by the toxicology of the single compounds. However, little is known about their combined effects. Methyl mercury (MeHg), polychlorinated biphenyls (PCBs), and brominated flame retardants (BFRs) are dominant contaminants in the environment and food. MeHg is a well known neurotoxicant, especially affecting the developing brain. There is increasing evidence that PCB and BFRs also have neurotoxic effects. An enhanced effect of these toxicants, due to either synergistic or additive effects, would be considered as a risk for the fetal development. Here we studied the combinatorial effects of MeHg in combination with PCB or BFR on the reuptake of glutamate in synaptosomes. To provide the optimal conclusion regarding type of interaction, we have analyzed the data using two mathematical models, the Löewe model of additivity and Bliss' model of independent action. Binary and ternary mixtures in different proportions were made. The toxicants had primarily additive effects, as shown with both models, although tendencies towards synergism were observed. MeHg was by far the most potent inhibitor of uptake with an EC(50) value of 0.33 microM. A reconstituted mixture from a relevant fish sample was made in order to elucidate which chemical was responsible for the observed effect. Some interaction was experienced between PCB and MeHg, but in general MeHg seemed to explain the observed effect. We also show that mixture effects should not be assessed by effect addition.

Comparing Factor, Class, and Mixture Models of Cannabis Initiation and DSM Cannabis Use Disorder Criteria, Including Craving, in the Brisbane Longitudinal Twin Study

PubMed Central

Kubarych, Thomas S.; Kendler, Kenneth S.; Aggen, Steven H.; Estabrook, Ryne; Edwards, Alexis C.; Clark, Shaunna L.; Martin, Nicholas G.; Hickie, Ian B.; Neale, Michael C.; Gillespie, Nathan A.

2014-01-01

Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use. PMID:24588857

A two-phase micromorphic model for compressible granular materials

NASA Astrophysics Data System (ADS)

Paolucci, Samuel; Li, Weiming; Powers, Joseph

2009-11-01

We introduce a new two-phase continuum model for compressible granular material based on micromorphic theory and treat it as a two-phase mixture with inner structure. By taking an appropriate number of moments of the local micro scale balance equations, the average phase balance equations result from a systematic averaging procedure. In addition to equations for mass, momentum and energy, the balance equations also include evolution equations for microinertia and microspin tensors. The latter equations combine to yield a general form of a compaction equation when the material is assumed to be isotropic. When non-linear and inertial effects are neglected, the generalized compaction equation reduces to that originally proposed by Bear and Nunziato. We use the generalized compaction equation to numerically model a mixture of granular high explosive and interstitial gas. One-dimensional shock tube and piston-driven solutions are presented and compared with experimental results and other known solutions.

On the general constraints in single qubit quantum process tomography

DOE PAGES

Bhandari, Ramesh; Peters, Nicholas A.

2016-05-18

In this study, we briefly review single-qubit quantum process tomography for trace-preserving and nontrace-preserving processes, and derive explicit forms of the general constraints for fitting experimental data. These forms provide additional insight into the structure of the process matrix. We illustrate this with several examples, including a discussion of qubit leakage error models and the intuition which can be gained from their process matrices.

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

PubMed

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.

Bayesian inference in an item response theory model with a generalized student t link function

NASA Astrophysics Data System (ADS)

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.

A new computational growth model for sea urchin skeletons.

PubMed

Zachos, Louis G

2009-08-07

A new computational model has been developed to simulate growth of regular sea urchin skeletons. The model incorporates the processes of plate addition and individual plate growth into a composite model of whole-body (somatic) growth. A simple developmental model based on hypothetical morphogens underlies the assumptions used to define the simulated growth processes. The data model is based on a Delaunay triangulation of plate growth center points, using the dual Voronoi polygons to define plate topologies. A spherical frame of reference is used for growth calculations, with affine deformation of the sphere (based on a Young-Laplace membrane model) to result in an urchin-like three-dimensional form. The model verifies that the patterns of coronal plates in general meet the criteria of Voronoi polygonalization, that a morphogen/threshold inhibition model for plate addition results in the alternating plate addition pattern characteristic of sea urchins, and that application of the Bertalanffy growth model to individual plates results in simulated somatic growth that approximates that seen in living urchins. The model suggests avenues of research that could explain some of the distinctions between modern sea urchins and the much more disparate groups of forms that characterized the Paleozoic Era.

Stability and value of male care for offspring: is it worth only half the trouble?

PubMed

Fromhage, Lutz; McNamara, John M; Houston, Alasdair I

2007-06-22

Models of parental investment often assume a trade-off for males between providing care and seeking additional mating opportunities. It is not obvious, however, how such additional matings should be accounted for in a consistent population model, because deserting males might increase their fertilization success at the cost of either caring males, other deserting males or both. Here, we present a game theory model that addresses all of these possibilities in a general way. In contrast to earlier work, we find that the source of deserting males' additional matings is irrelevant to the evolutionary stability of male care. We reject the claim that fitness gains through male care are intrinsically less valuable than those through desertion, and that the former must therefore be down-weighted by 1/2 when compared with the latter.

Constraining f(R) gravity in solar system, cosmology and binary pulsar systems

NASA Astrophysics Data System (ADS)

Liu, Tan; Zhang, Xing; Zhao, Wen

2018-02-01

The f (R) gravity can be cast into the form of a scalar-tensor theory, and scalar degree of freedom can be suppressed in high-density regions by the chameleon mechanism. In this article, for the general f (R) gravity, using a scalar-tensor representation with the chameleon mechanism, we calculate the parametrized post-Newtonian parameters γ and β, the effective gravitational constant Geff, and the effective cosmological constant Λeff. In addition, for the general f (R) gravity, we also calculate the rate of orbital period decay of the binary system due to gravitational radiation. Then we apply these results to specific f (R) models (Hu-Sawicki model, Tsujikawa model and Starobinsky model) and derive the constraints on the model parameters by combining the observations in solar system, cosmological scales and the binary systems.

Neurotoxicological and statistical analyses of a mixture of five organophosphorus pesticides using a ray design.

PubMed

Moser, V C; Casey, M; Hamm, A; Carter, W H; Simmons, J E; Gennings, C

2005-07-01

Environmental exposures generally involve chemical mixtures instead of single chemicals. Statistical models such as the fixed-ratio ray design, wherein the mixing ratio (proportions) of the chemicals is fixed across increasing mixture doses, allows for the detection and characterization of interactions among the chemicals. In this study, we tested for interaction(s) in a mixture of five organophosphorus (OP) pesticides (chlorpyrifos, diazinon, dimethoate, acephate, and malathion). The ratio of the five pesticides (full ray) reflected the relative dietary exposure estimates of the general population as projected by the US EPA Dietary Exposure Evaluation Model (DEEM). A second mixture was tested using the same dose levels of all pesticides, but excluding malathion (reduced ray). The experimental approach first required characterization of dose-response curves for the individual OPs to build a dose-additivity model. A series of behavioral measures were evaluated in adult male Long-Evans rats at the time of peak effect following a single oral dose, and then tissues were collected for measurement of cholinesterase (ChE) activity. Neurochemical (blood and brain cholinesterase [ChE] activity) and behavioral (motor activity, gait score, tail-pinch response score) endpoints were evaluated statistically for evidence of additivity. The additivity model constructed from the single chemical data was used to predict the effects of the pesticide mixture along the full ray (10-450 mg/kg) and the reduced ray (1.75-78.8 mg/kg). The experimental mixture data were also modeled and statistically compared to the additivity models. Analysis of the 5-OP mixture (the full ray) revealed significant deviation from additivity for all endpoints except tail-pinch response. Greater-than-additive responses (synergism) were observed at the lower doses of the 5-OP mixture, which contained non-effective dose levels of each of the components. The predicted effective doses (ED20, ED50) were about half that predicted by additivity, and for brain ChE and motor activity, there was a threshold shift in the dose-response curves. For the brain ChE and motor activity, there was no difference between the full (5-OP mixture) and reduced (4-OP mixture) rays, indicating that malathion did not influence the non-additivity. While the reduced ray for blood ChE showed greater deviation from additivity without malathion in the mixture, the non-additivity observed for the gait score was reversed when malathion was removed. Thus, greater-than-additive interactions were detected for both the full and reduced ray mixtures, and the role of malathion in the interactions varied depending on the endpoint. In all cases, the deviations from additivity occurred at the lower end of the dose-response curves.

Genetic analyses of protein yield in dairy cows applying random regression models with time-dependent and temperature x humidity-dependent covariates.

PubMed

Brügemann, K; Gernand, E; von Borstel, U U; König, S

2011-08-01

Data used in the present study included 1,095,980 first-lactation test-day records for protein yield of 154,880 Holstein cows housed on 196 large-scale dairy farms in Germany. Data were recorded between 2002 and 2009 and merged with meteorological data from public weather stations. The maximum distance between each farm and its corresponding weather station was 50 km. Hourly temperature-humidity indexes (THI) were calculated using the mean of hourly measurements of dry bulb temperature and relative humidity. On the phenotypic scale, an increase in THI was generally associated with a decrease in daily protein yield. For genetic analyses, a random regression model was applied using time-dependent (d in milk, DIM) and THI-dependent covariates. Additive genetic and permanent environmental effects were fitted with this random regression model and Legendre polynomials of order 3 for DIM and THI. In addition, the fixed curve was modeled with Legendre polynomials of order 3. Heterogeneous residuals were fitted by dividing DIM into 5 classes, and by dividing THI into 4 classes, resulting in 20 different classes. Additive genetic variances for daily protein yield decreased with increasing degrees of heat stress and were lowest at the beginning of lactation and at extreme THI. Due to higher additive genetic variances, slightly higher permanent environment variances, and similar residual variances, heritabilities were highest for low THI in combination with DIM at the end of lactation. Genetic correlations among individual values for THI were generally >0.90. These trends from the complex random regression model were verified by applying relatively simple bivariate animal models for protein yield measured in 2 THI environments; that is, defining a THI value of 60 as a threshold. These high correlations indicate the absence of any substantial genotype × environment interaction for protein yield. However, heritabilities and additive genetic variances from the random regression model tended to be slightly higher in the THI range corresponding to cows' comfort zone. Selecting such superior environments for progeny testing can contribute to an accurate genetic differentiation among selection candidates. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genomic selection of purebred animals for crossbred performance in the presence of dominant gene action

PubMed Central

2013-01-01

Background Genomic selection is an appealing method to select purebreds for crossbred performance. In the case of crossbred records, single nucleotide polymorphism (SNP) effects can be estimated using an additive model or a breed-specific allele model. In most studies, additive gene action is assumed. However, dominance is the likely genetic basis of heterosis. Advantages of incorporating dominance in genomic selection were investigated in a two-way crossbreeding program for a trait with different magnitudes of dominance. Training was carried out only once in the simulation. Results When the dominance variance and heterosis were large and overdominance was present, a dominance model including both additive and dominance SNP effects gave substantially greater cumulative response to selection than the additive model. Extra response was the result of an increase in heterosis but at a cost of reduced purebred performance. When the dominance variance and heterosis were realistic but with overdominance, the advantage of the dominance model decreased but was still significant. When overdominance was absent, the dominance model was slightly favored over the additive model, but the difference in response between the models increased as the number of quantitative trait loci increased. This reveals the importance of exploiting dominance even in the absence of overdominance. When there was no dominance, response to selection for the dominance model was as high as for the additive model, indicating robustness of the dominance model. The breed-specific allele model was inferior to the dominance model in all cases and to the additive model except when the dominance variance and heterosis were large and with overdominance. However, the advantage of the dominance model over the breed-specific allele model may decrease as differences in linkage disequilibrium between the breeds increase. Retraining is expected to reduce the advantage of the dominance model over the alternatives, because in general, the advantage becomes important only after five or six generations post-training. Conclusion Under dominance and without retraining, genomic selection based on the dominance model is superior to the additive model and the breed-specific allele model to maximize crossbred performance through purebred selection. PMID:23621868

Assessment of parametric uncertainty for groundwater reactive transport modeling,

USGS Publications Warehouse

Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.; Miller, Geoffery L.; Meyer, Philip D.; Kohler, Matthias; Yabusaki, Steve; Wu, Jichun

2014-01-01

The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood functions, improve model calibration, and reduce predictive uncertainty in other groundwater reactive transport and environmental modeling.

Uncertain programming models for portfolio selection with uncertain returns

NASA Astrophysics Data System (ADS)

Zhang, Bo; Peng, Jin; Li, Shengguo

2015-10-01

In an indeterminacy economic environment, experts' knowledge about the returns of securities consists of much uncertainty instead of randomness. This paper discusses portfolio selection problem in uncertain environment in which security returns cannot be well reflected by historical data, but can be evaluated by the experts. In the paper, returns of securities are assumed to be given by uncertain variables. According to various decision criteria, the portfolio selection problem in uncertain environment is formulated as expected-variance-chance model and chance-expected-variance model by using the uncertainty programming. Within the framework of uncertainty theory, for the convenience of solving the models, some crisp equivalents are discussed under different conditions. In addition, a hybrid intelligent algorithm is designed in the paper to provide a general method for solving the new models in general cases. At last, two numerical examples are provided to show the performance and applications of the models and algorithm.

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

NASA Astrophysics Data System (ADS)

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.

The effect of surface boundary conditions on the climate generated by a coarse-mesh general circulation model

NASA Technical Reports Server (NTRS)

Cohen, C.

1981-01-01

A hierarchy of experiments was run, starting with an all water planet with zonally symmetric sea surface temperatures, then adding, one at a time, flat continents, mountains, surface physics, and realistic sea surface temperatures. The model was run with the sun fixed at a perpetual January. Ensemble means and standard deviations were computed and the t-test was used to determine the statistical significance of the results. The addition of realistic surface physics does not affect the model climatology to as large as extent as does the addition of mountains. Departures from zonal symmetry of the SST field result in a better simulation of the real atmosphere.

Fifteenth NASTRAN (R) Users' Colloquium

NASA Technical Reports Server (NTRS)

1987-01-01

Numerous applications of the NASA Structural Analysis (NASTRAN) computer program, a general purpose finite element code, are discussed. Additional features that can be added to NASTRAN, interactive plotting of NASTRAN data on microcomputers, mass modeling for bars, the design of wind tunnel models, the analysis of ship structures subjected to underwater explosions, and buckling analysis of radio antennas are among the topics discussed.

Microscopic Interpretation and Generalization of the Bloch-Torrey Equation for Diffusion Magnetic Resonance

PubMed Central

Seroussi, Inbar; Grebenkov, Denis S.; Pasternak, Ofer; Sochen, Nir

2017-01-01

In order to bridge microscopic molecular motion with macroscopic diffusion MR signal in complex structures, we propose a general stochastic model for molecular motion in a magnetic field. The Fokker-Planck equation of this model governs the probability density function describing the diffusion-magnetization propagator. From the propagator we derive a generalized version of the Bloch-Torrey equation and the relation to the random phase approach. This derivation does not require assumptions such as a spatially constant diffusion coefficient, or ad-hoc selection of a propagator. In particular, the boundary conditions that implicitly incorporate the microstructure into the diffusion MR signal can now be included explicitly through a spatially varying diffusion coefficient. While our generalization is reduced to the conventional Bloch-Torrey equation for piecewise constant diffusion coefficients, it also predicts scenarios in which an additional term to the equation is required to fully describe the MR signal. PMID:28242566

General integrable n-level, many-mode Janes-Cummings-Dicke models and classical r-matrices with spectral parameters

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

Skrypnyk, T., E-mail: taras.skrypnyk@unimib.it, E-mail: tskrypnyk@imath.kiev.ua

Using the technique of classical r-matrices and quantum Lax operators, we construct the most general form of the quantum integrable “n-level, many-mode” spin-boson Jaynes-Cummings-Dicke-type hamiltonians describing an interaction of a molecule of N n-level atoms with many modes of electromagnetic field and containing, in general, additional non-linear interaction terms. We explicitly obtain the corresponding quantum Lax operators and spin-boson analogs of the generalized Gaudin hamiltonians and prove their quantum commutativity. We investigate symmetries of the obtained models that are associated with the geometric symmetries of the classical r-matrices and construct the corresponding algebra of quantum integrals. We consider in detailmore » three classes of non-skew-symmetric classical r-matrices with spectral parameters and explicitly obtain the corresponding quantum Lax operators and Jaynes-Cummings-Dicke-type hamiltonians depending on the considered r-matrix.« less

Slushy weightings for the optimal pilot model. [considering visual tracking task

NASA Technical Reports Server (NTRS)

Dillow, J. D.; Picha, D. G.; Anderson, R. O.

1975-01-01

A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.

Student Engagement as a General Factor of Classroom Experience: Associations with Student Practices and Educational Outcomes in a University Gateway Course

PubMed Central

Shernof, David J.; Ruzek, Erik A.; Sannella, Alexander J.; Schorr, Roberta Y.; Sanchez-Wall, Lina; Bressler, Denise M.

2017-01-01

The purpose of this study was to evaluate a model for considering general and specific elements of student experience in a gateway course in undergraduate Financial Accounting in a large university on the East Coast, USA. Specifically, the study evaluated a bifactor analytic strategy including a general factor of student classroom experience, conceptualized as student engagement as rooted in flow theory, as well as factors representing specific dimensions of experience. The study further evaluated the association between these general and specific factors and both student classroom practices and educational outcomes. The sample of students (N = 407) in two cohorts of the undergraduate financial accounting course participated in the Experience Sampling Method (ESM) measuring students' classroom practices, perceptions, engagement, and perceived learning throughout the one-semester course. Course grade information was also collected. Results showed that a two-level bifactor model fit the data better than two traditional (i.e., non-bifactor) models and also avoided significant multicollinearity of the traditional models. In addition to student engagement (general factor), specific dimensions of classroom experience in the bifactor model at the within-student level included intrinsic motivation, academic intensity, salience, and classroom self-esteem. At the between-student level, specific aspects included work orientation, learning orientation, classroom self-esteem, and disengagement. Multilevel Structural Equation Modeling (MSEM) demonstrated that sitting in the front of the classroom (compared to the sitting in the back), taking notes, active listening, and working on problems during class had a positive effect on within-student variation in student engagement and attention. Engagement, in turn, predicted perceived learning. With respect to between-student effects, the tendency to sit in front seats had a significant effect on student engagement, which in turn had a significant effect on perceived learning and course grades. A significant indirect relationship of seating and active learning strategies on learning and course grade as mediated by student engagement was found. Support for the general aspect of student classroom experience was interpreted with flow theory and suggested the need for additional research. Findings also suggested that active learning strategies are associated with positive learning outcomes even in educational environments where possibilities for action are relatively constrained. PMID:28663733

Student Engagement as a General Factor of Classroom Experience: Associations with Student Practices and Educational Outcomes in a University Gateway Course.

PubMed

Shernof, David J; Ruzek, Erik A; Sannella, Alexander J; Schorr, Roberta Y; Sanchez-Wall, Lina; Bressler, Denise M

2017-01-01

The purpose of this study was to evaluate a model for considering general and specific elements of student experience in a gateway course in undergraduate Financial Accounting in a large university on the East Coast, USA. Specifically, the study evaluated a bifactor analytic strategy including a general factor of student classroom experience, conceptualized as student engagement as rooted in flow theory, as well as factors representing specific dimensions of experience. The study further evaluated the association between these general and specific factors and both student classroom practices and educational outcomes. The sample of students ( N = 407) in two cohorts of the undergraduate financial accounting course participated in the Experience Sampling Method (ESM) measuring students' classroom practices, perceptions, engagement, and perceived learning throughout the one-semester course. Course grade information was also collected. Results showed that a two-level bifactor model fit the data better than two traditional (i.e., non-bifactor) models and also avoided significant multicollinearity of the traditional models. In addition to student engagement (general factor), specific dimensions of classroom experience in the bifactor model at the within-student level included intrinsic motivation, academic intensity, salience, and classroom self-esteem. At the between-student level, specific aspects included work orientation, learning orientation, classroom self-esteem, and disengagement. Multilevel Structural Equation Modeling (MSEM) demonstrated that sitting in the front of the classroom (compared to the sitting in the back), taking notes, active listening, and working on problems during class had a positive effect on within-student variation in student engagement and attention. Engagement, in turn, predicted perceived learning. With respect to between-student effects, the tendency to sit in front seats had a significant effect on student engagement, which in turn had a significant effect on perceived learning and course grades. A significant indirect relationship of seating and active learning strategies on learning and course grade as mediated by student engagement was found. Support for the general aspect of student classroom experience was interpreted with flow theory and suggested the need for additional research. Findings also suggested that active learning strategies are associated with positive learning outcomes even in educational environments where possibilities for action are relatively constrained.

Using Case Studies as a Semester-Long Tool to Teach Neuroanatomy and Structure-Function Relationships to Undergraduates

PubMed Central

Kennedy, Susan

2013-01-01

In addition to being inherently interesting to students, case studies can serve as useful tools to teach neuroanatomy and demonstrate important relationships between brain structure and function. In most undergraduate courses, however, neuroanatomy is presented to students as a “unit” or chapter, much like other topics (e.g., receptors, pharmacology) covered in the course, over a period of a week or two. In this article, a relatively simple model of teaching neuroanatomy is described in which students are actively engaged in the presentation and discussion of case studies throughout the semester, following a general introduction to the structure of the nervous system. In this way, the teaching of neuroanatomy is “distributed” throughout the semester and put into a more user-friendly context for students as additional topics are introduced. Generally, students report enjoying learning brain structure using this method, and commented positively on the class activities associated with learning brain anatomy. Advantages and disadvantages of such a model are presented, as are suggestions for implementing similar models of undergraduate neuroanatomy education. PMID:24319386

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

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 1 2011-04-01 2011-04-01 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...

Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada

USGS Publications Warehouse

Rodriguez, Brian D.; Sweetkind, Donald S.

2015-01-01

The 3-D inversion was generally able to reproduce the gross resistivity structure of the “known” model, but the simulated conductive volcanic composite unit horizons were often too shallow when compared to the “known” model. Additionally, the chosen computation parameters such as station spacing appear to have resulted in computational artifacts that are difficult to interpret but could potentially be removed with further refinements of the 3-D resistivity inversion modeling technique.

APPLICATION OF THE SURFACE COMPLEXATION CONCEPT TO COMPLEX MINERAL ASSEMBLAGES

EPA Science Inventory

Two types of modeling approaches are illustrated for describing inorganic contaminant adsorption in aqueous environments: (a) the component additivity approach and (b) the generalized composite approach. Each approach is applied to simulate Zn2+ adsorption by a well-characterize...

A family of dynamic models for large-eddy simulation

NASA Technical Reports Server (NTRS)

Carati, D.; Jansen, K.; Lund, T.

1995-01-01

Since its first application, the dynamic procedure has been recognized as an effective means to compute rather than prescribe the unknown coefficients that appear in a subgrid-scale model for Large-Eddy Simulation (LES). The dynamic procedure is usually used to determine the nondimensional coefficient in the Smagorinsky (1963) model. In reality the procedure is quite general and it is not limited to the Smagorinsky model by any theoretical or practical constraints. The purpose of this note is to consider a generalized family of dynamic eddy viscosity models that do not necessarily rely on the local equilibrium assumption built into the Smagorinsky model. By invoking an inertial range assumption, it will be shown that the coefficients in the new models need not be nondimensional. This additional degree of freedom allows the use of models that are scaled on traditionally unknown quantities such as the dissipation rate. In certain cases, the dynamic models with dimensional coefficients are simpler to implement, and allow for a 30% reduction in the number of required filtering operations.

Cascade generalized predictive control strategy for boiler drum level.

PubMed

Xu, Min; Li, Shaoyuan; Cai, Wenjian

2005-07-01

This paper proposes a cascade model predictive control scheme for boiler drum level control. By employing generalized predictive control structures for both inner and outer loops, measured and unmeasured disturbances can be effectively rejected, and drum level at constant load is maintained. In addition, nonminimum phase characteristic and system constraints in both loops can be handled effectively by generalized predictive control algorithms. Simulation results are provided to show that cascade generalized predictive control results in better performance than that of well tuned cascade proportional integral differential controllers. The algorithm has also been implemented to control a 75-MW boiler plant, and the results show an improvement over conventional control schemes.

Mathematical Modeling of Intestinal Iron Absorption Using Genetic Programming

PubMed Central

Colins, Andrea; Gerdtzen, Ziomara P.; Nuñez, Marco T.; Salgado, J. Cristian

2017-01-01

Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex systems. PMID:28072870

A geostatistical extreme-value framework for fast simulation of natural hazard events

PubMed Central

Stephenson, David B.

2016-01-01

We develop a statistical framework for simulating natural hazard events that combines extreme value theory and geostatistics. Robust generalized additive model forms represent generalized Pareto marginal distribution parameters while a Student’s t-process captures spatial dependence and gives a continuous-space framework for natural hazard event simulations. Efficiency of the simulation method allows many years of data (typically over 10 000) to be obtained at relatively little computational cost. This makes the model viable for forming the hazard module of a catastrophe model. We illustrate the framework by simulating maximum wind gusts for European windstorms, which are found to have realistic marginal and spatial properties, and validate well against wind gust measurements. PMID:27279768

A Steady State and Quasi-Steady Interface Between the Generalized Fluid System Simulation Program and the SINDA/G Thermal Analysis Program

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Majumdar, Alok; Tiller, Bruce

2001-01-01

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program SINDA/G. The flow code, GFSSP, is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasisteady (unsteady solid, steady fluid) conjugate heat transfer modeling.

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

PubMed Central

2013-01-01

Background 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. Methods 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. Results 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. Conclusions The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data. PMID:24192051

Comparing physically-based and statistical landslide susceptibility model outputs - a case study from Lower Austria

NASA Astrophysics Data System (ADS)

Canli, Ekrem; Thiebes, Benni; Petschko, Helene; Glade, Thomas

2015-04-01

By now there is a broad consensus that due to human-induced global change the frequency and magnitude of heavy precipitation events is expected to increase in certain parts of the world. Given the fact, that rainfall serves as the most common triggering agent for landslide initiation, also an increased landside activity can be expected there. Landslide occurrence is a globally spread phenomenon that clearly needs to be handled. The present and well known problems in modelling landslide susceptibility and hazard give uncertain results in the prediction. This includes the lack of a universal applicable modelling solution for adequately assessing landslide susceptibility (which can be seen as the relative indication of the spatial probability of landslide initiation). Generally speaking, there are three major approaches for performing landslide susceptibility analysis: heuristic, statistical and deterministic models, all with different assumptions, its distinctive data requirements and differently interpretable outcomes. Still, detailed comparison of resulting landslide susceptibility maps are rare. In this presentation, the susceptibility modelling outputs of a deterministic model (Stability INdex MAPping - SINMAP) and a statistical modelling approach (generalized additive model - GAM) are compared. SINMAP is an infinite slope stability model which requires parameterization of soil mechanical parameters. Modelling with the generalized additive model, which represents a non-linear extension of a generalized linear model, requires a high quality landslide inventory that serves as the dependent variable in the statistical approach. Both methods rely on topographical data derived from the DTM. The comparison has been carried out in a study area located in the district of Waidhofen/Ybbs in Lower Austria. For the whole district (ca. 132 km²), 1063 landslides have been mapped and partially used within the analysis and the validation of the model outputs. The respective susceptibility maps have been reclassified to contain three susceptibility classes each. The comparison of the susceptibility maps was performed on a grid cell basis. A match of the maps was observed for grid cells located in the same susceptibility class. In contrast, a mismatch or deviation was observed for locations with different assigned susceptibility classes (up to two classes' difference). Although the modelling approaches differ significantly, more than 70% of the pixels reveal a match in the same susceptibility class. A mismatch by two classes' difference occurred in less than 2% of all pixels. Although the result looks promising and strengthens the confidence in the susceptibility zonation for this area, some of the general drawbacks related to the respective approaches still have to be addressed in further detail. Future work is heading towards an integration of probabilistic aspects into deterministic modelling.

Wave–turbulence interaction-induced vertical mixing and its effects in ocean and climate models

PubMed Central

Qiao, Fangli; Yuan, Yeli; Deng, Jia; Dai, Dejun; Song, Zhenya

2016-01-01

Heated from above, the oceans are stably stratified. Therefore, the performance of general ocean circulation models and climate studies through coupled atmosphere–ocean models depends critically on vertical mixing of energy and momentum in the water column. Many of the traditional general circulation models are based on total kinetic energy (TKE), in which the roles of waves are averaged out. Although theoretical calculations suggest that waves could greatly enhance coexisting turbulence, no field measurements on turbulence have ever validated this mechanism directly. To address this problem, a specially designed field experiment has been conducted. The experimental results indicate that the wave–turbulence interaction-induced enhancement of the background turbulence is indeed the predominant mechanism for turbulence generation and enhancement. Based on this understanding, we propose a new parametrization for vertical mixing as an additive part to the traditional TKE approach. This new result reconfirmed the past theoretical model that had been tested and validated in numerical model experiments and field observations. It firmly establishes the critical role of wave–turbulence interaction effects in both general ocean circulation models and atmosphere–ocean coupled models, which could greatly improve the understanding of the sea surface temperature and water column properties distributions, and hence model-based climate forecasting capability. PMID:26953182

General self-tuning solutions and no-go theorem

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

Förste, Stefan; Kim, Jihn E.; Lee, Hyun Min, E-mail: forste@th.physik.uni-bonn.de, E-mail: jihnekim@gmail.com, E-mail: hyun.min.lee@kias.re.kr

2013-03-01

We consider brane world models with one extra dimension. In the bulk there is in addition to gravity a three form gauge potential or equivalently a scalar (by generalisation of electric magnetic duality). We find classical solutions for which the 4d effective cosmological constant is adjusted by choice of integration constants. No go theorems for such self-tuning mechanism are circumvented by unorthodox Lagrangians for the three form respectively the scalar. It is argued that the corresponding effective 4d theory always includes tachyonic Kaluza-Klein excitations or ghosts. Known no go theorems are extended to a general class of models with unorthodoxmore » Lagrangians.« less

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

PubMed

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

NASA Astrophysics Data System (ADS)

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.

Including resonances in the multiperipheral model

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

Pinsky, S.S.; Snider, D.R.; Thomas, G.H.

1973-10-01

A simple generalization of the multiperipheral model (MPM) and the Mueller--Regge Model (MRM) is given which has improved phenomenological capabilities by explicitly incorporating resonance phenomena, and still is simple enough to be an important theoretical laboratory. The model is discussed both with and without charge. In addition, the one channel, two channel, three channel and N channel cases are explicitly treated. Particular attention is paid to the constraints of charge conservation and positivity in the MRM. The recently proven equivalence between the MRM and MPM is extended to this model, and is used extensively. (auth)

Documentation of the Goddard Laboratory for atmospheres fourth-order two-layer shallow water model

NASA Technical Reports Server (NTRS)

Takacs, L. L. (Compiler)

1986-01-01

The theory and numerical treatment used in the 2-level GLA fourth-order shallow water model are described. This model was designed to emulate the horizontal finite differences used by the GLA Fourth-Order General Circulation Model (Kalnay et al., 1983) in addition to its grid structure, form of high-latitude and global filtering, and time-integration schemes. A user's guide is also provided instructing the user on how to create initial conditions, execute the model, and post-process the data history.

Geodesy- and geology-based slip-rate models for the Western United States (excluding California) national seismic hazard maps

USGS Publications Warehouse

Petersen, Mark D.; Zeng, Yuehua; Haller, Kathleen M.; McCaffrey, Robert; Hammond, William C.; Bird, Peter; Moschetti, Morgan; Shen, Zhengkang; Bormann, Jayne; Thatcher, Wayne

2014-01-01

The 2014 National Seismic Hazard Maps for the conterminous United States incorporate additional uncertainty in fault slip-rate parameter that controls the earthquake-activity rates than was applied in previous versions of the hazard maps. This additional uncertainty is accounted for by new geodesy- and geology-based slip-rate models for the Western United States. Models that were considered include an updated geologic model based on expert opinion and four combined inversion models informed by both geologic and geodetic input. The two block models considered indicate significantly higher slip rates than the expert opinion and the two fault-based combined inversion models. For the hazard maps, we apply 20 percent weight with equal weighting for the two fault-based models. Off-fault geodetic-based models were not considered in this version of the maps. Resulting changes to the hazard maps are generally less than 0.05 g (acceleration of gravity). Future research will improve the maps and interpret differences between the new models.

[Geographical coverage of the Mexican Healthcare System and a spatial analysis of utilization of its General Hospitals in 1998].

PubMed

Hernández-Avila, Juan E; Rodríguez, Mario H; Rodríguez, Norma E; Santos, René; Morales, Evangelina; Cruz, Carlos; Sepúlveda-Amor, Jaime

2002-01-01

To describe the geographical coverage of the Mexican Healthcare System (MHS) services and to assess the utilization of its General Hospitals. A Geographic Information System (GIS) was used to include sociodemographic data by locality, the geographical location of all MHS healthcare services, and data on hospital discharge records. A maximum likelihood estimation model was developed to assess the utilization levels of 217 MHS General Hospitals. The model included data on human resources, additional infrastructure, and the population within a 25 km radius. In 1998, 10,806 localities with 72 million inhabitants had at least one public healthcare unit, and 97.2% of the population lived within 50 km of a healthcare unit; however, over 18 million people lived in rural localities without a healthcare unit. The mean annual hospital occupation rate was 48.5 +/- 28.5 per 100 bed/years, with high variability within and between states. Hospital occupation was significantly associated with the number of physicians in the unit, and in the Mexican Institute of Social Security units utilization was associated with additional health infrastructure, and with the population's poverty index. GIS analysis allows improved estimation of the coverage and utilization of MHS hospitals.

Singlet model interference effects with high scale UV physics

DOE PAGES

Dawson, S.; Lewis, I. M.

2017-01-06

One of the simplest extensions of the Standard Model (SM) is the addition of a scalar gauge singlet, S . If S is not forbidden by a symmetry from mixing with the Standard Model Higgs boson, the mixing will generate non-SM rates for Higgs production and decays. Generally, there could also be unknown high energy physics that generates additional effective low energy interactions. We show that interference effects between the scalar resonance of the singlet model and the effective field theory (EFT) operators can have significant effects in the Higgs sector. Here, we examine a non- Z 2 symmetricmore » scalar singlet model and demonstrate that a fit to the 125 GeV Higgs boson couplings and to limits on high mass resonances, S , exhibit an interesting structure and possible large cancellations of effects between the resonance contribution and the new EFT interactions, that invalidate conclusions based on the renormalizable singlet model alone.« less

Generalised teleparallel quintom dark energy non-minimally coupled with the scalar torsion and a boundary term

NASA Astrophysics Data System (ADS)

Bahamonde, Sebastian; Marciu, Mihai; Rudra, Prabir

2018-04-01

Within this work, we propose a new generalised quintom dark energy model in the teleparallel alternative of general relativity theory, by considering a non-minimal coupling between the scalar fields of a quintom model with the scalar torsion component T and the boundary term B. In the teleparallel alternative of general relativity theory, the boundary term represents the divergence of the torsion vector, B=2∇μTμ, and is related to the Ricci scalar R and the torsion scalar T, by the fundamental relation: R=‑T+B. We have investigated the dynamical properties of the present quintom scenario in the teleparallel alternative of general relativity theory by performing a dynamical system analysis in the case of decomposable exponential potentials. The study analysed the structure of the phase space, revealing the fundamental dynamical effects of the scalar torsion and boundary couplings in the case of a more general quintom scenario. Additionally, a numerical approach to the model is presented to analyse the cosmological evolution of the system.

On the learning difficulty of visual and auditory modal concepts: Evidence for a single processing system.

PubMed

Vigo, Ronaldo; Doan, Karina-Mikayla C; Doan, Charles A; Pinegar, Shannon

2018-02-01

The logic operators (e.g., "and," "or," "if, then") play a fundamental role in concept formation, syntactic construction, semantic expression, and deductive reasoning. In spite of this very general and basic role, there are relatively few studies in the literature that focus on their conceptual nature. In the current investigation, we examine, for the first time, the learning difficulty experienced by observers in classifying members belonging to these primitive "modal concepts" instantiated with sets of acoustic and visual stimuli. We report results from two categorization experiments that suggest the acquisition of acoustic and visual modal concepts is achieved by the same general cognitive mechanism. Additionally, we attempt to account for these results with two models of concept learning difficulty: the generalized invariance structure theory model (Vigo in Cognition 129(1):138-162, 2013, Mathematical principles of human conceptual behavior, Routledge, New York, 2014) and the generalized context model (Nosofsky in J Exp Psychol Learn Mem Cogn 10(1):104-114, 1984, J Exp Psychol 115(1):39-57, 1986).

Identification of unmeasured variables in the set of model constraints of the data reconciliation in a power unit

NASA Astrophysics Data System (ADS)

Szega, Marcin; Nowak, Grzegorz Tadeusz

2013-12-01

In generalized method of data reconciliation as equations of conditions beside substance and energy balances can be used equations which don't have precisely the status of conservation lows. Empirical coefficients in these equations are traded as unknowns' values. To this kind of equations, in application of the generalized method of data reconciliation in supercritical power unit, can be classified: steam flow capacity of a turbine for a group of stages, adiabatic internal efficiency of group of stages, equations for pressure drop in pipelines and equations for heat transfer in regeneration heat exchangers. Mathematical model of a power unit was developed in the code Thermoflex. Using this model the off-design calculation has been made in several points of loads for the power unit. Using these calculations identification of unknown values and empirical coefficients for generalized method of data reconciliation used in power unit has been made. Additional equations of conditions will be used in the generalized method of data reconciliation which will be used in optimization of measurement placement in redundant measurement system in power unit for new control systems

A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations

NASA Astrophysics Data System (ADS)

Cariolle, D.; Teyssèdre, H.

2007-01-01

This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory works. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the resolution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000-2004. Overall, the results show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small. The model also reproduces fairly well the polar ozone variability, with notably the formation of "ozone holes" in the southern hemisphere with amplitudes and seasonal evolutions that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone contents inside the polar vortex of the southern hemisphere over longer periods in spring time. It is concluded that for the study of climatic scenarios or the assimilation of ozone data, the present parameterization gives an interesting alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models.

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

PubMed Central

Bürger, R; Gimelfarb, A

1999-01-01

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

Mouse Model of Halogenated Platinum Salt Hypersensitivity

EPA Science Inventory

Occupational exposure to halogenated platinum salts can trigger the development of asthma. Concern for increased asthma risk exists for the general population due to the use of platinum (Pt) in catalytic converters and its emerging use as a diesel fuel additive. To investigate a...

Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting, generalized additive models, and tree-based methods

Treesearch

Gretchen G. Moisen; Elizabeth A. Freeman; Jock A. Blackard; Tracey S. Frescino; Niklaus E. Zimmermann; Thomas C. Edwards

2006-01-01

Many efforts are underway to produce broad-scale forest attribute maps by modelling forest class and structure variables collected in forest inventories as functions of satellite-based and biophysical information. Typically, variants of classification and regression trees implemented in Rulequest's© See5 and Cubist (for binary and continuous responses,...

Characterizing Aeroelastic Systems Using Eigenanalysis, Explicitly Retaining The Aerodynamic Degrees of Freedom

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Dowell, Earl H.

2001-01-01

Discrete time aeroelastic models with explicitly retained aerodynamic modes have been generated employing a time marching vortex lattice aerodynamic model. This paper presents analytical results from eigenanalysis of these models. The potential of these models to calculate the behavior of modes that represent damped system motion (noncritical modes) in addition to the simple harmonic modes is explored. A typical section with only structural freedom in pitch is examined. The eigenvalues are examined and compared to experimental data. Issues regarding the convergence of the solution with regard to refining the aerodynamic discretization are investigated. Eigenvector behavior is examined; the eigenvector associated with a particular eigenvalue can be viewed as the set of modal participation factors for that particular mode. For the present formulation of the equations of motion, the vorticity for each aerodynamic element appears explicitly as an element of each eigenvector in addition to the structural dynamic generalized coordinates. Thus, modal participation of the aerodynamic degrees of freedom can be assessed in M addition to participation of structural degrees of freedom.

Update on Bayesian Blocks: Segmented Models for Sequential Data

NASA Technical Reports Server (NTRS)

Scargle, Jeff

2017-01-01

The Bayesian Block algorithm, in wide use in astronomy and other areas, has been improved in several ways. The model for block shape has been generalized to include other than constant signal rate - e.g., linear, exponential, or other parametric models. In addition the computational efficiency has been improved, so that instead of O(N**2) the basic algorithm is O(N) in most cases. Other improvements in the theory and application of segmented representations will be described.

Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping.

PubMed

Shafizadeh-Moghadam, Hossein; Valavi, Roozbeh; Shahabi, Himan; Chapi, Kamran; Shirzadi, Ataollah

2018-07-01

In this research, eight individual machine learning and statistical models are implemented and compared, and based on their results, seven ensemble models for flood susceptibility assessment are introduced. The individual models included artificial neural networks, classification and regression trees, flexible discriminant analysis, generalized linear model, generalized additive model, boosted regression trees, multivariate adaptive regression splines, and maximum entropy, and the ensemble models were Ensemble Model committee averaging (EMca), Ensemble Model confidence interval Inferior (EMciInf), Ensemble Model confidence interval Superior (EMciSup), Ensemble Model to estimate the coefficient of variation (EMcv), Ensemble Model to estimate the mean (EMmean), Ensemble Model to estimate the median (EMmedian), and Ensemble Model based on weighted mean (EMwmean). The data set covered 201 flood events in the Haraz watershed (Mazandaran province in Iran) and 10,000 randomly selected non-occurrence points. Among the individual models, the Area Under the Receiver Operating Characteristic (AUROC), which showed the highest value, belonged to boosted regression trees (0.975) and the lowest value was recorded for generalized linear model (0.642). On the other hand, the proposed EMmedian resulted in the highest accuracy (0.976) among all models. In spite of the outstanding performance of some models, nevertheless, variability among the prediction of individual models was considerable. Therefore, to reduce uncertainty, creating more generalizable, more stable, and less sensitive models, ensemble forecasting approaches and in particular the EMmedian is recommended for flood susceptibility assessment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Ensemble-Based Parameter Estimation in a Coupled General Circulation Model

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-09-10

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Whole-body PET parametric imaging employing direct 4D nested reconstruction and a generalized non-linear Patlak model

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Rahmim, Arman

2014-03-01

Graphical analysis is employed in the research setting to provide quantitative estimation of PET tracer kinetics from dynamic images at a single bed. Recently, we proposed a multi-bed dynamic acquisition framework enabling clinically feasible whole-body parametric PET imaging by employing post-reconstruction parameter estimation. In addition, by incorporating linear Patlak modeling within the system matrix, we enabled direct 4D reconstruction in order to effectively circumvent noise amplification in dynamic whole-body imaging. However, direct 4D Patlak reconstruction exhibits a relatively slow convergence due to the presence of non-sparse spatial correlations in temporal kinetic analysis. In addition, the standard Patlak model does not account for reversible uptake, thus underestimating the influx rate Ki. We have developed a novel whole-body PET parametric reconstruction framework in the STIR platform, a widely employed open-source reconstruction toolkit, a) enabling accelerated convergence of direct 4D multi-bed reconstruction, by employing a nested algorithm to decouple the temporal parameter estimation from the spatial image update process, and b) enhancing the quantitative performance particularly in regions with reversible uptake, by pursuing a non-linear generalized Patlak 4D nested reconstruction algorithm. A set of published kinetic parameters and the XCAT phantom were employed for the simulation of dynamic multi-bed acquisitions. Quantitative analysis on the Ki images demonstrated considerable acceleration in the convergence of the nested 4D whole-body Patlak algorithm. In addition, our simulated and patient whole-body data in the postreconstruction domain indicated the quantitative benefits of our extended generalized Patlak 4D nested reconstruction for tumor diagnosis and treatment response monitoring.

Near-road air pollutant concentrations of CO and PM 2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models

NASA Astrophysics Data System (ADS)

Zhang, Kai; Batterman, Stuart

2010-05-01

The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM 2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM 2.5 showed that GAM emission estimates were much higher (by 4-5 times) than the dispersion model results, and that the traffic-PM 2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM 2.5 concentrations, a likely result of underestimating PM 2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.

Numerical Test of the Additivity Principle in Anomalous Transport

NASA Astrophysics Data System (ADS)

Tamaki, Shuji

2017-10-01

The additivity principle (AP) is one of the remarkable predictions that systematically generates all information on current fluctuations once the value of average current in the linear response regime is input. However, conditions to justify the AP are still ambiguous. We hence consider three tractable models, and discuss possible conditions. The models include the harmonic chain (HC), momentum exchange (ME) model, and momentum flip (MF) model, which respectively show ballistic, anomalous, and diffusive transport. We compare the heat current cumulants predicted by the AP with exact numerical data obtained for these models. The HC does not show the AP, whereas the MF model satisfies it, as expected, since the AP was originally proposed for diffusive systems. Surprisingly, the ME model also shows the AP. The ME model is known to show the anomalous transport similar to that shown in nonlinear systems such as the Fermi-Pasta-Ulam model. Our finding indicates that general nonlinear systems may satisfy the AP. Possible conditions for satisfying the AP are discussed.

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

PubMed Central

Jóźwiak, Bertrand; Orczykowska, Magdalena; Dziubiński, Marek

2015-01-01

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. PMID:26599756

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

PubMed

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.

General Navier–Stokes-like momentum and mass-energy equations

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

Monreal, Jorge, E-mail: jmonreal@mail.usf.edu

2015-03-15

A new system of general Navier–Stokes-like equations is proposed to model electromagnetic flow utilizing analogues of hydrodynamic conservation equations. Such equations are intended to provide a different perspective and, potentially, a better understanding of electromagnetic mass, energy and momentum behaviour. Under such a new framework additional insights into electromagnetism could be gained. To that end, we propose a system of momentum and mass-energy conservation equations coupled through both momentum density and velocity vectors.

What do we gain from simplicity versus complexity in species distribution models?

USGS Publications Warehouse

Merow, Cory; Smith, Matthew J.; Edwards, Thomas C.; Guisan, Antoine; McMahon, Sean M.; Normand, Signe; Thuiller, Wilfried; Wuest, Rafael O.; Zimmermann, Niklaus E.; Elith, Jane

2014-01-01

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

Predicting locations of rare aquatic species’ habitat with a combination of species-specific and assemblage-based models

USGS Publications Warehouse

McKenna, James E.; Carlson, Douglas M.; Payne-Wynne, Molly L.

2013-01-01

Aim: Rare aquatic species are a substantial component of biodiversity, and their conservation is a major objective of many management plans. However, they are difficult to assess, and their optimal habitats are often poorly known. Methods to effectively predict the likely locations of suitable rare aquatic species habitats are needed. We combine two modelling approaches to predict occurrence and general abundance of several rare fish species. Location: Allegheny watershed of western New York State (USA) Methods: Our method used two empirical neural network modelling approaches (species specific and assemblage based) to predict stream-by-stream occurrence and general abundance of rare darters, based on broad-scale habitat conditions. Species-specific models were developed for longhead darter (Percina macrocephala), spotted darter (Etheostoma maculatum) and variegate darter (Etheostoma variatum) in the Allegheny drainage. An additional model predicted the type of rare darter-containing assemblage expected in each stream reach. Predictions from both models were then combined inclusively and exclusively and compared with additional independent data. Results Example rare darter predictions demonstrate the method's effectiveness. Models performed well (R2 ≥ 0.79), identified where suitable darter habitat was most likely to occur, and predictions matched well to those of collection sites. Additional independent data showed that the most conservative (exclusive) model slightly underestimated the distributions of these rare darters or predictions were displaced by one stream reach, suggesting that new darter habitat types were detected in the later collections. Main conclusions Broad-scale habitat variables can be used to effectively identify rare species' habitats. Combining species-specific and assemblage-based models enhances our ability to make use of the sparse data on rare species and to identify habitat units most likely and least likely to support those species. This hybrid approach may assist managers with the prioritization of habitats to be examined or conserved for rare species.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality.

PubMed

Yang, Lei; Qin, Guoyou; Zhao, Naiqing; Wang, Chunfang; Song, Guixiang

2012-10-30

Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton's method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality

PubMed Central

2012-01-01

Background Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Methods Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton’s method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. Results In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. Conclusions GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies. PMID:23110601

Generalized concentration addition mixtures model predicts glucocorticoid receptor activation by environmental full and partial agonist mixtures

EPA Science Inventory

This abstract will be submitted for the consideration of either a poster or platform presentation at the 2018 Annual Carolinas Society of Environmental Toxicology and Chemistry held in Research Triangle Park, NC April 25-27th.

A NEW VARIANCE ESTIMATOR FOR PARAMETERS OF SEMI-PARAMETRIC GENERALIZED ADDITIVE MODELS. (R829213)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Motion of gas in highly rarefied space

NASA Astrophysics Data System (ADS)

Chirkunov, Yu A.

2017-10-01

A model describing a motion of gas in a highly rarefied space received an unlucky number 13 in the list of the basic models of the motion of gas in the three-dimensional space obtained by L.V. Ovsyannikov. For a given initial pressure distribution, a special choice of mass Lagrangian variables leads to the system describing this motion for which the number of independent variables is less by one. Hence, there is a foliation of a highly rarefied gas with respect to pressure. In a strongly rarefied space for each given initial pressure distribution, all gas particles are localized on a two-dimensional surface that moves with time in this space We found some exact solutions of the obtained system that describe the processes taking place inside of the tornado. For this system we found all nontrivial conservation laws of the first order. In addition to the classical conservation laws the system has another conservation law, which generalizes the energy conservation law. With the additional condition we found another one generalized energy conservation law.

The accuracy of ultrashort echo time MRI sequences for medical additive manufacturing.

PubMed

van Eijnatten, Maureen; Rijkhorst, Erik-Jan; Hofman, Mark; Forouzanfar, Tymour; Wolff, Jan

2016-01-01

Additively manufactured bone models, implants and drill guides are becoming increasingly popular amongst maxillofacial surgeons and dentists. To date, such constructs are commonly manufactured using CT technology that induces ionizing radiation. Recently, ultrashort echo time (UTE) MRI sequences have been developed that allow radiation-free imaging of facial bones. The aim of the present study was to assess the feasibility of UTE MRI sequences for medical additive manufacturing (AM). Three morphologically different dry human mandibles were scanned using a CT and MRI scanner. Additionally, optical scans of all three mandibles were made to acquire a "gold standard". All CT and MRI scans were converted into Standard Tessellation Language (STL) models and geometrically compared with the gold standard. To quantify the accuracy of the AM process, the CT, MRI and gold-standard STL models of one of the mandibles were additively manufactured, optically scanned and compared with the original gold-standard STL model. Geometric differences between all three CT-derived STL models and the gold standard were <1.0 mm. All three MRI-derived STL models generally presented deviations <1.5 mm in the symphyseal and mandibular area. The AM process introduced minor deviations of <0.5 mm. This study demonstrates that MRI using UTE sequences is a feasible alternative to CT in generating STL models of the mandible and would therefore be suitable for surgical planning and AM. Further in vivo studies are necessary to assess the usability of UTE MRI sequences in clinical settings.

Binary nanoparticle superlattices of soft-particle systems

DOE PAGES

Travesset, Alex

2015-08-04

The solid-phase diagram of binary systems consisting of particles of diameter σ A=σ and σ B=γσ (γ≤1) interacting with an inverse p = 12 power law is investigated as a paradigm of a soft potential. In addition to the diameter ratio γ that characterizes hard-sphere models, the phase diagram is a function of an additional parameter that controls the relative interaction strength between the different particle types. Phase diagrams are determined from extremes of thermodynamic functions by considering 15 candidate lattices. In general, it is shown that the phase diagram of a soft repulsive potential leads to the morphological diversitymore » observed in experiments with binary nanoparticles, thus providing a general framework to understand their phase diagrams. In addition, particular emphasis is shown to the two most successful crystallization strategies so far: evaporation of solvent from nanoparticles with grafted hydrocarbon ligands and DNA programmable self-assembly.« less

Generalized additive regression models of discharge and mean velocity associated with direct-runoff conditions in Texas: Utility of the U.S. Geological Survey discharge measurement database

USGS Publications Warehouse

Asquith, William H.; Herrmann, George R.; Cleveland, Theodore G.

2013-01-01

A database containing more than 17,700 discharge values and ancillary hydraulic properties was assembled from summaries of discharge measurement records for 424 U.S. Geological Survey streamflow-gauging stations (stream gauges) in Texas. Each discharge exceeds the 90th-percentile daily mean streamflow as determined by period-of-record, stream-gauge-specific, flow-duration curves. Each discharge therefore is assumed to represent discharge measurement made during direct-runoff conditions. The hydraulic properties of each discharge measurement included concomitant cross-sectional flow area, water-surface top width, and reported mean velocity. Systematic and statewide investigation of these data in pursuit of regional models for the estimation of discharge and mean velocity has not been previously attempted. Generalized additive regression modeling is used to develop readily implemented procedures by end-users for estimation of discharge and mean velocity from select predictor variables at ungauged stream locations. The discharge model uses predictor variables of cross-sectional flow area, top width, stream location, mean annual precipitation, and a generalized terrain and climate index (OmegaEM) derived for a previous flood-frequency regionalization study. The mean velocity model uses predictor variables of discharge, top width, stream location, mean annual precipitation, and OmegaEM. The discharge model has an adjusted R-squared value of about 0.95 and a residual standard error (RSE) of about 0.22 base-10 logarithm (cubic meters per second); the mean velocity model has an adjusted R-squared value of about 0.67 and an RSE of about 0.063 fifth root (meters per second). Example applications and computations using both regression models are provided. - See more at: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0000635#sthash.jhGyPxgZ.dpuf

Low dose radiation risks for women surviving the a-bombs in Japan: generalized additive model.

PubMed

Dropkin, Greg

2016-11-24

Analyses of cancer mortality and incidence in Japanese A-bomb survivors have been used to estimate radiation risks, which are generally higher for women. Relative Risk (RR) is usually modelled as a linear function of dose. Extrapolation from data including high doses predicts small risks at low doses. Generalized Additive Models (GAMs) are flexible methods for modelling non-linear behaviour. GAMs are applied to cancer incidence in female low dose subcohorts, using anonymous public data for the 1958 - 1998 Life Span Study, to test for linearity, explore interactions, adjust for the skewed dose distribution, examine significance below 100 mGy, and estimate risks at 10 mGy. For all solid cancer incidence, RR estimated from 0 - 100 mGy and 0 - 20 mGy subcohorts is significantly raised. The response tapers above 150 mGy. At low doses, RR increases with age-at-exposure and decreases with time-since-exposure, the preferred covariate. Using the empirical cumulative distribution of dose improves model fit, and capacity to detect non-linear responses. RR is elevated over wide ranges of covariate values. Results are stable under simulation, or when removing exceptional data cells, or adjusting neutron RBE. Estimates of Excess RR at 10 mGy using the cumulative dose distribution are 10 - 45 times higher than extrapolations from a linear model fitted to the full cohort. Below 100 mGy, quasipoisson models find significant effects for all solid, squamous, uterus, corpus, and thyroid cancers, and for respiratory cancers when age-at-exposure > 35 yrs. Results for the thyroid are compatible with studies of children treated for tinea capitis, and Chernobyl survivors. Results for the uterus are compatible with studies of UK nuclear workers and the Techa River cohort. Non-linear models find large, significant cancer risks for Japanese women exposed to low dose radiation from the atomic bombings. The risks should be reflected in protection standards.

Impact of urban canopy models and external parameters on the modelled urban energy balance in a tropical city

NASA Astrophysics Data System (ADS)

Demuzere, Matthias; Harshan, Suraj; Järvi, Leena; Roth, Matthias; Betham Grimmond, Christine Susan; Masson, Valéry; Oleson, Keith; Velasco Saldana, Hector Erik; Wouters, Hendrik

2017-04-01

This paper provides the first comparative evaluation of four urban land surface models for a tropical residential neighbourhood in Singapore. The simulations are performed offline, for an 11-month period, using the bulk scheme TERRA_URB and three models of intermediate complexity (CLM, SURFEX and SUEWS). In addition, information from three different parameter lists are added to quantify the impact (interaction) of (between) external parameter settings and model formulations on the modelled urban energy balance components. Overall, the models' performance using the reference parameters aligns well with previous findings for mid- and high-latitude sites against (for) which the models are generally optimised (evaluated). The various combinations of models and different parameter values suggest that error statistics tend to be more dominated by the choice of the latter than the choice of model. Stratifying the observation period into dry / wet periods and hours since selected precipitation events reveals that the models' skill generally deteriorates during dry periods while e.g. CLM/SURFEX has a positive bias in the latent heat flux directly after a precipitation event. It is shown that the latter is due to simple representation of water intercepted on the impervious surfaces. In addition, the positive bias in modelled outgoing longwave radiation is attributed to neglecting the interactions between water vapor and radiation between the surface and the tower sensor. These findings suggest that future developments in urban climate research should continue the integration of more physically-based processes in urban canopy models, ensure the consistency between the observed and modelled atmospheric properties and focus on the correct representation of urban morphology and thermal and radiative characteristics.

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Motivation and Self-Regulation in Addiction: A Call for Convergence

PubMed Central

Köpetz, Cătălina E.; Lejuez, Carl W.; Wiers, Reinout W.; Kruglanski, Arie W.

2015-01-01

Addiction models have frequently invoked motivational mechanisms to explain the initiation and maintenance of addictive behaviors. However, in doing so, these models have emphasized the unique characteristics of addictive behaviors and overlooked the commonalities that they share with motivated behaviors in general. As a consequence, addiction research has failed to connect with and take advantage of promising and highly relevant advances in motivation and self-regulation research. The present article is a call for a convergence of the previous approaches to addictive behavior and the new advances in basic motivation and self-regulation. The authors emphasize the commonalities that addictive behaviors may share with motivated behavior in general. In addition, it is suggested that the same psychological principles underlying motivated action in general may apply to understand challenging aspects of the etiology and maintenance of addictive behaviors. PMID:26069472

Tomography and generative training with quantum Boltzmann machines

NASA Astrophysics Data System (ADS)

Kieferová, Mária; Wiebe, Nathan

2017-12-01

The promise of quantum neural nets, which utilize quantum effects to model complex data sets, has made their development an aspirational goal for quantum machine learning and quantum computing in general. Here we provide methods of training quantum Boltzmann machines. Our work generalizes existing methods and provides additional approaches for training quantum neural networks that compare favorably to existing methods. We further demonstrate that quantum Boltzmann machines enable a form of partial quantum state tomography that further provides a generative model for the input quantum state. Classical Boltzmann machines are incapable of this. This verifies the long-conjectured connection between tomography and quantum machine learning. Finally, we prove that classical computers cannot simulate our training process in general unless BQP=BPP , provide lower bounds on the complexity of the training procedures and numerically investigate training for small nonstoquastic Hamiltonians.

21 CFR 172.5 - General provisions for direct food additives.

Code of Federal Regulations, 2010 CFR

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...

21 CFR 172.5 - General provisions for direct food additives.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 3 2013-04-01 2013-04-01 false General provisions for direct food additives. 172... (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...

21 CFR 172.5 - General provisions for direct food additives.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 3 2011-04-01 2011-04-01 false General provisions for direct food additives. 172... (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...

21 CFR 172.5 - General provisions for direct food additives.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 3 2014-04-01 2014-04-01 false General provisions for direct food additives. 172... (CONTINUED) FOOD ADDITIVES PERMITTED FOR DIRECT ADDITION TO FOOD FOR HUMAN CONSUMPTION General Provisions § 172.5 General provisions for direct food additives. (a) Regulations prescribing conditions under which...

21 CFR 172.5 - General provisions for direct food additives.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 3 2012-04-01 2012-04-01 false General provisions for direct food additives. 172... (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...

[A Patient´s Personality: A Frequently Ignored but Important Component in General Medical Practice].

PubMed

Hengartner, Michael P

2018-06-01

A Patient´s Personality: A Frequently Ignored but Important Component in General Medical Practice Abstract. In general medical practice, a patient's personality is hardly considered and assessed. In this mini-review the author summarises how a comprehensive personality assessment may provide valuable patient information. Prospective effects of personality traits on general lifestyle as well as mental and physical health are presented. In addition, original research is introduced that shows meaningful associations between personality traits, clinical disease markers, and all-cause mortality. These findings are discussed with respect to selected etiological models. The studies illustrate that a personality assessment could be a useful aid for diagnosis, prognosis, and treatment planning.

A 1D-2D Shallow Water Equations solver for discontinuous porosity field based on a Generalized Riemann Problem

NASA Astrophysics Data System (ADS)

Ferrari, Alessia; Vacondio, Renato; Dazzi, Susanna; Mignosa, Paolo

2017-09-01

A novel augmented Riemann Solver capable of handling porosity discontinuities in 1D and 2D Shallow Water Equation (SWE) models is presented. With the aim of accurately approximating the porosity source term, a Generalized Riemann Problem is derived by adding an additional fictitious equation to the SWEs system and imposing mass and momentum conservation across the porosity discontinuity. The modified Shallow Water Equations are theoretically investigated, and the implementation of an augmented Roe Solver in a 1D Godunov-type finite volume scheme is presented. Robust treatment of transonic flows is ensured by introducing an entropy fix based on the wave pattern of the Generalized Riemann Problem. An Exact Riemann Solver is also derived in order to validate the numerical model. As an extension of the 1D scheme, an analogous 2D numerical model is also derived and validated through test cases with radial symmetry. The capability of the 1D and 2D numerical models to capture different wave patterns is assessed against several Riemann Problems with different wave patterns.

Dust Emissions, Transport, and Deposition Simulated with the NASA Finite-Volume General Circulation Model

NASA Technical Reports Server (NTRS)

Colarco, Peter; daSilva, Arlindo; Ginoux, Paul; Chin, Mian; Lin, S.-J.

2003-01-01

Mineral dust aerosols have radiative impacts on Earth's atmosphere, have been implicated in local and regional air quality issues, and have been identified as vectors for transporting disease pathogens and bringing mineral nutrients to terrestrial and oceanic ecosystems. We present for the first time dust simulations using online transport and meteorological analysis in the NASA Finite-Volume General Circulation Model (FVGCM). Our dust formulation follows the formulation in the offline Georgia Institute of Technology-Goddard Global Ozone Chemistry Aerosol Radiation and Transport Model (GOCART) using a topographical source for dust emissions. We compare results of the FVGCM simulations with GOCART, as well as with in situ and remotely sensed observations. Additionally, we estimate budgets of dust emission and transport into various regions.

Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits.

PubMed

Aliloo, Hassan; Pryce, Jennie E; González-Recio, Oscar; Cocks, Benjamin G; Hayes, Ben J

2016-02-01

Dominance effects may contribute to genetic variation of complex traits in dairy cattle, especially for traits closely related to fitness such as fertility. However, traditional genetic evaluations generally ignore dominance effects and consider additive genetic effects only. Availability of dense single nucleotide polymorphisms (SNPs) panels provides the opportunity to investigate the role of dominance in quantitative variation of complex traits at both the SNP and animal levels. Including dominance effects in the genomic evaluation of animals could also help to increase the accuracy of prediction of future phenotypes. In this study, we estimated additive and dominance variance components for fertility and milk production traits of genotyped Holstein and Jersey cows in Australia. The predictive abilities of a model that accounts for additive effects only (additive), and a model that accounts for both additive and dominance effects (additive + dominance) were compared in a fivefold cross-validation. Estimates of the proportion of dominance variation relative to phenotypic variation that is captured by SNPs, for production traits, were up to 3.8 and 7.1 % in Holstein and Jersey cows, respectively, whereas, for fertility, they were equal to 1.2 % in Holstein and very close to zero in Jersey cows. We found that including dominance in the model was not consistently advantageous. Based on maximum likelihood ratio tests, the additive + dominance model fitted the data better than the additive model, for milk, fat and protein yields in both breeds. However, regarding the prediction of phenotypes assessed with fivefold cross-validation, including dominance effects in the model improved accuracy only for fat yield in Holstein cows. Regression coefficients of phenotypes on genetic values and mean squared errors of predictions showed that the predictive ability of the additive + dominance model was superior to that of the additive model for some of the traits. In both breeds, dominance effects were significant (P < 0.01) for all milk production traits but not for fertility. Accuracy of prediction of phenotypes was slightly increased by including dominance effects in the genomic evaluation model. Thus, it can help to better identify highly performing individuals and be useful for culling decisions.

Activities, self-referent memory beliefs, and cognitive performance: evidence for direct and mediated relations.

PubMed

Jopp, Daniela; Hertzog, Christopher

2007-12-01

In this study, the authors investigated the role of activities and self-referent memory beliefs for cognitive performance in a life-span sample. A factor analysis identified 8 activity factors, including Developmental Activities, Experiential Activities, Social Activities, Physical Activities, Technology Use, Watching Television, Games, and Crafts. A second-order general activity factor was significantly related to a general factor of cognitive function as defined by ability tests. Structural regression models suggested that prediction of cognition by activity level was partially mediated by memory beliefs, controlling for age, education, health, and depressive affect. Models adding paths from general and specific activities to aspects of crystallized intelligence suggested additional unique predictive effects for some activities. In alternative models, nonsignificant effects of beliefs on activities were detected when cognition predicted both variables, consistent with the hypothesis that beliefs derive from monitoring cognition and have no influence on activity patterns. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Statistical thermodynamics foundation for photovoltaic and photothermal conversion. II. Application to photovoltaic conversion

NASA Astrophysics Data System (ADS)

Badescu, Viorel; Landsberg, Peter T.

1995-08-01

The general theory developed in part I was applied to build up two models of photovoltaic conversion. To this end two different systems were analyzed. The first system consists of the whole absorber (converter), for which the balance equations for energy and entropy are written and then used to derive an upper bound for solar energy conversion. The second system covers a part of the absorber (converter), namely the valence and conduction electronic bands. The balance of energy is used in this case to derive, under additional assumptions, another upper limit for the conversion efficiency. This second system deals with the real location where the power is generated. Both models take into consideration the radiation polarization and reflection, and the effects of concentration. The second model yields a more accurate upper bound for the conversion efficiency. A generalized solar cell equation is derived. It is proved that other previous theories are particular cases of the present more general formalism.

Adaptation, Growth, and Resilience in Biological Distribution Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. We show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as plant and animal vasculature. In addition, we show how the incorporation of spatially collective fluctuating sources yields a minimal model of realistic reticulation in distribution networks and thus resilience against damage.

FURTHER ANALYSIS OF SUBTYPES OF AUTOMATICALLY REINFORCED SIB: A REPLICATION AND QUANTITATIVE ANALYSIS OF PUBLISHED DATASETS

PubMed Central

Hagopian, Louis P.; Rooker, Griffin W.; Zarcone, Jennifer R.; Bonner, Andrew C.; Arevalo, Alexander R.

2017-01-01

Hagopian, Rooker, and Zarcone (2015) evaluated a model for subtyping automatically reinforced self-injurious behavior (SIB) based on its sensitivity to changes in functional analysis conditions and the presence of self-restraint. The current study tested the generality of the model by applying it to all datasets of automatically reinforced SIB published from 1982 to 2015. We identified 49 datasets that included sufficient data to permit subtyping. Similar to the original study, Subtype-1 SIB was generally amenable to treatment using reinforcement alone, whereas Subtype-2 SIB was not. Conclusions could not be drawn about Subtype-3 SIB due to the small number of datasets. Nevertheless, the findings support the generality of the model and suggest that sensitivity of SIB to disruption by alternative reinforcement is an important dimension of automatically reinforced SIB. Findings also suggest that automatically reinforced SIB should no longer be considered a single category and that additional research is needed to better understand and treat Subtype-2 SIB. PMID:28032344

Global adaptation patterns of Australian and CIMMYT spring bread wheat.

PubMed

Mathews, Ky L; Chapman, Scott C; Trethowan, Richard; Pfeiffer, Wolfgang; van Ginkel, Maarten; Crossa, Jose; Payne, Thomas; Delacy, Ian; Fox, Paul N; Cooper, Mark

2007-10-01

The International Adaptation Trial (IAT) is a special purpose nursery designed to investigate the genotype-by-environment interactions and worldwide adaptation for grain yield of Australian and CIMMYT spring bread wheat (Triticum aestivum L.) and durum wheat (T. turgidum L. var. durum). The IAT contains lines representing Australian and CIMMYT wheat breeding programs and was distributed to 91 countries between 2000 and 2004. Yield data of 41 reference lines from 106 trials were analysed. A multiplicative mixed model accounted for trial variance heterogeneity and inter-trial correlations characteristic of multi-environment trials. A factor analytic model explained 48% of the genetic variance for the reference lines. Pedigree information was then incorporated to partition the genetic line effects into additive and non-additive components. This model explained 67 and 56% of the additive by environment and non-additive by environment genetic variances, respectively. Australian and CIMMYT germplasm showed good adaptation to their respective target production environments. In general, Australian lines performed well in south and west Australia, South America, southern Africa, Iran and high latitude European and Canadian locations. CIMMYT lines performed well at CIMMYT's key yield testing location in Mexico (CIANO), north-eastern Australia, the Indo-Gangetic plains, West Asia North Africa and locations in Europe and Canada. Maturity explained some of the global adaptation patterns. In general, southern Australian germplasm were later maturing than CIMMYT material. While CIANO continues to provide adapted lines to northern Australia, selecting for yield among later maturing CIMMYT material in CIANO may identify lines adapted to southern and western Australian environments.

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

Dawson, S.; Lewis, I. M.

One of the simplest extensions of the Standard Model (SM) is the addition of a scalar gauge singlet, S . If S is not forbidden by a symmetry from mixing with the Standard Model Higgs boson, the mixing will generate non-SM rates for Higgs production and decays. Generally, there could also be unknown high energy physics that generates additional effective low energy interactions. We show that interference effects between the scalar resonance of the singlet model and the effective field theory (EFT) operators can have significant effects in the Higgs sector. Here, we examine a non- Z 2 symmetricmore » scalar singlet model and demonstrate that a fit to the 125 GeV Higgs boson couplings and to limits on high mass resonances, S , exhibit an interesting structure and possible large cancellations of effects between the resonance contribution and the new EFT interactions, that invalidate conclusions based on the renormalizable singlet model alone.« less

A new class of enhanced kinetic sampling methods for building Markov state models

NASA Astrophysics Data System (ADS)

Bhoutekar, Arti; Ghosh, Susmita; Bhattacharya, Swati; Chatterjee, Abhijit

2017-10-01

Markov state models (MSMs) and other related kinetic network models are frequently used to study the long-timescale dynamical behavior of biomolecular and materials systems. MSMs are often constructed bottom-up using brute-force molecular dynamics (MD) simulations when the model contains a large number of states and kinetic pathways that are not known a priori. However, the resulting network generally encompasses only parts of the configurational space, and regardless of any additional MD performed, several states and pathways will still remain missing. This implies that the duration for which the MSM can faithfully capture the true dynamics, which we term as the validity time for the MSM, is always finite and unfortunately much shorter than the MD time invested to construct the model. A general framework that relates the kinetic uncertainty in the model to the validity time, missing states and pathways, network topology, and statistical sampling is presented. Performing additional calculations for frequently-sampled states/pathways may not alter the MSM validity time. A new class of enhanced kinetic sampling techniques is introduced that aims at targeting rare states/pathways that contribute most to the uncertainty so that the validity time is boosted in an effective manner. Examples including straightforward 1D energy landscapes, lattice models, and biomolecular systems are provided to illustrate the application of the method. Developments presented here will be of interest to the kinetic Monte Carlo community as well.

Mixed Model Methods for Genomic Prediction and Variance Component Estimation of Additive and Dominance Effects Using SNP Markers

PubMed Central

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005–0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level. PMID:24498162

Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

PubMed

Da, Yang; Wang, Chunkao; Wang, Shengwen; Hu, Guo

2014-01-01

We established a genomic model of quantitative trait with genomic additive and dominance relationships that parallels the traditional quantitative genetics model, which partitions a genotypic value as breeding value plus dominance deviation and calculates additive and dominance relationships using pedigree information. Based on this genomic model, two sets of computationally complementary but mathematically identical mixed model methods were developed for genomic best linear unbiased prediction (GBLUP) and genomic restricted maximum likelihood estimation (GREML) of additive and dominance effects using SNP markers. These two sets are referred to as the CE and QM sets, where the CE set was designed for large numbers of markers and the QM set was designed for large numbers of individuals. GBLUP and associated accuracy formulations for individuals in training and validation data sets were derived for breeding values, dominance deviations and genotypic values. Simulation study showed that GREML and GBLUP generally were able to capture small additive and dominance effects that each accounted for 0.00005-0.0003 of the phenotypic variance and GREML was able to differentiate true additive and dominance heritability levels. GBLUP of the total genetic value as the summation of additive and dominance effects had higher prediction accuracy than either additive or dominance GBLUP, causal variants had the highest accuracy of GREML and GBLUP, and predicted accuracies were in agreement with observed accuracies. Genomic additive and dominance relationship matrices using SNP markers were consistent with theoretical expectations. The GREML and GBLUP methods can be an effective tool for assessing the type and magnitude of genetic effects affecting a phenotype and for predicting the total genetic value at the whole genome level.

Z/sub n/ Baxter model: symmetries and the Belavin parametrization

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

Richey, M.P.; Tracy, C.A.

1986-02-01

The Z/sub n/ Baxter model is an exactly solvable lattice model in the special case of the Belavin parametrization. For this parametrization the authors calculate the partition function in an antiferromagnetic region and the order parameter in a ferromagnetic region. They find that the order parameter is expressible in terms of a modular function of level n which for n=2 is the Onsager-Yang-Baxter result. In addition they determine the symmetry group of the finite lattice partition function for the general Z/sub n/ Baxter model.

Emergent universe model with dissipative effects

NASA Astrophysics Data System (ADS)

Debnath, P. S.; Paul, B. C.

2017-12-01

Emergent universe model is presented in general theory of relativity with isotropic fluid in addition to viscosity. We obtain cosmological solutions that permit emergent universe scenario in the presence of bulk viscosity that are described by either Eckart theory or Truncated Israel Stewart (TIS) theory. The stability of the solutions are also studied. In this case, the emergent universe (EU) model is analyzed with observational data. In the presence of viscosity, one obtains emergent universe scenario, which however is not permitted in the absence of viscosity. The EU model is compatible with cosmological observations.

Optimal exploitation strategies for an animal population in a Markovian environment: A theory and an example

USGS Publications Warehouse

Anderson, D.R.

1975-01-01

Optimal exploitation strategies were studied for an animal population in a Markovian (stochastic, serially correlated) environment. This is a general case and encompasses a number of important special cases as simplifications. Extensive empirical data on the Mallard (Anas platyrhynchos) were used as an example of general theory. The number of small ponds on the central breeding grounds was used as an index to the state of the environment. A general mathematical model was formulated to provide a synthesis of the existing literature, estimates of parameters developed from an analysis of data, and hypotheses regarding the specific effect of exploitation on total survival. The literature and analysis of data were inconclusive concerning the effect of exploitation on survival. Therefore, two hypotheses were explored: (1) exploitation mortality represents a largely additive form of mortality, and (2) exploitation mortality is compensatory with other forms of mortality, at least to some threshold level. Models incorporating these two hypotheses were formulated as stochastic dynamic programming models and optimal exploitation strategies were derived numerically on a digital computer. Optimal exploitation strategies were found to exist under the rather general conditions. Direct feedback control was an integral component in the optimal decision-making process. Optimal exploitation was found to be substantially different depending upon the hypothesis regarding the effect of exploitation on the population. If we assume that exploitation is largely an additive force of mortality in Mallards, then optimal exploitation decisions are a convex function of the size of the breeding population and a linear or slight concave function of the environmental conditions. Under the hypothesis of compensatory mortality forces, optimal exploitation decisions are approximately linearly related to the size of the Mallard breeding population. Dynamic programming is suggested as a very general formulation for realistic solutions to the general optimal exploitation problem. The concepts of state vectors and stage transformations are completely general. Populations can be modeled stochastically and the objective function can include extra-biological factors. The optimal level of exploitation in year t must be based on the observed size of the population and the state of the environment in year t unless the dynamics of the population, the state of the environment, and the result of the exploitation decisions are completely deterministic. Exploitation based on an average harvest, or harvest rate, or designed to maintain a constant breeding population size is inefficient.

Heliophysics Data and Modeling Research Using VSPO

NASA Technical Reports Server (NTRS)

Roberts, D. Aaron; Hesse, Michael; Cornwell, Carl

2007-01-01

The primary advantage of Virtual Observatories in scientific research is efficiency: rapid searches for and access to data in convenient forms makes it possible to explore scientific questions without spending days or weeks on ancilary tasks. The Virtual Space Physics Observatory provides a general portal to Heliophysics data for this task. Here we will illustrate the advantages of the VO approach by examining specific geomagnetically active times and tracing the activity through the Sun-Earth system. In addition to previous and additional data sources, we will demonstrate an extension of the capabilities to allow searching for model run results from the range of CCMC models. This approach allows the user to quickly compare models and observations at a qualitative level; considerably more work will be needed to develop more seamless connections to data streams and the equivalent numerical output from simulations.

Detection of greenhouse-gas-induced climatic change. Progress report, July 1, 1994--July 31, 1995

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

Jones, P.D.; Wigley, T.M.L.

1995-07-21

The objective of this research is to assembly and analyze instrumental climate data and to develop and apply climate models as a basis for detecting greenhouse-gas-induced climatic change, and validation of General Circulation Models. In addition to changes due to variations in anthropogenic forcing, including greenhouse gas and aerosol concentration changes, the global climate system exhibits a high degree of internally-generated and externally-forced natural variability. To detect the anthropogenic effect, its signal must be isolated from the ``noise`` of this natural climatic variability. A high quality, spatially extensive data base is required to define the noise and its spatial characteristics.more » To facilitate this, available land and marine data bases will be updated and expanded. The data will be analyzed to determine the potential effects on climate of greenhouse gas and aerosol concentration changes and other factors. Analyses will be guided by a variety of models, from simple energy balance climate models to coupled atmosphere ocean General Circulation Models. These analyses are oriented towards obtaining early evidence of anthropogenic climatic change that would lead either to confirmation, rejection or modification of model projections, and towards the statistical validation of General Circulation Model control runs and perturbation experiments.« less

Small-scale multi-axial hybrid simulation of a shear-critical reinforced concrete frame

NASA Astrophysics Data System (ADS)

Sadeghian, Vahid; Kwon, Oh-Sung; Vecchio, Frank

2017-10-01

This study presents a numerical multi-scale simulation framework which is extended to accommodate hybrid simulation (numerical-experimental integration). The framework is enhanced with a standardized data exchange format and connected to a generalized controller interface program which facilitates communication with various types of laboratory equipment and testing configurations. A small-scale experimental program was conducted using a six degree-of-freedom hydraulic testing equipment to verify the proposed framework and provide additional data for small-scale testing of shearcritical reinforced concrete structures. The specimens were tested in a multi-axial hybrid simulation manner under a reversed cyclic loading condition simulating earthquake forces. The physical models were 1/3.23-scale representations of a beam and two columns. A mixed-type modelling technique was employed to analyze the remainder of the structures. The hybrid simulation results were compared against those obtained from a large-scale test and finite element analyses. The study found that if precautions are taken in preparing model materials and if the shear-related mechanisms are accurately considered in the numerical model, small-scale hybrid simulations can adequately simulate the behaviour of shear-critical structures. Although the findings of the study are promising, to draw general conclusions additional test data are required.

Quantile regression via vector generalized additive models.

PubMed

Yee, Thomas W

2004-07-30

One of the most popular methods for quantile regression is the LMS method of Cole and Green. The method naturally falls within a penalized likelihood framework, and consequently allows for considerable flexible because all three parameters may be modelled by cubic smoothing splines. The model is also very understandable: for a given value of the covariate, the LMS method applies a Box-Cox transformation to the response in order to transform it to standard normality; to obtain the quantiles, an inverse Box-Cox transformation is applied to the quantiles of the standard normal distribution. The purposes of this article are three-fold. Firstly, LMS quantile regression is presented within the framework of the class of vector generalized additive models. This confers a number of advantages such as a unifying theory and estimation process. Secondly, a new LMS method based on the Yeo-Johnson transformation is proposed, which has the advantage that the response is not restricted to be positive. Lastly, this paper describes a software implementation of three LMS quantile regression methods in the S language. This includes the LMS-Yeo-Johnson method, which is estimated efficiently by a new numerical integration scheme. The LMS-Yeo-Johnson method is illustrated by way of a large cross-sectional data set from a New Zealand working population. Copyright 2004 John Wiley & Sons, Ltd.

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

PubMed

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

2015-03-01

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

Evaluating models of remember-know judgments: complexity, mimicry, and discriminability.

PubMed

Cohen, Andrew L; Rotello, Caren M; Macmillan, Neil A

2008-10-01

Remember-know judgments provide additional information in recognition memory tests, but the nature of this information and the attendant decision process are in dispute. Competing models have proposed that remember judgments reflect a sum of familiarity and recollective information (the one-dimensional model), are based on a difference between these strengths (STREAK), or are purely recollective (the dual-process model). A choice among these accounts is sometimes made by comparing the precision of their fits to data, but this strategy may be muddied by differences in model complexity: Some models that appear to provide good fits may simply be better able to mimic the data produced by other models. To evaluate this possibility, we simulated data with each of the models in each of three popular remember-know paradigms, then fit those data to each of the models. We found that the one-dimensional model is generally less complex than the others, but despite this handicap, it dominates the others as the best-fitting model. For both reasons, the one-dimensional model should be preferred. In addition, we found that some empirical paradigms are ill-suited for distinguishing among models. For example, data collected by soliciting remember/know/new judgments--that is, the trinary task--provide a particularly weak ground for distinguishing models. Additional tables and figures may be downloaded from the Psychonomic Society's Archive of Norms, Stimuli, and Data, at www.psychonomic.org/archive.

Time Scale Effects in Acute Association between Air-Pollution and Mortality

EPA Science Inventory

We used wavelet analysis and generalized additive models (GAM) to study timescale effects in the acute association between mortality and air-pollution. Daily averages of measured NO₂ concentrations in the metropolitan Paris area are used as indicators of human exposure...

GENERALIZED ADDITIVE DISTRIBUTED LAG MODELS: QUANTIFYING MORTALITY DISPLACEMENT. (R827353C004,R827353C005)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Noise limitations in optical linear algebra processors.

PubMed

Batsell, S G; Jong, T L; Walkup, J F; Krile, T F

1990-05-10

A general statistical noise model is presented for optical linear algebra processors. A statistical analysis which includes device noise, the multiplication process, and the addition operation is undertaken. We focus on those processes which are architecturally independent. Finally, experimental results which verify the analytical predictions are also presented.

Structural Equation Modeling: A Framework for Ocular and Other Medical Sciences Research

PubMed Central

Christ, Sharon L.; Lee, David J.; Lam, Byron L.; Diane, Zheng D.

2017-01-01

Structural equation modeling (SEM) is a modeling framework that encompasses many types of statistical models and can accommodate a variety of estimation and testing methods. SEM has been used primarily in social sciences but is increasingly used in epidemiology, public health, and the medical sciences. SEM provides many advantages for the analysis of survey and clinical data, including the ability to model latent constructs that may not be directly observable. Another major feature is simultaneous estimation of parameters in systems of equations that may include mediated relationships, correlated dependent variables, and in some instances feedback relationships. SEM allows for the specification of theoretically holistic models because multiple and varied relationships may be estimated together in the same model. SEM has recently expanded by adding generalized linear modeling capabilities that include the simultaneous estimation of parameters of different functional form for outcomes with different distributions in the same model. Therefore, mortality modeling and other relevant health outcomes may be evaluated. Random effects estimation using latent variables has been advanced in the SEM literature and software. In addition, SEM software has increased estimation options. Therefore, modern SEM is quite general and includes model types frequently used by health researchers, including generalized linear modeling, mixed effects linear modeling, and population average modeling. This article does not present any new information. It is meant as an introduction to SEM and its uses in ocular and other health research. PMID:24467557

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

Blume-Kohout, Robin J; Scholten, Travis L.

Quantum state tomography on a d-dimensional system demands resources that grow rapidly with d. They may be reduced by using model selection to tailor the number of parameters in the model (i.e., the size of the density matrix). Most model selection methods typically rely on a test statistic and a null theory that describes its behavior when two models are equally good. Here, we consider the loglikelihood ratio. Because of the positivity constraint ρ ≥ 0, quantum state space does not generally satisfy local asymptotic normality (LAN), meaning the classical null theory for the loglikelihood ratio (the Wilks theorem) shouldmore » not be used. Thus, understanding and quantifying how positivity affects the null behavior of this test statistic is necessary for its use in model selection for state tomography. We define a new generalization of LAN, metric-projected LAN, show that quantum state space satisfies it, and derive a replacement for the Wilks theorem. In addition to enabling reliable model selection, our results shed more light on the qualitative effects of the positivity constraint on state tomography.« less

A knowledge base architecture for distributed knowledge agents

NASA Technical Reports Server (NTRS)

Riedesel, Joel; Walls, Bryan

1990-01-01

A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

Ancestral haplotype-based association mapping with generalized linear mixed models accounting for stratification.

PubMed

Zhang, Z; Guillaume, F; Sartelet, A; Charlier, C; Georges, M; Farnir, F; Druet, T

2012-10-01

In many situations, genome-wide association studies are performed in populations presenting stratification. Mixed models including a kinship matrix accounting for genetic relatedness among individuals have been shown to correct for population and/or family structure. Here we extend this methodology to generalized linear mixed models which properly model data under various distributions. In addition we perform association with ancestral haplotypes inferred using a hidden Markov model. The method was shown to properly account for stratification under various simulated scenari presenting population and/or family structure. Use of ancestral haplotypes resulted in higher power than SNPs on simulated datasets. Application to real data demonstrates the usefulness of the developed model. Full analysis of a dataset with 4600 individuals and 500 000 SNPs was performed in 2 h 36 min and required 2.28 Gb of RAM. The software GLASCOW can be freely downloaded from www.giga.ulg.ac.be/jcms/prod_381171/software. francois.guillaume@jouy.inra.fr Supplementary data are available at Bioinformatics online.

Cable equation for general geometry

NASA Astrophysics Data System (ADS)

López-Sánchez, Erick J.; Romero, Juan M.

2017-02-01

The cable equation describes the voltage in a straight cylindrical cable, and this model has been employed to model electrical potential in dendrites and axons. However, sometimes this equation might give incorrect predictions for some realistic geometries, in particular when the radius of the cable changes significantly. Cables with a nonconstant radius are important for some phenomena, for example, discrete swellings along the axons appear in neurodegenerative diseases such as Alzheimers, Parkinsons, human immunodeficiency virus associated dementia, and multiple sclerosis. In this paper, using the Frenet-Serret frame, we propose a generalized cable equation for a general cable geometry. This generalized equation depends on geometric quantities such as the curvature and torsion of the cable. We show that when the cable has a constant circular cross section, the first fundamental form of the cable can be simplified and the generalized cable equation depends on neither the curvature nor the torsion of the cable. Additionally, we find an exact solution for an ideal cable which has a particular variable circular cross section and zero curvature. For this case we show that when the cross section of the cable increases the voltage decreases. Inspired by this ideal case, we rewrite the generalized cable equation as a diffusion equation with a source term generated by the cable geometry. This source term depends on the cable cross-sectional area and its derivates. In addition, we study different cables with swelling and provide their numerical solutions. The numerical solutions show that when the cross section of the cable has abrupt changes, its voltage is smaller than the voltage in the cylindrical cable. Furthermore, these numerical solutions show that the voltage can be affected by geometrical inhomogeneities on the cable.

Metadynamics for training neural network model chemistries: A competitive assessment

NASA Astrophysics Data System (ADS)

Herr, John E.; Yao, Kun; McIntyre, Ryker; Toth, David W.; Parkhill, John

2018-06-01

Neural network model chemistries (NNMCs) promise to facilitate the accurate exploration of chemical space and simulation of large reactive systems. One important path to improving these models is to add layers of physical detail, especially long-range forces. At short range, however, these models are data driven and data limited. Little is systematically known about how data should be sampled, and "test data" chosen randomly from some sampling techniques can provide poor information about generality. If the sampling method is narrow, "test error" can appear encouragingly tiny while the model fails catastrophically elsewhere. In this manuscript, we competitively evaluate two common sampling methods: molecular dynamics (MD), normal-mode sampling, and one uncommon alternative, Metadynamics (MetaMD), for preparing training geometries. We show that MD is an inefficient sampling method in the sense that additional samples do not improve generality. We also show that MetaMD is easily implemented in any NNMC software package with cost that scales linearly with the number of atoms in a sample molecule. MetaMD is a black-box way to ensure samples always reach out to new regions of chemical space, while remaining relevant to chemistry near kbT. It is a cheap tool to address the issue of generalization.

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

NASA Astrophysics Data System (ADS)

Mikaelian, Karnig O.

2009-02-01

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 such as air/SF6/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 toward 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.

Forest height estimation from mountain forest areas using general model-based decomposition for polarimetric interferometric synthetic aperture radar images

NASA Astrophysics Data System (ADS)

Minh, Nghia Pham; Zou, Bin; Cai, Hongjun; Wang, Chengyi

2014-01-01

The estimation of forest parameters over mountain forest areas using polarimetric interferometric synthetic aperture radar (PolInSAR) images is one of the greatest interests in remote sensing applications. For mountain forest areas, scattering mechanisms are strongly affected by the ground topography variations. Most of the previous studies in modeling microwave backscattering signatures of forest area have been carried out over relatively flat areas. Therefore, a new algorithm for the forest height estimation from mountain forest areas using the general model-based decomposition (GMBD) for PolInSAR image is proposed. This algorithm enables the retrieval of not only the forest parameters, but also the magnitude associated with each mechanism. In addition, general double- and single-bounce scattering models are proposed to fit for the cross-polarization and off-diagonal term by separating their independent orientation angle, which remains unachieved in the previous model-based decompositions. The efficiency of the proposed approach is demonstrated with simulated data from PolSARProSim software and ALOS-PALSAR spaceborne PolInSAR datasets over the Kalimantan areas, Indonesia. Experimental results indicate that forest height could be effectively estimated by GMBD.

Second virial coefficient of a generalized Lennard-Jones potential.

PubMed

González-Calderón, Alfredo; Rocha-Ichante, Adrián

2015-01-21

We present an exact analytical solution for the second virial coefficient of a generalized Lennard-Jones type of pair potential model. The potential can be reduced to the Lennard-Jones, hard-sphere, and sticky hard-sphere models by tuning the potential parameters corresponding to the width and depth of the well. Thus, the second virial solution can also regain the aforementioned cases. Moreover, the obtained expression strongly resembles the one corresponding to the Kihara potential. In fact, the Fk functions are the same. Furthermore, for these functions, the complete expansions at low and high temperature are given. Additionally, we propose an alternative stickiness parameter based on the obtained second virial coefficient.

Radiation bounce from the Lee-Wick construction?

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

Karouby, Johanna; Brandenberger, Robert

2010-09-15

It was recently realized that matter modeled by the scalar field sector of the Lee-Wick standard model yields, in the context of a homogeneous and isotropic cosmological background, a bouncing cosmology. However, bouncing cosmologies induced by pressureless matter are in general unstable to the addition of relativistic matter (i.e. radiation). Here we study the possibility of obtaining a bouncing cosmology if we add not only radiation, but also its Lee-Wick partner, to the matter sector. We find that, in general, no bounce occurs. The only way to obtain a bounce is to choose initial conditions with very special phases ofmore » the radiation field and its Lee-Wick partner.« less

Stochastic resonance and noise delayed extinction in a model of two competing species

NASA Astrophysics Data System (ADS)

Valenti, D.; Fiasconaro, A.; Spagnolo, B.

2004-01-01

We study the role of the noise in the dynamics of two competing species. We consider generalized Lotka-Volterra equations in the presence of a multiplicative noise, which models the interaction between the species and the environment. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence of a periodic driving term, which accounts for the environment temperature variation. We find noise-induced periodic oscillations of the species concentrations and stochastic resonance phenomenon. We find also a nonmonotonic behavior of the mean extinction time of one of the two competing species as a function of the additive noise intensity.

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

EPA Pesticide Factsheets

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

Independent Verification of Mars-GRAM 2010 with Mars Climate Sounder Data

NASA Technical Reports Server (NTRS)

Justh, Hilary L.; Burns, Kerry L.

2014-01-01

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission and engineering applications. Applications of Mars-GRAM include systems design, performance analysis, and operations planning for aerobraking, entry, descent and landing, and aerocapture. Atmospheric influences on landing site selection and long-term mission conceptualization and development can also be addressed utilizing Mars-GRAM. Mars-GRAM's perturbation modeling capability is commonly used, in a Monte Carlo mode, to perform high-fidelity engineering end-to-end simulations for entry, descent, and landing. Mars-GRAM is an evolving software package resulting in improved accuracy and additional features. Mars-GRAM 2005 has been validated against Radio Science data, and both nadir and limb data from the Thermal Emission Spectrometer (TES). From the surface to 80 km altitude, Mars-GRAM is based on the NASA Ames Mars General Circulation Model (MGCM). Above 80 km, Mars-GRAM is based on the University of Michigan Mars Thermospheric General Circulation Model (MTGCM). The most recent release of Mars-GRAM 2010 includes an update to Fortran 90/95 and the addition of adjustment factors. These adjustment factors are applied to the input data from the MGCM and the MTGCM for the mapping year 0 user-controlled dust case. The adjustment factors are expressed as a function of height (z), latitude and areocentric solar longitude (Ls).

Modelling Vulnerability and Range Shifts in Ant Communities Responding to Future Global Warming in Temperate Forests.

PubMed

Kwon, Tae-Sung; Li, Fengqing; Kim, Sung-Soo; Chun, Jung Hwa; Park, Young-Seuk

2016-01-01

Global warming is likely leading to species' distributional shifts, resulting in changes in local community compositions and diversity patterns. In this study, we applied species distribution models to evaluate the potential impacts of temperature increase on ant communities in Korean temperate forests, by testing hypotheses that 1) the risk of extinction of forest ant species would increase over time, and 2) the changes in species distribution ranges could drive upward movements of ant communities and further alter patterns of species richness. We sampled ant communities at 335 evenly distributed sites across South Korea and modelled the future distribution range for each species using generalized additive models. To account for spatial autocorrelation, autocovariate regressions were conducted prior to generalized additive models. Among 29 common ant species, 12 species were estimated to shrink their suitable geographic areas, whereas five species would benefit from future global warming. Species richness was highest at low altitudes in the current period, and it was projected to be highest at the mid-altitudes in the 2080s, resulting in an upward movement of 4.9 m yr-1. This altered the altitudinal pattern of species richness from a monotonic-decrease curve (common in temperate regions) to a bell-shaped curve (common in tropical regions). Overall, ant communities in temperate forests are vulnerable to the on-going global warming and their altitudinal movements are similar to other faunal communities.

Radar altimeter waveform modeled parameter recovery. [SEASAT-1 data

NASA Technical Reports Server (NTRS)

1981-01-01

Satellite-borne radar altimeters include waveform sampling gates providing point samples of the transmitted radar pulse after its scattering from the ocean's surface. Averages of the waveform sampler data can be fitted by varying parameters in a model mean return waveform. The theoretical waveform model used is described as well as a general iterative nonlinear least squares procedures used to obtain estimates of parameters characterizing the modeled waveform for SEASAT-1 data. The six waveform parameters recovered by the fitting procedure are: (1) amplitude; (2) time origin, or track point; (3) ocean surface rms roughness; (4) noise baseline; (5) ocean surface skewness; and (6) altitude or off-nadir angle. Additional practical processing considerations are addressed and FORTRAN source listing for subroutines used in the waveform fitting are included. While the description is for the Seasat-1 altimeter waveform data analysis, the work can easily be generalized and extended to other radar altimeter systems.

Generalized Galileons: instabilities of bouncing and Genesis cosmologies and modified Genesis

NASA Astrophysics Data System (ADS)

Libanov, M.; Mironov, S.; Rubakov, V.

2016-08-01

We study spatially flat bouncing cosmologies and models with the early-time Genesis epoch in a popular class of generalized Galileon theories. We ask whether there exist solutions of these types which are free of gradient and ghost instabilities. We find that irrespectively of the forms of the Lagrangian functions, the bouncing models either are plagued with these instabilities or have singularities. The same result holds for the original Genesis model and its variants in which the scale factor tends to a constant as t → -∞. The result remains valid in theories with additional matter that obeys the Null Energy Condition and interacts with the Galileon only gravitationally. We propose a modified Genesis model which evades our no-go argument and give an explicit example of healthy cosmology that connects the modified Genesis epoch with kination (the epoch still driven by the Galileon field, which is a conventional massless scalar field at that stage).

Improved short-term variability in the thermosphere-ionosphere-mesosphere-electrodynamics general circulation model

NASA Astrophysics Data System (ADS)

Häusler, K.; Hagan, M. E.; Baumgaertner, A. J. G.; Maute, A.; Lu, G.; Doornbos, E.; Bruinsma, S.; Forbes, J. M.; Gasperini, F.

2014-08-01

We report on a new source of tidal variability in the National Center for Atmospheric Research thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM). Lower boundary forcing of the TIME-GCM for a simulation of November-December 2009 based on 3-hourly Modern-Era Retrospective Analysis for Research and Application (MERRA) reanalysis data includes day-to-day variations in both diurnal and semidiurnal tides of tropospheric origin. Comparison with TIME-GCM results from a heretofore standard simulation that includes climatological tropospheric tides from the global-scale wave model reveal evidence of the impacts of MERRA forcing throughout the model domain, including measurable tidal variability in the TIME-GCM upper thermosphere. Additional comparisons with measurements made by the Gravity field and steady-state Ocean Circulation Explorer satellite show improved TIME-GCM capability to capture day-to-day variations in thermospheric density for the November-December 2009 period with the new MERRA lower boundary forcing.

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

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 1 2014-04-01 2014-04-01 false General restrictions on use of color additives. 70.5 Section 70.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL COLOR ADDITIVES General Provisions § 70.5 General restrictions on use of color additives. (a...

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

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 1 2013-04-01 2013-04-01 false General restrictions on use of color additives. 70.5 Section 70.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL COLOR ADDITIVES General Provisions § 70.5 General restrictions on use of color additives. (a...

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

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 1 2012-04-01 2012-04-01 false General restrictions on use of color additives. 70.5 Section 70.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL COLOR ADDITIVES General Provisions § 70.5 General restrictions on use of color additives. (a...

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

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 1 2010-04-01 2010-04-01 false General restrictions on use of color additives. 70.5 Section 70.5 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL COLOR ADDITIVES General Provisions § 70.5 General restrictions on use of color additives. (a...

Specific personality traits and general personality dysfunction as predictors of the presence and severity of personality disorders in a clinical sample.

PubMed

Berghuis, Han; Kamphuis, Jan H; Verheul, Roel

2014-01-01

This study examined the associations of specific personality traits and general personality dysfunction in relation to the presence and severity of Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]; American Psychiatric Association, 1994) personality disorders in a Dutch clinical sample. Two widely used measures of specific personality traits were selected, the Revised NEO Personality Inventory as a measure of normal personality traits, and the Dimensional Assessment of Personality Pathology-Basic Questionnaire as a measure of pathological traits. In addition, 2 promising measures of personality dysfunction were selected, the General Assessment of Personality Disorder and the Severity Indices of Personality Problems. Theoretically predicted associations were found between the measures, and all measures predicted the presence and severity of DSM-IV personality disorders. The combination of general personality dysfunction models and personality traits models provided incremental information about the presence and severity of personality disorders, suggesting that an integrative approach of multiple perspectives might serve comprehensive assessment of personality disorders.

Linking livestock snow disaster mortality and environmental stressors in the Qinghai-Tibetan Plateau: Quantification based on generalized additive models.

PubMed

Li, Yijia; Ye, Tao; Liu, Weihang; Gao, Yu

2018-06-01

Livestock snow disaster occurs widely in Central-to-Eastern Asian temperate and alpine grasslands. The effects of snow disaster on livestock involve a complex interaction between precipitation, vegetation, livestock, and herder communities. Quantifying the relationship among livestock mortality, snow hazard intensity, and seasonal environmental stressors is of great importance for snow disaster early warning, risk assessments, and adaptation strategies. Using a wide-spatial extent, long-time series, and event-based livestock snow disaster dataset, this study quantified those relationships and established a quantitative model of livestock mortality for prediction purpose for the Qinghai-Tibet Plateau region. Estimations using generalized additive models (GAMs) were shown to accurately predict livestock mortality and mortality rate due to snow disaster, with adjusted-R 2 up to 0.794 and 0.666, respectively. These results showed that a longer snow disaster duration, lower temperatures during the disaster, and a drier summer with less vegetation all contribute significantly and non-linearly to higher mortality (rate), after controlling for elevation and socioeconomic conditions. These results can be readily applied to risk assessment and risk-based adaptation actions. Copyright © 2017 Elsevier B.V. All rights reserved.

Compositions and their application to the analysis of choice.

PubMed

Jensen, Greg

2014-07-01

Descriptions of steady-state patterns of choice allocation under concurrent schedules of reinforcement have long relied on the "generalized matching law" (Baum, 1974), a log-odds power function. Although a powerful model in some contexts, a series of conflicting empirical results have cast its generality in doubt. The relevance and analytic relevance of matching models can be greatly expanded by considering them in terms of compositions (Aitchison, 1986). A composition encodes a set of ratios (e.g., 5:3:2) as a vector with a constant sum, and this constraint (called closure) restricts the data to a nonstandard sample space. By exploiting this sample space, unbiased estimates of model parameters can be obtained to predict behavior given any number of choice alternatives. Additionally, the compositional analysis of choice provides tools that can accommodate both violations of scale invariance and unequal discriminability of stimuli signaling schedules of reinforcement. In order to demonstrate how choice data can be analyzed using the compositional approach, data from three previously published studies are reanalyzed. Additionally, new data is reported comparing matching behavior given four, six, and eight response alternatives. © Society for the Experimental Analysis of Behavior.

Allele-sharing models: LOD scores and accurate linkage tests.

PubMed

Kong, A; Cox, N J

1997-11-01

Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested.

Allele-sharing models: LOD scores and accurate linkage tests.

PubMed Central

Kong, A; Cox, N J

1997-01-01

Starting with a test statistic for linkage analysis based on allele sharing, we propose an associated one-parameter model. Under general missing-data patterns, this model allows exact calculation of likelihood ratios and LOD scores and has been implemented by a simple modification of existing software. Most important, accurate linkage tests can be performed. Using an example, we show that some previously suggested approaches to handling less than perfectly informative data can be unacceptably conservative. Situations in which this model may not perform well are discussed, and an alternative model that requires additional computations is suggested. PMID:9345087

Auditory models for speech analysis

NASA Astrophysics Data System (ADS)

Maybury, Mark T.

This paper reviews the psychophysical basis for auditory models and discusses their application to automatic speech recognition. First an overview of the human auditory system is presented, followed by a review of current knowledge gleaned from neurological and psychoacoustic experimentation. Next, a general framework describes established peripheral auditory models which are based on well-understood properties of the peripheral auditory system. This is followed by a discussion of current enhancements to that models to include nonlinearities and synchrony information as well as other higher auditory functions. Finally, the initial performance of auditory models in the task of speech recognition is examined and additional applications are mentioned.

The linear relationship between the Vulnerable Elders Survey-13 score and mortality in an Asian population of community-dwelling older persons.

PubMed

Wang, Jye; Lin, Wender; Chang, Ling-Hui

2018-01-01

The Vulnerable Elders Survey-13 (VES-13) has been used as a screening tool to identify vulnerable community-dwelling older persons for more in-depth assessment and targeted interventions. Although many studies supported its use in different populations, few have addressed Asian populations. The optimal scaling system for the VES-13 in predicting health outcomes also has not been adequately tested. This study (1) assesses the applicability of the VES-13 to predict the mortality of community-dwelling older persons in Taiwan, (2) identifies the best scaling system for the VES-13 in predicting mortality using generalized additive models (GAMs), and (3) determines whether including covariates, such as socio-demographic factors and common geriatric syndromes, improves model fitting. This retrospective longitudinal cohort study analyzed the data of 2184 community-dwelling persons 65 years old or older from the 2003 wave of the national-wide Taiwan Longitudinal Study on Aging. Cox proportional hazards models and Generalized Additive Models (GAMs) were used. The VES-13 significantly predicted the mortality of Taiwan's community-dwelling elders. A one-point increase in the VES-13 score raised the risk of death by 26% (hazard ratio, 1.26; 95% confidence interval, 1.21-1.32). The hazard ratio of death increased linearly with each additional VES-13 score point, suggesting that using a continuous scale is appropriate. Inclusion of socio-demographic factors and geriatric syndromes improved the model-fitting. The VES-13 is appropriate for an Asian population. VES-13 scores linearly predict the mortality of this population. Adjusting the weighting of the physical activity items may improve the performance of the VES-13. Copyright © 2017 Elsevier B.V. All rights reserved.

An Underlying Common Factor, Influenced by Genetics and Unique Environment, Explains the Covariation Between Major Depressive Disorder, Generalized Anxiety Disorder, and Burnout: A Swedish Twin Study.

PubMed

Mather, Lisa; Blom, Victoria; Bergström, Gunnar; Svedberg, Pia

2016-12-01

Depression and anxiety are highly comorbid due to shared genetic risk factors, but less is known about whether burnout shares these risk factors. We aimed to examine whether the covariation between major depressive disorder (MDD), generalized anxiety disorder (GAD), and burnout is explained by common genetic and/or environmental factors. This cross-sectional study included 25,378 Swedish twins responding to a survey in 2005-2006. Structural equation models were used to analyze whether the trait variances and covariances were due to additive genetics, non-additive genetics, shared environment, and unique environment. Univariate analyses tested sex limitation models and multivariate analysis tested Cholesky, independent pathway, and common pathway models. The phenotypic correlations were 0.71 (0.69-0.74) between MDD and GAD, 0.58 (0.56-0.60) between MDD and burnout, and 0.53 (0.50-0.56) between GAD and burnout. Heritabilities were 45% for MDD, 49% for GAD, and 38% for burnout; no statistically significant sex differences were found. A common pathway model was chosen as the final model. The common factor was influenced by genetics (58%) and unique environment (42%), and explained 77% of the variation in MDD, 69% in GAD, and 44% in burnout. GAD and burnout had additive genetic factors unique to the phenotypes (11% each), while MDD did not. Unique environment explained 23% of the variability in MDD, 20% in GAD, and 45% in burnout. In conclusion, the covariation was explained by an underlying common factor, largely influenced by genetics. Burnout was to a large degree influenced by unique environmental factors not shared with MDD and GAD.

Change-in-ratio methods for estimating population size

USGS Publications Warehouse

Udevitz, Mark S.; Pollock, Kenneth H.; McCullough, Dale R.; Barrett, Reginald H.

2002-01-01

Change-in-ratio (CIR) methods can provide an effective, low cost approach for estimating the size of wildlife populations. They rely on being able to observe changes in proportions of population subclasses that result from the removal of a known number of individuals from the population. These methods were first introduced in the 1940’s to estimate the size of populations with 2 subclasses under the assumption of equal subclass encounter probabilities. Over the next 40 years, closed population CIR models were developed to consider additional subclasses and use additional sampling periods. Models with assumptions about how encounter probabilities vary over time, rather than between subclasses, also received some attention. Recently, all of these CIR models have been shown to be special cases of a more general model. Under the general model, information from additional samples can be used to test assumptions about the encounter probabilities and to provide estimates of subclass sizes under relaxations of these assumptions. These developments have greatly extended the applicability of the methods. CIR methods are attractive because they do not require the marking of individuals, and subclass proportions often can be estimated with relatively simple sampling procedures. However, CIR methods require a carefully monitored removal of individuals from the population, and the estimates will be of poor quality unless the removals induce substantial changes in subclass proportions. In this paper, we review the state of the art for closed population estimation with CIR methods. Our emphasis is on the assumptions of CIR methods and on identifying situations where these methods are likely to be effective. We also identify some important areas for future CIR research.

Generalized image charge solvation model for electrostatic interactions in molecular dynamics simulations of aqueous solutions

PubMed Central

Deng, Shaozhong; Xue, Changfeng; Baumketner, Andriy; Jacobs, Donald; Cai, Wei

2013-01-01

This paper extends the image charge solvation model (ICSM) [J. Chem. Phys. 131, 154103 (2009)], a hybrid explicit/implicit method to treat electrostatic interactions in computer simulations of biomolecules formulated for spherical cavities, to prolate spheroidal and triaxial ellipsoidal cavities, designed to better accommodate non-spherical solutes in molecular dynamics (MD) simulations. In addition to the utilization of a general truncated octahedron as the MD simulation box, central to the proposed extension is an image approximation method to compute the reaction field for a point charge placed inside such a non-spherical cavity by using a single image charge located outside the cavity. The resulting generalized image charge solvation model (GICSM) is tested in simulations of liquid water, and the results are analyzed in comparison with those obtained from the ICSM simulations as a reference. We find that, for improved computational efficiency due to smaller simulation cells and consequently a less number of explicit solvent molecules, the generalized model can still faithfully reproduce known static and dynamic properties of liquid water at least for systems considered in the present paper, indicating its great potential to become an accurate but more efficient alternative to the ICSM when bio-macromolecules of irregular shapes are to be simulated. PMID:23913979

Analysis of nonlocal neural fields for both general and gamma-distributed connectivities

NASA Astrophysics Data System (ADS)

Hutt, Axel; Atay, Fatihcan M.

2005-04-01

This work studies the stability of equilibria in spatially extended neuronal ensembles. We first derive the model equation from statistical properties of the neuron population. The obtained integro-differential equation includes synaptic and space-dependent transmission delay for both general and gamma-distributed synaptic connectivities. The latter connectivity type reveals infinite, finite, and vanishing self-connectivities. The work derives conditions for stationary and nonstationary instabilities for both kernel types. In addition, a nonlinear analysis for general kernels yields the order parameter equation of the Turing instability. To compare the results to findings for partial differential equations (PDEs), two typical PDE-types are derived from the examined model equation, namely the general reaction-diffusion equation and the Swift-Hohenberg equation. Hence, the discussed integro-differential equation generalizes these PDEs. In the case of the gamma-distributed kernels, the stability conditions are formulated in terms of the mean excitatory and inhibitory interaction ranges. As a novel finding, we obtain Turing instabilities in fields with local inhibition-lateral excitation, while wave instabilities occur in fields with local excitation and lateral inhibition. Numerical simulations support the analytical results.

Picture this: The value of multiple visual representations for student learning of quantum concepts in general chemistry

NASA Astrophysics Data System (ADS)

Allen, Emily Christine

Mental models for scientific learning are often defined as, "cognitive tools situated between experiments and theories" (Duschl & Grandy, 2012). In learning, these cognitive tools are used to not only take in new information, but to help problem solve in new contexts. Nancy Nersessian (2008) describes a mental model as being "[loosely] characterized as a representation of a system with interactive parts with representations of those interactions. Models can be qualitative, quantitative, and/or simulative (mental, physical, computational)" (p. 63). If conceptual parts used by the students in science education are inaccurate, then the resulting model will not be useful. Students in college general chemistry courses are presented with multiple abstract topics and often struggle to fit these parts into complete models. This is especially true for topics that are founded on quantum concepts, such as atomic structure and molecular bonding taught in college general chemistry. The objectives of this study were focused on how students use visual tools introduced during instruction to reason with atomic and molecular structure, what misconceptions may be associated with these visual tools, and how visual modeling skills may be taught to support students' use of visual tools for reasoning. The research questions for this study follow from Gilbert's (2008) theory that experts use multiple representations when reasoning and modeling a system, and Kozma and Russell's (2005) theory of representational competence levels. This study finds that as students developed greater command of their understanding of abstract quantum concepts, they spontaneously provided additional representations to describe their more sophisticated models of atomic and molecular structure during interviews. This suggests that when visual modeling with multiple representations is taught, along with the limitations of the representations, it can assist students in the development of models for reasoning about abstract topics such as atomic and molecular structure. There is further gain if students' difficulties with these representations are targeted through the use additional instruction such as a workbook that requires the students to exercise their visual modeling skills.

A generalized groundwater fluctuation model based on precipitation for estimating water table levels of deep unconfined aquifers

NASA Astrophysics Data System (ADS)

Jeong, Jina; Park, Eungyu; Shik Han, Weon; Kim, Kue-Young; Suk, Heejun; Beom Jo, Si

2018-07-01

A generalized water table fluctuation model based on precipitation was developed using a statistical conceptualization of unsaturated infiltration fluxes. A gamma distribution function was adopted as a transfer function due to its versatility in representing recharge rates with temporally dispersed infiltration fluxes, and a Laplace transformation was used to obtain an analytical solution. To prove the general applicability of the model, convergences with previous water table fluctuation models were shown as special cases. For validation, a few hypothetical cases were developed, where the applicability of the model to a wide range of unsaturated zone conditions was confirmed. For further validation, the model was applied to water table level estimations of three monitoring wells with considerably thick unsaturated zones on Jeju Island. The results show that the developed model represented the pattern of hydrographs from the two monitoring wells fairly well. The lag times from precipitation to recharge estimated from the developed system transfer function were found to agree with those from a conventional cross-correlation analysis. The developed model has the potential to be adopted for the hydraulic characterization of both saturated and unsaturated zones by being calibrated to actual data when extraneous and exogenous causes of water table fluctuation are limited. In addition, as it provides reference estimates, the model can be adopted as a tool for surveilling groundwater resources under hydraulically stressed conditions.

Stratospheric temperatures and tracer transport in a nudged 4-year middle atmosphere GCM simulation

NASA Astrophysics Data System (ADS)

van Aalst, M. K.; Lelieveld, J.; Steil, B.; Brühl, C.; Jöckel, P.; Giorgetta, M. A.; Roelofs, G.-J.

2005-02-01

We have performed a 4-year simulation with the Middle Atmosphere General Circulation Model MAECHAM5/MESSy, while slightly nudging the model's meteorology in the free troposphere (below 113 hPa) towards ECMWF analyses. We show that the nudging 5 technique, which leaves the middle atmosphere almost entirely free, enables comparisons with synoptic observations. The model successfully reproduces many specific features of the interannual variability, including details of the Antarctic vortex structure. In the Arctic, the model captures general features of the interannual variability, but falls short in reproducing the timing of sudden stratospheric warmings. A 10 detailed comparison of the nudged model simulations with ECMWF data shows that the model simulates realistic stratospheric temperature distributions and variabilities, including the temperature minima in the Antarctic vortex. Some small (a few K) model biases were also identified, including a summer cold bias at both poles, and a general cold bias in the lower stratosphere, most pronounced in midlatitudes. A comparison 15 of tracer distributions with HALOE observations shows that the model successfully reproduces specific aspects of the instantaneous circulation. The main tracer transport deficiencies occur in the polar lowermost stratosphere. These are related to the tropopause altitude as well as the tracer advection scheme and model resolution. The additional nudging of equatorial zonal winds, forcing the quasi-biennial oscillation, sig20 nificantly improves stratospheric temperatures and tracer distributions.

A stochastic diffusion process for Lochner's generalized Dirichlet distribution

DOE PAGES

Bakosi, J.; Ristorcelli, J. R.

2013-10-01

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N stochastic variables with Lochner’s generalized Dirichlet distribution as its asymptotic solution. Individual samples of a discrete ensemble, obtained from the system of stochastic differential equations, equivalent to the Fokker-Planck equation developed here, satisfy a unit-sum constraint at all times and ensure a bounded sample space, similarly to the process developed in for the Dirichlet distribution. Consequently, the generalized Dirichlet diffusion process may be used to represent realizations of a fluctuating ensemble of N variables subject to a conservation principle.more » Compared to the Dirichlet distribution and process, the additional parameters of the generalized Dirichlet distribution allow a more general class of physical processes to be modeled with a more general covariance matrix.« less

Pond tadpoles with generalized morphology: is it time to reconsider their functional roles in aquatic communities?

PubMed

Petranka, James W; Kennedy, Caroline A

1999-09-01

With rare exceptions, anuran larvae have traditionally been considered to occupy lower trophic levels in aquatic communities where they function as microphagous suspension feeders. This view is being challenged by studies showing that tadpoles with generalized morphology often function as macrophagous predators. Here, we review the literature concerning macrophagy by tadpoles and provide two additional examples involving generalized tadpoles. In the first, we demonstrate with laboratory and field experiments that wood frog (Rana sylvatica) tadpoles are major predators of macroinvertebrates in ponds. In the second, we show that green frog (R. clamitans) tadpoles can cause catastrophic reproductive failure of the wood frog via egg predation. These results and data from other studies challenge the assumption that generalized tadpoles function as filter-feeding omnivores, and question the general applicability of community organization models which assume that predation risk increases with pond permanence. We suggest that predation risk is greater in temporary ponds than in more permanent ponds for many organisms that are vulnerable to predation by tadpoles. This being so, a conditional model based upon interactions that are species-specific, life-stage-specific, and context-dependent may better explain community organization along hydrological gradients than models which assume that temporary ponds have few or no predators.

Association of daily asthma emergency department visits and hospital admissions with ambient air pollutants among the pediatric Medicaid population in Detroit: time-series and time-stratified case-crossover analyses with threshold effects.

PubMed

Li, Shi; Batterman, Stuart; Wasilevich, Elizabeth; Wahl, Robert; Wirth, Julie; Su, Feng-Chiao; Mukherjee, Bhramar

2011-11-01

Asthma morbidity has been associated with ambient air pollutants in time-series and case-crossover studies. In such study designs, threshold effects of air pollutants on asthma outcomes have been relatively unexplored, which are of potential interest for exploring concentration-response relationships. This study analyzes daily data on the asthma morbidity experienced by the pediatric Medicaid population (ages 2-18 years) of Detroit, Michigan and concentrations of pollutants fine particles (PM2.5), CO, NO2 and SO2 for the 2004-2006 period, using both time-series and case-crossover designs. We use a simple, testable and readily implementable profile likelihood-based approach to estimate threshold parameters in both designs. Evidence of significant increases in daily acute asthma events was found for SO2 and PM2.5, and a significant threshold effect was estimated for PM2.5 at 13 and 11 μg m(-3) using generalized additive models and conditional logistic regression models, respectively. Stronger effect sizes above the threshold were typically noted compared to standard linear relationship, e.g., in the time series analysis, an interquartile range increase (9.2 μg m(-3)) in PM2.5 (5-day-moving average) had a risk ratio of 1.030 (95% CI: 1.001, 1.061) in the generalized additive models, and 1.066 (95% CI: 1.031, 1.102) in the threshold generalized additive models. The corresponding estimates for the case-crossover design were 1.039 (95% CI: 1.013, 1.066) in the conditional logistic regression, and 1.054 (95% CI: 1.023, 1.086) in the threshold conditional logistic regression. This study indicates that the associations of SO2 and PM2.5 concentrations with asthma emergency department visits and hospitalizations, as well as the estimated PM2.5 threshold were fairly consistent across time-series and case-crossover analyses, and suggests that effect estimates based on linear models (without thresholds) may underestimate the true risk. Copyright © 2011 Elsevier Inc. All rights reserved.

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249

Sensitivity to Uncertainty in Asteroid Impact Risk Assessment

NASA Astrophysics Data System (ADS)

Mathias, D.; Wheeler, L.; Prabhu, D. K.; Aftosmis, M.; Dotson, J.; Robertson, D. K.

2015-12-01

The Engineering Risk Assessment (ERA) team at NASA Ames Research Center is developing a physics-based impact risk model for probabilistically assessing threats from potential asteroid impacts on Earth. The model integrates probabilistic sampling of asteroid parameter ranges with physics-based analyses of entry, breakup, and impact to estimate damage areas and casualties from various impact scenarios. Assessing these threats is a highly coupled, dynamic problem involving significant uncertainties in the range of expected asteroid characteristics, how those characteristics may affect the level of damage, and the fidelity of various modeling approaches and assumptions. The presented model is used to explore the sensitivity of impact risk estimates to these uncertainties in order to gain insight into what additional data or modeling refinements are most important for producing effective, meaningful risk assessments. In the extreme cases of very small or very large impacts, the results are generally insensitive to many of the characterization and modeling assumptions. However, the nature of the sensitivity can change across moderate-sized impacts. Results will focus on the value of additional information in this critical, mid-size range, and how this additional data can support more robust mitigation decisions.

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

PubMed

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.

Computational Modeling of Low-Density Ultracold Plasmas

NASA Astrophysics Data System (ADS)

Witte, Craig

In this dissertation I describe a number of different computational investigations which I have undertaken during my time at Colorado State University. Perhaps the most significant of my accomplishments was the development of a general molecular dynamic model that simulates a wide variety of physical phenomena in ultracold plasmas (UCPs). This model formed the basis of most of the numerical investigations discussed in this thesis. The model utilized the massively parallel architecture of GPUs to achieve significant computing speed increases (up to 2 orders of magnitude) above traditional single core computing. This increased computing power allowed for each particle in an actual UCP experimental system to be explicitly modeled in simulations. By using this model, I was able to undertake a number of theoretical investigations into ultracold plasma systems. Chief among these was our lab's investigation of electron center-of-mass damping, in which the molecular dynamics model was an essential tool in interpreting the results of the experiment. Originally, it was assumed that this damping would solely be a function of electron-ion collisions. However, the model was able to identify an additional collisionless damping mechanism that was determined to be significant in the first iteration of our experiment. To mitigate this collisionless damping, the model was used to find a new parameter range where this mechanism was negligible. In this new parameter range, the model was an integral part in verifying the achievement of a record low measured UCP electron temperature of 1.57 +/- 0.28K and a record high electron strong coupling parameter, Gamma, of 0.35 +/-0.08$. Additionally, the model, along with experimental measurements, was used to verify the breakdown of the standard weak coupling approximation for Coulomb collisions. The general molecular dynamics model was also used in other contexts. These included the modeling of both the formation process of ultracold plasmas and the thermalization of the electron component of an ultracold plasma. Our modeling of UCP formation is still in its infancy, and there is still much outstanding work. However, we have already discovered a previously unreported electron heating mechanism that arises from an external electric field being applied during UCP formation. Thermalization modeling showed that the ion density distribution plays a role in the thermalization of electrons in ultracold plasma, a consideration not typically included in plasma modeling. A Gaussian ion density distribution was shown to lead to a slightly faster electron thermalization rate than an equivalent uniform ion density distribution as a result of collisionless effects. Three distinct phases of UCP electron thermalization during formation were identified. Finally, the dissertation will describe additional computational investigations that preceded the general molecular dynamics model. These include simulations of ultracold plasma ion expansion driven by non-neutrality, as well as an investigation into electron evaporation. To test the effects of non-neutrality on ion expansion, a numerical model was developed that used the King model of the electron to describe the electron distribution for an arbitrary charge imbalance. The model found that increased non-neutrality of the plasma led to the rapid expansion of ions on the plasma exterior, which in turn led to a sharp ion cliff-like spatial structure. Additionally, this rapid expansion led to additional cooling of the electron component of the plasma. The evaporation modeling was used to test the underlying assumptions of previously developed analytical expression for charged particle evaporation. The model used Monte Carlo techniques to simulate the collisions and the evaporation process. The model found that neither of the underlying assumption of the charged particle evaporation expressions held true for typical ultracold plasma parameters and provides a route for computations in spite of the breakdown of these two typical assumptions.

Models for Conducting Institutional Research. New Directions for Community Colleges, Number 72.

ERIC Educational Resources Information Center

MacDougall, Peter, Ed.; Friedlander, Jack, Ed.

1990-01-01

Recent mandates from state and accrediting agencies are requiring community colleges to provide evidence of their success in such areas as basic skills and remediation, general education, major-field content, student development, transfer effectiveness, job training, job placement, and fiscal accountability. This volume, in addition to describing…

Teaching Mass and Energy Balances by Experiment

ERIC Educational Resources Information Center

Orbey, Nese; De Jesús Vega, Marisel; Zalluhoglu, Fulya Sudur

2017-01-01

A general tank-draining problem was used as an experimental project in two undergraduate-level chemical engineering courses. The project aimed to illustrate the critical nature of experimentation in addition to use of mass and energy conservation principles in developing mathematical models that correctly describes a system. The students designed…

EXAMINATION OF QUINONE TOXICITY USING YEAST SACCHAROMYCES CEREVISIAE MODEL SYSTEM. (R827352C007)

EPA Science Inventory

The toxicity of quinones is generally thought to occur by two mechanisms: the formation of covalent bonds with biological molecules by Michael addition chemistry and the catalytic reduction of oxygen to superoxide and other reactive oxygen species (ROS) (redox cycling). In an ...

In-Class Purposes of Flipped Mathematics Educators

ERIC Educational Resources Information Center

Eisenhut, Lindsay A.; Taylor, Cynthia E.

2015-01-01

This paper provides empirical findings from a study that examined how three grade 7-12 flipped mathematics educators utilized class time when implementing a flipped learning model. Additionally, the researchers investigated the educators' purposes for various in-class tasks as well as their general use of class time. The data revealed flipped…

Sex Education for Deaf-Blind Youths and Adults.

ERIC Educational Resources Information Center

Ingraham, Cynthia L.; Vernon, McCay; Clemente, Brenda; Olney, Linda

2000-01-01

This article describes a model sex education program developed for youths and adults who are deafblind by the Helen Keller National Center for Deaf-Blind Youths and Adults. In addition, it also discusses major related issues and presents general recommendations and a resource for further information. (Contains 11 references.) (Author/CR)

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

NASA Astrophysics Data System (ADS)

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.

Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates

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

Sengupta, Manajit; Gotseff, Peter

2013-12-01

This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear skymore » model performance.« less

A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models.

PubMed

Brouwer, Andrew F; Meza, Rafael; Eisenberg, Marisa C

2017-07-01

Multistage clonal expansion (MSCE) models of carcinogenesis are continuous-time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous-time Markov processes. © 2016 Society for Risk Analysis.

Beyond Negative Affectivity: A Hierarchical Model of Global and Transdiagnostic Vulnerabilities for Emotional Disorders.

PubMed

Paulus, Daniel J; Talkovsky, Alexander M; Heggeness, Luke F; Norton, Peter J

2015-01-01

Negative affectivity (NA) has been linked to anxiety and depression (DEP). Identifying the common factors between anxiety and DEP is important when explaining their overlap and comorbidity. However, general factors such as NA tend to have differential relationships with different disorders, suggesting the need to identify mediators in order to explicate these relationships. The current study tests a theoretically and empirically derived hierarchical model of emotional disorders including both a general factor (NA) and transdiagnostic risk factors [anxiety sensitivity (AS) and intolerance of uncertainty (IoU)] using structural equation modeling. AS was tested as a mid-level factor between NA and panic disorder/agoraphobia, while IoU was tested as a mid-level factor between NA and social phobia, generalized anxiety disorder, obsessive-compulsive disorder, and DEP. Data from 642 clinical outpatients with a heterogeneous presentation of emotional disorders were available for analysis. The hierarchical model fits the data adequately. Moreover, while a simplified model removing AS and IoU fits the data well, it resulted in a significant loss of information for all latent disorder constructs. Data were unavailable to estimate post-traumatic stress disorder or specific phobias. Future work will need to extend to other emotional disorders. This study demonstrates the importance of both general factors that link disorders together and semi-specific transdiagnostic factors partially explaining their heterogeneity. Including these mid-level factors in hierarchical models of psychopathology can help account for additional variance and help to clarify the relationship between disorder constructs and NA.

A Time-Regularized, Multiple Gravity-Assist Low-Thrust, Bounded-Impulse Model for Trajectory Optimization

NASA Technical Reports Server (NTRS)

Ellison, Donald H.; Englander, Jacob A.; Conway, Bruce A.

2017-01-01

The multiple gravity assist low-thrust (MGALT) trajectory model combines the medium-fidelity Sims-Flanagan bounded-impulse transcription with a patched-conics flyby model and is an important tool for preliminary trajectory design. While this model features fast state propagation via Keplers equation and provides a pleasingly accurate estimation of the total mass budget for the eventual flight suitable integrated trajectory it does suffer from one major drawback, namely its temporal spacing of the control nodes. We introduce a variant of the MGALT transcription that utilizes the generalized anomaly from the universal formulation of Keplers equation as a decision variable in addition to the trajectory phase propagation time. This results in two improvements over the traditional model. The first is that the maneuver locations are equally spaced in generalized anomaly about the orbit rather than time. The second is that the Kepler propagator now has the generalized anomaly as its independent variable instead of time and thus becomes an iteration-free propagation method. The new algorithm is outlined, including the impact that this has on the computation of Jacobian entries for numerical optimization, and a motivating application problem is presented that illustrates the improvements that this model has over the traditional MGALT transcription.

A Time-Regularized Multiple Gravity-Assist Low-Thrust Bounded-Impulse Model for Trajectory Optimization

NASA Technical Reports Server (NTRS)

Ellison, Donald H.; Englander, Jacob A.; Conway, Bruce A.

2017-01-01

The multiple gravity assist low-thrust (MGALT) trajectory model combines the medium-fidelity Sims-Flanagan bounded-impulse transcription with a patched-conics flyby model and is an important tool for preliminary trajectory design. While this model features fast state propagation via Kepler's equation and provides a pleasingly accurate estimation of the total mass budget for the eventual flight-suitable integrated trajectory it does suffer from one major drawback, namely its temporal spacing of the control nodes. We introduce a variant of the MGALT transcription that utilizes the generalized anomaly from the universal formulation of Kepler's equation as a decision variable in addition to the trajectory phase propagation time. This results in two improvements over the traditional model. The first is that the maneuver locations are equally spaced in generalized anomaly about the orbit rather than time. The second is that the Kepler propagator now has the generalized anomaly as its independent variable instead of time and thus becomes an iteration-free propagation method. The new algorithm is outlined, including the impact that this has on the computation of Jacobian entries for numerical optimization, and a motivating application problem is presented that illustrates the improvements that this model has over the traditional MGALT transcription.

Using multiple-exemplar training to teach a generalized repertoire of sharing to children with autism.

PubMed

Marzullo-Kerth, Denise; Reeve, Sharon A; Reeve, Kenneth F; Townsend, Dawn B

2011-01-01

The current study examined the utility of multiple-exemplar training to teach children with autism to share. Stimuli from 3 of 4 categories were trained using a treatment package of video modeling, prompting, and reinforcement. Offers to share increased for all 3 children following the introduction of treatment, with evidence of skill maintenance. In addition, within-stimulus-category generalization of sharing was evident for all participants, although only 1 participant demonstrated across-category generalization of sharing. Offers to share occurred in a novel setting, with familiar and novel stimuli, and in the presence of novel adults and peers for all participants during posttreatment probes.

Generalized Heisenberg Algebras, SUSYQM and Degeneracies: Infinite Well and Morse Potential

NASA Astrophysics Data System (ADS)

Hussin, Véronique; Marquette, Ian

2011-03-01

We consider classical and quantum one and two-dimensional systems with ladder operators that satisfy generalized Heisenberg algebras. In the classical case, this construction is related to the existence of closed trajectories. In particular, we apply these results to the infinite well and Morse potentials. We discuss how the degeneracies of the permutation symmetry of quantum two-dimensional systems can be explained using products of ladder operators. These products satisfy interesting commutation relations. The two-dimensional Morse quantum system is also related to a generalized two-dimensional Morse supersymmetric model. Arithmetical or accidental degeneracies of such system are shown to be associated to additional supersymmetry.

LETTER TO THE EDITOR: The quantum Knizhnik Zamolodchikov equation, generalized Razumov Stroganov sum rules and extended Joseph polynomials

NASA Astrophysics Data System (ADS)

Di Francesco, P.; Zinn-Justin, P.

2005-12-01

We prove higher rank analogues of the Razumov Stroganov sum rule for the ground state of the O(1) loop model on a semi-infinite cylinder: we show that a weighted sum of components of the ground state of the Ak-1 IRF model yields integers that generalize the numbers of alternating sign matrices. This is done by constructing minimal polynomial solutions of the level 1 U_q(\\widehat{\\frak{sl}(k)}) quantum Knizhnik Zamolodchikov equations, which may also be interpreted as quantum incompressible q-deformations of quantum Hall effect wavefunctions at filling fraction ν = k. In addition to the generalized Razumov Stroganov point q = -eiπ/k+1, another combinatorially interesting point is reached in the rational limit q → -1, where we identify the solution with extended Joseph polynomials associated with the geometry of upper triangular matrices with vanishing kth power.

The accuracy of ultrashort echo time MRI sequences for medical additive manufacturing

PubMed Central

Rijkhorst, Erik-Jan; Hofman, Mark; Forouzanfar, Tymour; Wolff, Jan

2016-01-01

Objectives: Additively manufactured bone models, implants and drill guides are becoming increasingly popular amongst maxillofacial surgeons and dentists. To date, such constructs are commonly manufactured using CT technology that induces ionizing radiation. Recently, ultrashort echo time (UTE) MRI sequences have been developed that allow radiation-free imaging of facial bones. The aim of the present study was to assess the feasibility of UTE MRI sequences for medical additive manufacturing (AM). Methods: Three morphologically different dry human mandibles were scanned using a CT and MRI scanner. Additionally, optical scans of all three mandibles were made to acquire a “gold standard”. All CT and MRI scans were converted into Standard Tessellation Language (STL) models and geometrically compared with the gold standard. To quantify the accuracy of the AM process, the CT, MRI and gold-standard STL models of one of the mandibles were additively manufactured, optically scanned and compared with the original gold-standard STL model. Results: Geometric differences between all three CT-derived STL models and the gold standard were <1.0 mm. All three MRI-derived STL models generally presented deviations <1.5 mm in the symphyseal and mandibular area. The AM process introduced minor deviations of <0.5 mm. Conclusions: This study demonstrates that MRI using UTE sequences is a feasible alternative to CT in generating STL models of the mandible and would therefore be suitable for surgical planning and AM. Further in vivo studies are necessary to assess the usability of UTE MRI sequences in clinical settings. PMID:26943179

Quantum field theory in generalised Snyder spaces

NASA Astrophysics Data System (ADS)

Meljanac, S.; Meljanac, D.; Mignemi, S.; Štrajn, R.

2017-05-01

We discuss the generalisation of the Snyder model that includes all possible deformations of the Heisenberg algebra compatible with Lorentz invariance and investigate its properties. We calculate perturbatively the law of addition of momenta and the star product in the general case. We also undertake the construction of a scalar field theory on these noncommutative spaces showing that the free theory is equivalent to the commutative one, like in other models of noncommutative QFT.

Who needs collaborative care treatment? A qualitative study exploring attitudes towards and experiences with mental healthcare among general practitioners and care managers.

PubMed

Møller, Marlene Christina Rosengaard; Mygind, Anna; Bro, Flemming

2018-05-30

Collaborative care treatment is widely recognized as an effective approach to improve the quality of mental healthcare through enhanced and structured collaboration between general practice and specialized psychiatry. However, studies indicate that the complexity of collaborative care treatment interventions challenge the implementation in real-life general practice settings. Four Danish Collaborative Care Models were launched in 2014 for patients with mild/moderate anxiety and depression. These involved collaboration between general practitioners, care managers and consultant psychiatrists. Taking a multi-practice bottom-up approach, this paper aims to explore the perceived barriers and enablers related to collaborative care for patients with mental health problems and to investigate the actual experiences with a Danish collaborative care model in a single-case study in order to identify enablers and barriers for successful implementation. Combining interviews and observations of usual treatment practices, we conducted a multi-practice study among general practitioners who were not involved in the Danish collaborative care models to explore their perspectives on existing mental health treatment and to investigate (from a bottom-up approach) their perceptions of and need for collaborative care in mental health treatment. Additionally, by combining observations and qualitative interviews, we followed the implementation of a Danish collaborative care model in a single-case study to convey identified barriers and enablers of the collaborative care model. Experienced and perceived enablers of the Danish collaborative care model mainly consisted of a need for new treatment options to deal with mild/moderate anxiety and depression. The model was considered to meet the need for a free fast track to high-quality treatment. Experienced barriers included: poor adaptation of the model to the working conditions and needs in daily general practice, time consumption, unsustainable logistical set-up and unclear care manager role. General practitioners in the multi-practice study considered access to treatment and not collaboration with specialised psychiatry to be essential for this group of patients. The study calls for increased attention to implementation processes and better adaptation of collaborative care models to the clinical reality of general practice. Future interventions should address the treatment needs of specific patient populations and should involve relevant stakeholders in the design and implementation processes.

Evaluating mallard adaptive management models with time series

USGS Publications Warehouse

Conn, P.B.; Kendall, W.L.

2004-01-01

Wildlife practitioners concerned with midcontinent mallard (Anas platyrhynchos) management in the United States have instituted a system of adaptive harvest management (AHM) as an objective format for setting harvest regulations. Under the AHM paradigm, predictions from a set of models that reflect key uncertainties about processes underlying population dynamics are used in coordination with optimization software to determine an optimal set of harvest decisions. Managers use comparisons of the predictive abilities of these models to gauge the relative truth of different hypotheses about density-dependent recruitment and survival, with better-predicting models giving more weight to the determination of harvest regulations. We tested the effectiveness of this strategy by examining convergence rates of 'predictor' models when the true model for population dynamics was known a priori. We generated time series for cases when the a priori model was 1 of the predictor models as well as for several cases when the a priori model was not in the model set. We further examined the addition of different levels of uncertainty into the variance structure of predictor models, reflecting different levels of confidence about estimated parameters. We showed that in certain situations, the model-selection process favors a predictor model that incorporates the hypotheses of additive harvest mortality and weakly density-dependent recruitment, even when the model is not used to generate data. Higher levels of predictor model variance led to decreased rates of convergence to the model that generated the data, but model weight trajectories were in general more stable. We suggest that predictive models should incorporate all sources of uncertainty about estimated parameters, that the variance structure should be similar for all predictor models, and that models with different functional forms for population dynamics should be considered for inclusion in predictor model! sets. All of these suggestions should help lower the probability of erroneous learning in mallard ABM and adaptive management in general.

A penalized framework for distributed lag non-linear models.

PubMed

Gasparrini, Antonio; Scheipl, Fabian; Armstrong, Ben; Kenward, Michael G

2017-09-01

Distributed lag non-linear models (DLNMs) are a modelling tool for describing potentially non-linear and delayed dependencies. Here, we illustrate an extension of the DLNM framework through the use of penalized splines within generalized additive models (GAM). This extension offers built-in model selection procedures and the possibility of accommodating assumptions on the shape of the lag structure through specific penalties. In addition, this framework includes, as special cases, simpler models previously proposed for linear relationships (DLMs). Alternative versions of penalized DLNMs are compared with each other and with the standard unpenalized version in a simulation study. Results show that this penalized extension to the DLNM class provides greater flexibility and improved inferential properties. The framework exploits recent theoretical developments of GAMs and is implemented using efficient routines within freely available software. Real-data applications are illustrated through two reproducible examples in time series and survival analysis. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

Penalized nonparametric scalar-on-function regression via principal coordinates

PubMed Central

Reiss, Philip T.; Miller, David L.; Wu, Pei-Shien; Hua, Wen-Yu

2016-01-01

A number of classical approaches to nonparametric regression have recently been extended to the case of functional predictors. This paper introduces a new method of this type, which extends intermediate-rank penalized smoothing to scalar-on-function regression. In the proposed method, which we call principal coordinate ridge regression, one regresses the response on leading principal coordinates defined by a relevant distance among the functional predictors, while applying a ridge penalty. Our publicly available implementation, based on generalized additive modeling software, allows for fast optimal tuning parameter selection and for extensions to multiple functional predictors, exponential family-valued responses, and mixed-effects models. In an application to signature verification data, principal coordinate ridge regression, with dynamic time warping distance used to define the principal coordinates, is shown to outperform a functional generalized linear model. PMID:29217963

Dynamical analysis of an n‑H‑T cosmological quintessence real gas model with a general equation of state

NASA Astrophysics Data System (ADS)

Ivanov, Rossen I.; Prodanov, Emil M.

2018-01-01

The cosmological dynamics of a quintessence model based on real gas with general equation of state is presented within the framework of a three-dimensional dynamical system describing the time evolution of the number density, the Hubble parameter and the temperature. Two global first integrals are found and examples for gas with virial expansion and van der Waals gas are presented. The van der Waals system is completely integrable. In addition to the unbounded trajectories, stemming from the presence of the conserved quantities, stable periodic solutions (closed orbits) also exist under certain conditions and these represent models of a cyclic Universe. The cyclic solutions exhibit regions characterized by inflation and deflation, while the open trajectories are characterized by inflation in a “fly-by” near an unstable critical point.

Multi Sensor Data Integration for AN Accurate 3d Model Generation

NASA Astrophysics Data System (ADS)

Chhatkuli, S.; Satoh, T.; Tachibana, K.

2015-05-01

The aim of this paper is to introduce a novel technique of data integration between two different data sets, i.e. laser scanned RGB point cloud and oblique imageries derived 3D model, to create a 3D model with more details and better accuracy. In general, aerial imageries are used to create a 3D city model. Aerial imageries produce an overall decent 3D city models and generally suit to generate 3D model of building roof and some non-complex terrain. However, the automatically generated 3D model, from aerial imageries, generally suffers from the lack of accuracy in deriving the 3D model of road under the bridges, details under tree canopy, isolated trees, etc. Moreover, the automatically generated 3D model from aerial imageries also suffers from undulated road surfaces, non-conforming building shapes, loss of minute details like street furniture, etc. in many cases. On the other hand, laser scanned data and images taken from mobile vehicle platform can produce more detailed 3D road model, street furniture model, 3D model of details under bridge, etc. However, laser scanned data and images from mobile vehicle are not suitable to acquire detailed 3D model of tall buildings, roof tops, and so forth. Our proposed approach to integrate multi sensor data compensated each other's weakness and helped to create a very detailed 3D model with better accuracy. Moreover, the additional details like isolated trees, street furniture, etc. which were missing in the original 3D model derived from aerial imageries could also be integrated in the final model automatically. During the process, the noise in the laser scanned data for example people, vehicles etc. on the road were also automatically removed. Hence, even though the two dataset were acquired in different time period the integrated data set or the final 3D model was generally noise free and without unnecessary details.

Assessment of corneal properties based on statistical modeling of OCT speckle.

PubMed

Jesus, Danilo A; Iskander, D Robert

2017-01-01

A new approach to assess the properties of the corneal micro-structure in vivo based on the statistical modeling of speckle obtained from Optical Coherence Tomography (OCT) is presented. A number of statistical models were proposed to fit the corneal speckle data obtained from OCT raw image. Short-term changes in corneal properties were studied by inducing corneal swelling whereas age-related changes were observed analyzing data of sixty-five subjects aged between twenty-four and seventy-three years. Generalized Gamma distribution has shown to be the best model, in terms of the Akaike's Information Criterion, to fit the OCT corneal speckle. Its parameters have shown statistically significant differences (Kruskal-Wallis, p < 0.001) for short and age-related corneal changes. In addition, it was observed that age-related changes influence the corneal biomechanical behaviour when corneal swelling is induced. This study shows that Generalized Gamma distribution can be utilized to modeling corneal speckle in OCT in vivo providing complementary quantified information where micro-structure of corneal tissue is of essence.

Energy budgets of animals: behavioral and ecological implications

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

Porter, W P

1979-01-01

This year's progress has been: (1) to extend the general microclimate model two ways: (a) to incorporate wet ground surfaces (bogs), and (b) to incorporate slope effects. Tests of the model in a Michigan bog and the Galapagos Islands show temperature accuracies to within 4/sup 0/C at worst at any soil or air location, which is about a 2% error in estimation of metabolism. (2) The addition to ectotherm modeling an analysis of: (a) reproduction in heterogeneous and uncertain environments; (b) prediction of distribution limits due to egg incubation requirements; (c) addition of appendage-torso modeling and tests on large ectotherms;more » (d) social systems interactions with environmental and physiological variables; and (3) to continue the endotherm (deer mouse) experimental research and extend the growth and reproduction studies to include the entire reproductive and growth cycle in the deer mouse.« less

A novel heuristic for optimization aggregate production problem: Evidence from flat panel display in Malaysia

NASA Astrophysics Data System (ADS)

Al-Kuhali, K.; Hussain M., I.; Zain Z., M.; Mullenix, P.

2015-05-01

Aim: This paper contribute to the flat panel display industry it terms of aggregate production planning. Methodology: For the minimization cost of total production of LCD manufacturing, a linear programming was applied. The decision variables are general production costs, additional cost incurred for overtime production, additional cost incurred for subcontracting, inventory carrying cost, backorder costs and adjustments for changes incurred within labour levels. Model has been developed considering a manufacturer having several product types, which the maximum types are N, along a total time period of T. Results: Industrial case study based on Malaysia is presented to test and to validate the developed linear programming model for aggregate production planning. Conclusion: The model development is fit under stable environment conditions. Overall it can be recommended to adapt the proven linear programming model to production planning of Malaysian flat panel display industry.

Hydrodynamics with strength: scaling-invariant solutions for elastic-plastic cavity expansion models

NASA Astrophysics Data System (ADS)

Albright, Jason; Ramsey, Scott; Baty, Roy

2017-11-01

Spherical cavity expansion (SCE) models are used to describe idealized detonation and high-velocity impact in a variety of materials. The common theme in SCE models is the presence of a pressure-driven cavity or void within a domain comprised of plastic and elastic response sub-regions. In past work, the yield criterion characterizing material strength in the plastic sub-region is usually taken for granted and assumed to take a known functional form restrictive to certain classes of materials, e.g. ductile metals or brittle geologic materials. Our objective is to systematically determine a general functional form for the yield criterion under the additional requirement that the SCE admits a similarity solution. Solutions determined under this additional requirement have immediate implications toward development of new compressible flow algorithm verification test problems. However, more importantly, these results also provide novel insight into modeling the yield criteria from the perspective of hydrodynamic scaling.

Folding and stability of helical bundle proteins from coarse-grained models.

PubMed

Kapoor, Abhijeet; Travesset, Alex

2013-07-01

We develop a coarse-grained model where solvent is considered implicitly, electrostatics are included as short-range interactions, and side-chains are coarse-grained to a single bead. The model depends on three main parameters: hydrophobic, electrostatic, and side-chain hydrogen bond strength. The parameters are determined by considering three level of approximations and characterizing the folding for three selected proteins (training set). Nine additional proteins (containing up to 126 residues) as well as mutated versions (test set) are folded with the given parameters. In all folding simulations, the initial state is a random coil configuration. Besides the native state, some proteins fold into an additional state differing in the topology (structure of the helical bundle). We discuss the stability of the native states, and compare the dynamics of our model to all atom molecular dynamics simulations as well as some general properties on the interactions governing folding dynamics. Copyright © 2013 Wiley Periodicals, Inc.

The Interrelations Between Internalized Homophobia, Depressive Symptoms, and Suicidal Ideation Among Australian Gay Men, Lesbians, and Bisexual Women.

PubMed

McLaren, Suzanne

2016-01-01

Internalized homophobia has been linked to depression among gay men, lesbians, and bisexuals. Relatively little research has investigated the link between internalized homophobia and suicidal thoughts and behaviors. The current research investigated the interrelations among internalized homophobia, depressive symptoms, and suicidal ideation by testing additive, mediation, and moderation models. Self-identified Australian gay men (n = 360), lesbians (n = 444), and bisexual women (n = 114) completed the Internalized Homophobia Scale, the Center for Epidemiological Studies Depression Scale, and the suicide subscale of the General Health Questionnaire. Results supported the additive and partial mediation models for gay men and the mediation and moderation models for lesbians. None of the models were supported for bisexual women. The findings imply that clinicians should focus on reducing internalized homophobia and depressive symptoms among gay men and lesbians, and depressive symptoms among bisexual women, to reduce suicidal ideation.

Effect of canard position and wing leading-edge flap deflection on wing buffet at transonic speeds

NASA Technical Reports Server (NTRS)

Gloss, B. B.; Henderson, W. P.; Huffman, J. K.

1974-01-01

A generalized wind-tunnel model, with canard and wing planform typical of highly maneuverable aircraft, was tested. The addition of a canard above the wing chord plane, for the configuration with leading-edge flaps undeflected, produced substantially higher total configuration lift coefficients before buffet onset than the configuration with the canard off and leading-edge flaps undeflected. The wing buffet intensity was substantially lower for the canard-wing configuration than the wing-alone configuration. The low-canard configuration generally displayed the poorest buffet characteristics. Deflecting the wing leading-edge flaps substantially improved the wing buffet characteristics for canard-off configurations. The addition of the high canard did not appear to substantially improve the wing buffet characteristics of the wing with leading-edge flaps deflected.

Use of a Generalized Additive Model to Investigate Key Abiotic Factors Affecting Microcystin Cellular Quotas in Heavy Bloom Areas of Lake Taihu

PubMed Central

Tao, Min; Xie, Ping; Chen, Jun; Qin, Boqiang; Zhang, Dawen; Niu, Yuan; Zhang, Meng; Wang, Qing; Wu, Laiyan

2012-01-01

Lake Taihu is the third largest freshwater lake in China and is suffering from serious cyanobacterial blooms with the associated drinking water contamination by microcystin (MC) for millions of citizens. So far, most studies on MCs have been limited to two small bays, while systematic research on the whole lake is lacking. To explain the variations in MC concentrations during cyanobacterial bloom, a large-scale survey at 30 sites across the lake was conducted monthly in 2008. The health risks of MC exposure were high, especially in the northern area. Both Microcystis abundance and MC cellular quotas presented positive correlations with MC concentration in the bloom seasons, suggesting that the toxic risks during Microcystis proliferations were affected by variations in both Microcystis density and MC production per Microcystis cell. Use of a powerful predictive modeling tool named generalized additive model (GAM) helped visualize significant effects of abiotic factors related to carbon fixation and proliferation of Microcystis (conductivity, dissolved inorganic carbon (DIC), water temperature and pH) on MC cellular quotas from recruitment period of Microcystis to the bloom seasons, suggesting the possible use of these factors, in addition to Microcystis abundance, as warning signs to predict toxic events in the future. The interesting relationship between macrophytes and MC cellular quotas of Microcystis (i.e., high MC cellular quotas in the presence of macrophytes) needs further investigation. PMID:22384128

Multi-allelic haplotype model based on genetic partition for genomic prediction and variance component estimation using SNP markers.

PubMed

Da, Yang

2015-12-18

The amount of functional genomic information has been growing rapidly but remains largely unused in genomic selection. Genomic prediction and estimation using haplotypes in genome regions with functional elements such as all genes of the genome can be an approach to integrate functional and structural genomic information for genomic selection. Towards this goal, this article develops a new haplotype approach for genomic prediction and estimation. A multi-allelic haplotype model treating each haplotype as an 'allele' was developed for genomic prediction and estimation based on the partition of a multi-allelic genotypic value into additive and dominance values. Each additive value is expressed as a function of h - 1 additive effects, where h = number of alleles or haplotypes, and each dominance value is expressed as a function of h(h - 1)/2 dominance effects. For a sample of q individuals, the limit number of effects is 2q - 1 for additive effects and is the number of heterozygous genotypes for dominance effects. Additive values are factorized as a product between the additive model matrix and the h - 1 additive effects, and dominance values are factorized as a product between the dominance model matrix and the h(h - 1)/2 dominance effects. Genomic additive relationship matrix is defined as a function of the haplotype model matrix for additive effects, and genomic dominance relationship matrix is defined as a function of the haplotype model matrix for dominance effects. Based on these results, a mixed model implementation for genomic prediction and variance component estimation that jointly use haplotypes and single markers is established, including two computing strategies for genomic prediction and variance component estimation with identical results. The multi-allelic genetic partition fills a theoretical gap in genetic partition by providing general formulations for partitioning multi-allelic genotypic values and provides a haplotype method based on the quantitative genetics model towards the utilization of functional and structural genomic information for genomic prediction and estimation.

Impact of acute care surgery to departmental productivity.

PubMed

Barnes, Stephen L; Cooper, Christopher J; Coughenour, Jeffrey P; MacIntyre, Allan D; Kessel, James W

2011-10-01

The face of trauma surgery is rapidly evolving with a paradigm shift toward acute care surgery (ACS). The formal development of ACS has been viewed by some general surgeons as a threat to their practice. We sought to evaluate the impact of a new division of ACS to both departmental productivity and provider satisfaction at a University Level I Trauma Center. Two-year retrospective analysis of annual work relative value unit (wRVU) productivity, operative volume, and FTEs before and after establishment of an ACS division at a University Level I trauma center. Provider satisfaction was measured using a 10-point scale. Analysis completed using Microsoft Excel with a p value less than 0.05 significant. The change to an ACS model resulted in a 94% increase in total wRVU production (78% evaluation and management, 122% operative; p<0.05) for ACS, whereas general surgery wRVU production increased 8% (-15% evaluation and management, 14% operative; p<0.05). Operative productivity was substantial after transition to ACS, with 129% and 44% increases (p<0.05) in operative and elective case load, respectively. Decline in overall general surgery operative volume was attributed to reduction in emergent cases. Establishment of the ACS model necessitated one additional FTE. Job satisfaction substantially improved with the ACS model while allowing general surgery a more focused practice. The ACS practice model significantly enhances provider productivity and job satisfaction when compared with trauma alone. Fears of a productivity impact to the nontrauma general surgeon were not realized.

Failed reciprocity in close social relationships and health: findings from the Whitehall II study.

PubMed

Chandola, Tarani; Marmot, Michael; Siegrist, Johannes

2007-10-01

To extend the model of effort-reward imbalance at work to close and more general social relationships and test the associations with different measures of health. Lack of reciprocity at work is associated with poorer health in a number of studies. However, few studies have analysed the effect of nonreciprocity in other kinds of social relationships on health. The Whitehall II Study is an ongoing prospective study of British civil servants (n=10308 at baseline in 1985-88). Cross-sectional data from the latest phase (7, n=6944 in 2002-04) were used in the analyses. The main exposure was a questionnaire measuring nonreciprocal social relations in partnership, parent-children, and general trusting relationships. Health measures included the SF-36 mental and physical component scores, General Health Questionnaire-30 depression subscale, Jenkins' Sleep disturbance questionnaire, and the Rose Angina questionnaire. Logistic and linear regression models were analysed, adjusted for potential confounders, and mediators of the association. Lack of reciprocity is associated with all measures of poorer health. This association attenuates after adjustment for previous health and additional confounders and mediators but remains significant in a majority of models. Negative social support from a close person is independently associated with reduced health, but adjusting for this effect does not eliminate the association of nonreciprocity with poor health. The effort-reward imbalance at work model has been extended to close and more general social relationships. Lack of reciprocity in partnership, parent-children and general trusting relationships is associated with poorer health.

Generalized noise terms for the quantized fluctuational electrodynamics

NASA Astrophysics Data System (ADS)

Partanen, Mikko; Häyrynen, Teppo; Tulkki, Jukka; Oksanen, Jani

2017-03-01

The quantization of optical fields in vacuum has been known for decades, but extending the field quantization to lossy and dispersive media in nonequilibrium conditions has proven to be complicated due to the position-dependent electric and magnetic responses of the media. In fact, consistent position-dependent quantum models for the photon number in resonant structures have only been formulated very recently and only for dielectric media. Here we present a general position-dependent quantized fluctuational electrodynamics (QFED) formalism that extends the consistent field quantization to describe the photon number also in the presence of magnetic field-matter interactions. It is shown that the magnetic fluctuations provide an additional degree of freedom in media where the magnetic coupling to the field is prominent. Therefore, the field quantization requires an additional independent noise operator that is commuting with the conventional bosonic noise operator describing the polarization current fluctuations in dielectric media. In addition to allowing the detailed description of field fluctuations, our methods provide practical tools for modeling optical energy transfer and the formation of thermal balance in general dielectric and magnetic nanodevices. We use QFED to investigate the magnetic properties of microcavity systems to demonstrate an example geometry in which it is possible to probe fields arising from the electric and magnetic source terms. We show that, as a consequence of the magnetic Purcell effect, the tuning of the position of an emitter layer placed inside a vacuum cavity can make the emissivity of a magnetic emitter to exceed the emissivity of a corresponding electric emitter.

Simultaneous Spectrophotometric Determination of Rifampicin, Isoniazid and Pyrazinamide in a Single Step

PubMed Central

Asadpour-Zeynali, Karim; Saeb, Elhameh

2016-01-01

Three antituberculosis medications are investigated in this work consist of rifampicin, isoniazid and pyrazinamide. The ultra violet (UV) spectra of these compounds are overlapped, thus use of suitable chemometric methods are helpful for simultaneous spectrophotometric determination of them. A generalized version of net analyte signal standard addition method (GNASSAM) was used for determination of three antituberculosis medications as a model system. In generalized net analyte signal standard addition method only one standard solution was prepared for all analytes. This standard solution contains a mixture of all analytes of interest, and the addition of such solution to sample, causes increases in net analyte signal of each analyte which are proportional to the concentrations of analytes in added standards solution. For determination of concentration of each analyte in some synthetic mixtures, the UV spectra of pure analytes and each sample were recorded in the range of 210 nm-550 nm. The standard addition procedure was performed for each sample and the UV spectrum was recorded after each addition and finally the results were analyzed by net analyte signal method. Obtained concentrations show acceptable performance of GNASSAM in these cases. PMID:28243267

Supersonic dynamic stability characteristics of the test technique demonstrator NASP configuration

NASA Technical Reports Server (NTRS)

Dress, David A.; Boyden, Richmond P.; Cruz, Christopher I.

1992-01-01

Wind tunnel tests of a National Aero-Space Plane (NASP) configuration were conducted in both test sections of the Langley Unitary Plan Wind Tunnel. The model used is a Langley designed blended body NASP configuration. Dynamic stability characteristics were measured on this configuration at Mach numbers of 2.0, 2.5, 3.5, and 4.5. In addition to tests of the baseline configuration, component buildup tests were conducted. The test results show that the baseline configuration generally has positive damping about all three axes with only isolated exceptions. In addition, there was generally good agreement between the in-pulse dynamic parameters and the corresponding static data which were measured during another series of tests in the Unitary Plan Wind Tunnel. Also included are comparisons of the experimental damping parameters with results from the engineering predictive code APAS (Aerodynamic Preliminary Analysis System). These comparisons show good agreement at low angles of attack; however, the comparisons are generally not as good at the higher angles of attack.

A general circulation model study of atmospheric carbon monoxide

NASA Technical Reports Server (NTRS)

Pinto, J. P.; Rind, D.; Russell, G. L.; Lerner, J. A.; Hansen, J. E.; Yung, Y. L.; 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 to the 15th g/yr, in addition to sources from incomplete combustion of fossil fuels and oxidation of methane. The globally averaged OH concentration calculated in the model is 750,000/cu cm. Models that calculate globally averaged OH concentrations much lower than this 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.

Interplay between inhibited transport and reaction in nanoporous materials

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

Ackerman, David Michael

2013-01-01

This work presents a detailed formulation of reaction and diffusion dynamics of molecules in confined pores such as mesoporous silica and zeolites. A general reaction-diffusion model and discrete Monte Carlo simulations are presented. Both transient and steady state behavior is covered. Failure of previous mean-field models for these systems is explained and discussed. A coarse-grained, generalized hydrodynamic model is developed that accurately captures the interplay between reaction and restricted transport in these systems. This method incorporates the non-uniform chemical diffusion behavior present in finite pores with multi-component diffusion. Two methods of calculating these diffusion values are developed: a random walkmore » based approach and a driven diffusion model based on an extension of Fick's law. The effects of reaction, diffusion, pore length, and catalytic site distribution are investigated. In addition to strictly single file motion, quasi-single file diffusion is incorporated into the model to match a range of experimental systems. The connection between these experimental systems and model parameters is made through Langevin dynamics modeling of particles in confined pores.« less

General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models

USGS Publications Warehouse

Miller, David A.W.

2012-01-01

Sensitivity analysis is a useful tool for the study of ecological models that has many potential applications for patch occupancy modeling. Drawing from the rich foundation of existing methods for Markov chain models, I demonstrate new methods for sensitivity analysis of the equilibrium state dynamics of occupancy models. Estimates from three previous studies are used to illustrate the utility of the sensitivity calculations: a joint occupancy model for a prey species, its predators, and habitat used by both; occurrence dynamics from a well-known metapopulation study of three butterfly species; and Golden Eagle occupancy and reproductive dynamics. I show how to deal efficiently with multistate models and how to calculate sensitivities involving derived state variables and lower-level parameters. In addition, I extend methods to incorporate environmental variation by allowing for spatial and temporal variability in transition probabilities. The approach used here is concise and general and can fully account for environmental variability in transition parameters. The methods can be used to improve inferences in occupancy studies by quantifying the effects of underlying parameters, aiding prediction of future system states, and identifying priorities for sampling effort.

Implications of new petrographic analysis for the Olmec "mother culture" model.

PubMed

Flannery, Kent V; Balkansky, Andrew K; Feinman, Gary M; Grove, David C; Marcus, Joyce; Redmond, Elsa M; Reynolds, Robert G; Sharer, Robert J; Spencer, Charles S; Yaeger, Jason

2005-08-09

Petrographic analysis of Formative Mexican ceramics by J. B. Stoltman et al. (see the companion piece in this issue of PNAS) refutes a recent model of Olmec "one-way" trade. In this paper, we address the model's more fundamental problems of sampling bias, anthropological implausibility, and logical non sequiturs. No bridging argument exists to link motifs on pottery to the social, political, and religious institutions of the Olmec. In addition, the model of unreciprocated exchange is implausible, given everything that the anthropological and ethnohistoric records tell us about non-Western societies of that general sociopolitical level.

System maintenance manual for master modeling of aerodynamic surfaces by three-dimensional explicit representation

NASA Technical Reports Server (NTRS)

Gibson, A. F.

1983-01-01

A system of computer programs has been developed to model general three-dimensional surfaces. Surfaces are modeled as sets of parametric bicubic patches. There are also capabilities to transform coordinate to compute mesh/surface intersection normals, and to format input data for a transonic potential flow analysis. A graphical display of surface models and intersection normals is available. There are additional capabilities to regulate point spacing on input curves and to compute surface intersection curves. Internal details of the implementation of this system are explained, and maintenance procedures are specified.

A DGTD method for the numerical modeling of the interaction of light with nanometer scale metallic structures taking into account non-local dispersion effects

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

Schmitt, Nikolai; Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder; Scheid, Claire

2016-07-01

The interaction of light with metallic nanostructures is increasingly attracting interest because of numerous potential applications. Sub-wavelength metallic structures, when illuminated with a frequency close to the plasma frequency of the metal, present resonances that cause extreme local field enhancements. Exploiting the latter in applications of interest requires a detailed knowledge about the occurring fields which can actually not be obtained analytically. For the latter mentioned reason, numerical tools are thus an absolute necessity. The insight they provide is very often the only way to get a deep enough understanding of the very rich physics at play. For the numericalmore » modeling of light-structure interaction on the nanoscale, the choice of an appropriate material model is a crucial point. Approaches that are adopted in a first instance are based on local (i.e. with no interaction between electrons) dispersive models, e.g. Drude or Drude–Lorentz models. From the mathematical point of view, when a time-domain modeling is considered, these models lead to an additional system of ordinary differential equations coupled to Maxwell's equations. However, recent experiments have shown that the repulsive interaction between electrons inside the metal makes the response of metals intrinsically non-local and that this effect cannot generally be overlooked. Technological achievements have enabled the consideration of metallic structures in a regime where such non-localities have a significant influence on the structures' optical response. This leads to an additional, in general non-linear, system of partial differential equations which is, when coupled to Maxwell's equations, significantly more difficult to treat. Nevertheless, dealing with a linearized non-local dispersion model already opens the route to numerous practical applications of plasmonics. In this work, we present a Discontinuous Galerkin Time-Domain (DGTD) method able to solve the system of Maxwell's equations coupled to a linearized non-local dispersion model relevant to plasmonics. While the method is presented in the general 3D case, numerical results are given for 2D simulation settings.« less

A revised linear ozone photochemistry parameterization for use in transport and general circulation models: multi-annual simulations

NASA Astrophysics Data System (ADS)

Cariolle, D.; Teyssèdre, H.

2007-05-01

This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2-D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory work. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the solution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000-2004. Overall, the results from the two versions show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small, of the order of 10%. The model also reproduces fairly well the polar ozone variability, notably the formation of "ozone holes" in the Southern Hemisphere with amplitudes and a seasonal evolution that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone content inside the polar vortex of the Southern Hemisphere over longer periods in spring time. It is concluded that for the study of climate scenarios or the assimilation of ozone data, the present parameterization gives a valuable alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models.

Assessing the cost-effectiveness of a routine versus an extensive laboratory work-up in the diagnosis of anaemia in Dutch general practice.

PubMed

Kip, Michelle Ma; Schop, Annemarie; Stouten, Karlijn; Dekker, Soraya; Dinant, Geert-Jan; Koffijberg, Hendrik; Bindels, Patrick Je; IJzerman, Maarten J; Levin, Mark-David; Kusters, Ron

2018-01-01

Background Establishing the underlying cause of anaemia in general practice is a diagnostic challenge. Currently, general practitioners individually determine which laboratory tests to request (routine work-up) in order to diagnose the underlying cause. However, an extensive work-up (consisting of 14 tests) increases the proportion of patients correctly diagnosed. This study investigates the cost-effectiveness of this extensive work-up. Methods A decision-analytic model was developed, incorporating all societal costs from the moment a patient presents to a general practitioner with symptoms suggestive of anaemia (aged ≥ 50 years), until the patient was (correctly) diagnosed and treated in primary care, or referred to (and diagnosed in) secondary care. Model inputs were derived from an online survey among general practitioners, expert estimates and published data. The primary outcome measure was expressed as incremental cost per additional patient diagnosed with the correct underlying cause of anaemia in either work-up. Results The probability of general practitioners diagnosing the correct underlying cause increased from 49.6% (95% CI: 44.8% to 54.5%) in the routine work-up to 56.0% (95% CI: 51.2% to 60.8%) in the extensive work-up (i.e. +6.4% [95% CI: -0.6% to 13.1%]). Costs are expected to increase slightly from €842/patient (95% CI: €704 to €994) to €845/patient (95% CI: €711 to €994), i.e. +€3/patient (95% CI: €-35 to €40) in the extensive work-up, indicating incremental costs of €43 per additional patient correctly diagnosed. Conclusions The extensive laboratory work-up is more effective for diagnosing the underlying cause of anaemia by general practitioners, at a minimal increase in costs. As accompanying benefits in terms of quality of life and reduced productivity losses could not be captured in this analysis, the extensive work-up is likely cost-effective.

NASA Handbook for Models and Simulations: An Implementation Guide for NASA-STD-7009

NASA Technical Reports Server (NTRS)

Steele, Martin J.

2013-01-01

The purpose of this Handbook is to provide technical information, clarification, examples, processes, and techniques to help institute good modeling and simulation practices in the National Aeronautics and Space Administration (NASA). As a companion guide to NASA-STD- 7009, Standard for Models and Simulations, this Handbook provides a broader scope of information than may be included in a Standard and promotes good practices in the production, use, and consumption of NASA modeling and simulation products. NASA-STD-7009 specifies what a modeling and simulation activity shall or should do (in the requirements) but does not prescribe how the requirements are to be met, which varies with the specific engineering discipline, or who is responsible for complying with the requirements, which depends on the size and type of project. A guidance document, which is not constrained by the requirements of a Standard, is better suited to address these additional aspects and provide necessary clarification. This Handbook stems from the Space Shuttle Columbia Accident Investigation (2003), which called for Agency-wide improvements in the "development, documentation, and operation of models and simulations"' that subsequently elicited additional guidance from the NASA Office of the Chief Engineer to include "a standard method to assess the credibility of the models and simulations."2 General methods applicable across the broad spectrum of model and simulation (M&S) disciplines were sought to help guide the modeling and simulation processes within NASA and to provide for consistent reporting ofM&S activities and analysis results. From this, the standardized process for the M&S activity was developed. The major contents of this Handbook are the implementation details of the general M&S requirements ofNASA-STD-7009, including explanations, examples, and suggestions for improving the credibility assessment of an M&S-based analysis.

Feature Extraction of Event-Related Potentials Using Wavelets: An Application to Human Performance Monitoring

NASA Technical Reports Server (NTRS)

Trejo, Leonard J.; Shensa, Mark J.; Remington, Roger W. (Technical Monitor)

1998-01-01

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many f ree parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation,-, algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance.

Feature extraction of event-related potentials using wavelets: an application to human performance monitoring

NASA Technical Reports Server (NTRS)

Trejo, L. J.; Shensa, M. J.

1999-01-01

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many free parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance. Copyright 1999 Academic Press.

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

PubMed

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.

MULTI: a shared memory approach to cooperative molecular modeling.

PubMed

Darden, T; Johnson, P; Smith, H

1991-03-01

A general purpose molecular modeling system, MULTI, based on the UNIX shared memory and semaphore facilities for interprocess communication is described. In addition to the normal querying or monitoring of geometric data, MULTI also provides processes for manipulating conformations, and for displaying peptide or nucleic acid ribbons, Connolly surfaces, close nonbonded contacts, crystal-symmetry related images, least-squares superpositions, and so forth. This paper outlines the basic techniques used in MULTI to ensure cooperation among these specialized processes, and then describes how they can work together to provide a flexible modeling environment.

The NASTRAN user's manual (level 17.0)

NASA Technical Reports Server (NTRS)

1979-01-01

NASTRAN embodies a lumped element approach, wherein the distributed physical properties of a structure are represented by a model consisting of a finite number of idealized substructures or elements that are interconnected at a finite of grid points, to which loads are applied. All input and output data pertain to the idealized structural model. The general procedures for defining structural models are described and instructions are given for each of the bulk data cards and case control cards. Additional information on the case control cards and use of parameters is included for each rigid format.

Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: V. Predictive absorbability models.

PubMed

Langenbucher, Frieder

2007-08-01

This paper discusses Excel applications related to the prediction of drug absorbability from physicochemical constants. PHDISSOC provides a generalized model for pH profiles of electrolytic dissociation, water solubility, and partition coefficient. SKMODEL predicts drug absorbability, based on a log-log plot of water solubility and O/W partitioning; augmented by additional features such as electrolytic dissociation, melting point, and the dose administered. GIABS presents a mechanistic model of g.i. drug absorption. BIODATCO presents a database compiling relevant drug data to be used for quantitative predictions.

A Machine Learning Approach to Student Modeling.

DTIC Science & Technology

1984-05-01

machine learning , and describe ACN, a student modeling system that incorporates this approach. This system begins with a set of overly general rules, which it uses to search a problem space until it arrives at the same answer as the student. The ACM computer program then uses the solution path it has discovered to determine positive and negative instances of its initial rules, and employs a discrimination learning mechanism to place additional conditions on these rules. The revised rules will reproduce the solution path without search, and constitute a cognitive model of

Analytical properties of a three-compartmental dynamical demographic model

NASA Astrophysics Data System (ADS)

Postnikov, E. B.

2015-07-01

The three-compartmental demographic model by Korotaeyv-Malkov-Khaltourina, connecting population size, economic surplus, and education level, is considered from the point of view of dynamical systems theory. It is shown that there exist two integrals of motion, which enables the system to be reduced to one nonlinear ordinary differential equation. The study of its structure provides analytical criteria for the dominance ranges of the dynamics of Malthus and Kremer. Additionally, the particular ranges of parameters enable the derived general ordinary differential equations to be reduced to the models of Gompertz and Thoularis-Wallace.

The Effect of Enhanced Diabatic Heating on Stratospheric Circulation. Degree awarded by Michigan University, 1997.

NASA Technical Reports Server (NTRS)

Kleb, Mary M.

1997-01-01

The objective of this research focuses on the stratospheric dynamical response to the increase in aerosol loading and subsequent enhanced diabatic heating resulting from the eruption of Mt. Pinatubo. The Langley research Center three dimensional general circulation model and modifications made to that model for this study are described (addition of hydrogen fluoride tracer and diabatic heating enhancement). Unperturbed hydrogen fluoride distribution is compared to the hydrogen fluoride distribution measured by HALOE. A comparison of control and perturbed model runs is presented.

Susceptible-infected-recovered epidemics in random networks with population awareness

NASA Astrophysics Data System (ADS)

Wu, Qingchu; Chen, Shufang

2017-10-01

The influence of epidemic information-based awareness on the spread of infectious diseases on networks cannot be ignored. Within the effective degree modeling framework, we discuss the susceptible-infected-recovered model in complex networks with general awareness and general degree distribution. By performing the linear stability analysis, the conditions of epidemic outbreak can be deduced and the results of the previous research can be further expanded. Results show that the local awareness can suppress significantly the epidemic spreading on complex networks via raising the epidemic threshold and such effects are closely related to the formulation of awareness functions. In addition, our results suggest that the recovered information-based awareness has no effect on the critical condition of epidemic outbreak.

Error suppression for Hamiltonian quantum computing in Markovian environments

NASA Astrophysics Data System (ADS)

Marvian, Milad; Lidar, Daniel A.

2017-03-01

Hamiltonian quantum computing, such as the adiabatic and holonomic models, can be protected against decoherence using an encoding into stabilizer subspace codes for error detection and the addition of energy penalty terms. This method has been widely studied since it was first introduced by Jordan, Farhi, and Shor (JFS) in the context of adiabatic quantum computing. Here, we extend the original result to general Markovian environments, not necessarily in Lindblad form. We show that the main conclusion of the original JFS study holds under these general circumstances: Assuming a physically reasonable bath model, it is possible to suppress the initial decay out of the encoded ground state with an energy penalty strength that grows only logarithmically in the system size, at a fixed temperature.

Minority stress and college persistence attitudes among African American, Asian American, and Latino students: perception of university environment as a mediator.

PubMed

Wei, Meifen; Ku, Tsun-Yao; Liao, Kelly Yu-Hsin

2011-04-01

We examined whether perception of university environment mediated the association between minority status stress and college persistence attitudes after controlling for perceived general stress. Participants were 160 Asian American, African American, and Latino students who attended a predominantly White university. Results of a path model analysis showed that university environment was a significant mediator for the association between minority status stress and college persistence attitudes. Additionally, minority status stress was distinct from perceived general stress. Finally, the results from a multiple-group comparison indicated that the magnitude of the mediation effect was invariant across Asian American, African American, and Latino college students, thus supporting the generalizability of the mediation model.

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

Code of Federal Regulations, 2014 CFR

2014-04-01

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

Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure.

PubMed

Yung, Yiu-Fai; Browne, Michael W; Zhang, Wei

2015-02-01

This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple-group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy-to-use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large. © 2014 The British Psychological Society.

GEOS-5 Chemistry Transport Model User's Guide

NASA Technical Reports Server (NTRS)

Kouatchou, J.; Molod, A.; Nielsen, J. E.; Auer, B.; Putman, W.; Clune, T.

2015-01-01

The Goddard Earth Observing System version 5 (GEOS-5) General Circulation Model (GCM) makes use of the Earth System Modeling Framework (ESMF) to enable model configurations with many functions. One of the options of the GEOS-5 GCM is the GEOS-5 Chemistry Transport Model (GEOS-5 CTM), which is an offline simulation of chemistry and constituent transport driven by a specified meteorology and other model output fields. This document describes the basic components of the GEOS-5 CTM, and is a user's guide on to how to obtain and run simulations on the NCCS Discover platform. In addition, we provide information on how to change the model configuration input files to meet users' needs.

General personality and psychopathology in referred and nonreferred children and adolescents: an investigation of continuity, pathoplasty, and complication models.

PubMed

De Bolle, Marleen; Beyers, Wim; De Clercq, Barbara; De Fruyt, Filip

2012-11-01

This study investigated the continuity, pathoplasty, and complication models as plausible explanations for personality-psychopathology relations in a combined sample of community (n = 571) and referred (n = 146) children and adolescents. Multivariate structural equation modeling was used to examine the structural relations between latent personality and psychopathology change across a 2-year period. Item response theory models were fitted as an additional test of the continuity hypothesis. Even after correcting for item overlap, the results provided strong support for the continuity model, demonstrating that personality and psychopathology displayed dynamic change patterns across time. Item response theory models further supported the continuity conceptualization for understanding the association between internalizing problems and emotional stability and extraversion as well as between externalizing problems and benevolence and conscientiousness. In addition to the continuity model, particular personality and psychopathology combinations provided evidence for the pathoplasty and complication models. The theoretical and practical implications of these results are discussed, and suggestions for future research are provided. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Variable Selection with Prior Information for Generalized Linear Models via the Prior LASSO Method.

PubMed

Jiang, Yuan; He, Yunxiao; Zhang, Heping

LASSO is a popular statistical tool often used in conjunction with generalized linear models that can simultaneously select variables and estimate parameters. When there are many variables of interest, as in current biological and biomedical studies, the power of LASSO can be limited. Fortunately, so much biological and biomedical data have been collected and they may contain useful information about the importance of certain variables. This paper proposes an extension of LASSO, namely, prior LASSO (pLASSO), to incorporate that prior information into penalized generalized linear models. The goal is achieved by adding in the LASSO criterion function an additional measure of the discrepancy between the prior information and the model. For linear regression, the whole solution path of the pLASSO estimator can be found with a procedure similar to the Least Angle Regression (LARS). Asymptotic theories and simulation results show that pLASSO provides significant improvement over LASSO when the prior information is relatively accurate. When the prior information is less reliable, pLASSO shows great robustness to the misspecification. We illustrate the application of pLASSO using a real data set from a genome-wide association study.

Comparative analysis of long-term chlorophyll data with generalized additive model - San Francisco Bay and St. Lucie Estuary

EPA Science Inventory

The health of estuarine ecosystems is often influenced by hydraulic and nutrient loading from upstream watersheds. We examined four decades of monitoring data of nutrient export into the Indian River Lagoon and San Francisco Bay, both of which have received considerable attentio...

Danger and Usefulness Are Detected Early in Auditory Lexical Processing: Evidence from Electroencephalography

ERIC Educational Resources Information Center

Kryuchkova, Tatiana; Tucker, Benjamin V.; Wurm, Lee H.; Baayen, R. Harald

2012-01-01

Visual emotionally charged stimuli have been shown to elicit early electrophysiological responses (e.g., Ihssen, Heim, & Keil, 2007; Schupp, Junghofer, Weike, & Hamm, 2003; Stolarova, Keil, & Moratti, 2006). We presented isolated words to listeners, and observed, using generalized additive modeling, oscillations in the upper part of the delta…

Brief Report: Diminishing Geographic Variability in Autism Spectrum Disorders over Time?

ERIC Educational Resources Information Center

Hoffman, Kate; Vieira, Veronica M.; Daniels, Julie L.

2014-01-01

We investigated differences in the geographic distribution of autism spectrum disorders (ASD) over time in central North Carolina with data from the Autism and Developmental Disabilities Monitoring Network. Using generalized additive models and geographic information systems we produced maps of ASD risk in 2002-2004 and 2006-2008. Overall the risk…

Assessing the Chances of Success: Naive Statistics versus Kind Experience

ERIC Educational Resources Information Center

Hogarth, Robin M.; Mukherjee, Kanchan; Soyer, Emre

2013-01-01

Additive integration of information is ubiquitous in judgment and has been shown to be effective even when multiplicative rules of probability theory are prescribed. We explore the generality of these findings in the context of estimating probabilities of success in contests. We first define a normative model of these probabilities that takes…

Mining and Modeling Real-World Networks: Patterns, Anomalies, and Tools

ERIC Educational Resources Information Center

Akoglu, Leman

2012-01-01

Large real-world graph (a.k.a network, relational) data are omnipresent, in online media, businesses, science, and the government. Analysis of these massive graphs is crucial, in order to extract descriptive and predictive knowledge with many commercial, medical, and environmental applications. In addition to its general structure, knowing what…

On Synchronization Primitive Systems.

DTIC Science & Technology

The report studies the question: what synchronization primitive should be used to handle inter-process communication. A formal model is presented...between these synchronization primitives. Although only four synchronization primitives are compared, the general methods can be used to compare other... synchronization primitives. Moreover, in the definitions of these synchronization primitives, conditional branches are explicitly allowed. In addition

“Skill of Generalized Additive Model to Detect PM2.5 Health Signal in the Presence of Confounding Variables”

EPA Science Inventory

Summary. Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables of interest (and...

Some Additional Lessons from the Wechsler Scales: A Rejoinder to Kaufman and Keith.

ERIC Educational Resources Information Center

Macmann, Gregg M.; Barnett, David W.

1994-01-01

Reacts to previous arguments regarding verbal and performance constructs of Wechsler Scales. Contends that general factor model is more plausible representation of data for these scales. Suggests issue is moot when considered in regards to practical applications. Supports analysis of needed skills and instructional environments in educational…

Integration of SAR and DEM data: Geometrical considerations

NASA Technical Reports Server (NTRS)

Kropatsch, Walter G.

1991-01-01

General principles for integrating data from different sources are derived from the experience of registration of SAR images with digital elevation models (DEM) data. The integration consists of establishing geometrical relations between the data sets that allow us to accumulate information from both data sets for any given object point (e.g., elevation, slope, backscatter of ground cover, etc.). Since the geometries of the two data are completely different they cannot be compared on a pixel by pixel basis. The presented approach detects instances of higher level features in both data sets independently and performs the matching at the high level. Besides the efficiency of this general strategy it further allows the integration of additional knowledge sources: world knowledge and sensor characteristics are also useful sources of information. The SAR features layover and shadow can be detected easily in SAR images. An analytical method to find such regions also in a DEM needs in addition the parameters of the flight path of the SAR sensor and the range projection model. The generation of the SAR layover and shadow maps is summarized and new extensions to this method are proposed.

Assessment of an Explicit Algebraic Reynolds Stress Model

NASA Technical Reports Server (NTRS)

Carlson, Jan-Renee

2005-01-01

This study assesses an explicit algebraic Reynolds stress turbulence model in the in the three-dimensional Reynolds averaged Navier-Stokes (RANS) solver, ISAAC (Integrated Solution Algorithm for Arbitrary Con gurations). Additionally, it compares solutions for two select configurations between ISAAC and the RANS solver PAB3D. This study compares with either direct numerical simulation data, experimental data, or empirical models for several different geometries with compressible, separated, and high Reynolds number flows. In general, the turbulence model matched data or followed experimental trends well, and for the selected configurations, the computational results of ISAAC closely matched those of PAB3D using the same turbulence model.

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to that of the complex model including epistatic effects. Conclusions This simulation study showed that the fBayesB approach is convenient for genetic value prediction. Jointly estimating additive and non-additive effects (especially dominance) has reasonable impact on the accuracy of prediction and the proportion of genetic variation assigned to the additive genetic source. PMID:21867519

Inter-hospital transfer is associated with increased mortality and costs in severe sepsis and septic shock: An instrumental variables approach.

PubMed

Mohr, Nicholas M; Harland, Karisa K; Shane, Dan M; Ahmed, Azeemuddin; Fuller, Brian M; Torner, James C

2016-12-01

The objective of this study was to evaluate the impact of regionalization on sepsis survival, to describe the role of inter-hospital transfer in rural sepsis care, and to measure the cost of inter-hospital transfer in a predominantly rural state. Observational case-control study using statewide administrative claims data from 2005 to 2014 in a predominantly rural Midwestern state. Mortality and marginal costs were estimated with multivariable generalized estimating equations models and with instrumental variables models. A total of 18 246 patients were included, of which 59% were transferred between hospitals. Transferred patients had higher mortality and longer hospital length-of-stay than non-transferred patients. Using a multivariable generalized estimating equations (GEE) model to adjust for potentially confounding factors, inter-hospital transfer was associated with increased mortality (aOR 1.7, 95% CI 1.5-1.9). Using an instrumental variables model, transfer was associated with a 9.2% increased risk of death. Transfer was associated with additional costs of $6897 (95% CI $5769-8024). Even when limiting to only those patients who received care in the largest hospitals, transfer was still associated with $5167 (95% CI $3696-6638) in additional cost. The majority of rural sepsis patients are transferred, and these transferred patients have higher mortality and significantly increased cost of care. Copyright © 2016 Elsevier Inc. All rights reserved.

Exact solutions of the Navier-Stokes equations generalized for flow in porous media

NASA Astrophysics Data System (ADS)

Daly, Edoardo; Basser, Hossein; Rudman, Murray

2018-05-01

Flow of Newtonian fluids in porous media is often modelled using a generalized version of the full non-linear Navier-Stokes equations that include additional terms describing the resistance to flow due to the porous matrix. Because this formulation is becoming increasingly popular in numerical models, exact solutions are required as a benchmark of numerical codes. The contribution of this study is to provide a number of non-trivial exact solutions of the generalized form of the Navier-Stokes equations for parallel flow in porous media. Steady-state solutions are derived in the case of flows in a medium with constant permeability along the main direction of flow and a constant cross-stream velocity in the case of both linear and non-linear drag. Solutions are also presented for cases in which the permeability changes in the direction normal to the main flow. An unsteady solution for a flow with velocity driven by a time-periodic pressure gradient is also derived. These solutions form a basis for validating computational models across a wide range of Reynolds and Darcy numbers.

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

PubMed

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.

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

Cembranos, Jose A.R.; Valcarcel, Jorge Gigante, E-mail: cembra@fis.ucm.es, E-mail: jorgegigante@ucm.es

We derive a new exact static and spherically symmetric vacuum solution in the framework of the Poincaré gauge field theory with dynamical massless torsion. This theory is built in such a form that allows to recover General Relativity when the first Bianchi identity of the model is fulfilled by the total curvature. The solution shows a Reissner-Nordström type geometry with a Coulomb-like curvature provided by the torsion field. It is also shown the existence of a generalized Reissner-Nordström-de Sitter solution when additional electromagnetic fields and/or a cosmological constant are coupled to gravity.

Generalized group field theories and quantum gravity transition amplitudes

NASA Astrophysics Data System (ADS)

Oriti, Daniele

2006-03-01

We construct a generalized formalism for group field theories, in which the domain of the field is extended to include additional proper time variables, as well as their conjugate mass variables. This formalism allows for different types of quantum gravity transition amplitudes in perturbative expansion, and we show how both causal spin foam models and the usual a-causal ones can be derived from it, within a sum over triangulations of all topologies. We also highlight the relation of the so-derived causal transition amplitudes with simplicial gravity actions.

Modelling Vulnerability and Range Shifts in Ant Communities Responding to Future Global Warming in Temperate Forests

PubMed Central

Kim, Sung-Soo; Chun, Jung Hwa; Park, Young-Seuk

2016-01-01

Global warming is likely leading to species’ distributional shifts, resulting in changes in local community compositions and diversity patterns. In this study, we applied species distribution models to evaluate the potential impacts of temperature increase on ant communities in Korean temperate forests, by testing hypotheses that 1) the risk of extinction of forest ant species would increase over time, and 2) the changes in species distribution ranges could drive upward movements of ant communities and further alter patterns of species richness. We sampled ant communities at 335 evenly distributed sites across South Korea and modelled the future distribution range for each species using generalized additive models. To account for spatial autocorrelation, autocovariate regressions were conducted prior to generalized additive models. Among 29 common ant species, 12 species were estimated to shrink their suitable geographic areas, whereas five species would benefit from future global warming. Species richness was highest at low altitudes in the current period, and it was projected to be highest at the mid-altitudes in the 2080s, resulting in an upward movement of 4.9 m yr−1. This altered the altitudinal pattern of species richness from a monotonic-decrease curve (common in temperate regions) to a bell-shaped curve (common in tropical regions). Overall, ant communities in temperate forests are vulnerable to the on-going global warming and their altitudinal movements are similar to other faunal communities. PMID:27504632

Diurnal Forcing of Planetary Atmospheres

NASA Technical Reports Server (NTRS)

Houben, Howard C.

1997-01-01

Much progress has been made on calculations of the Martian seasonal water cycle using the Mars Climate Model developed for this purpose. Two papers, documenting the model and the water transport results obtained with it have been published in the Journal of Geophysical Research - Planets. An additional paper describing results related to the evolution of the seasonal water cycle as a result of orbital changes was published in Advances in Space Research. Since that time, further studies have concentrated on the consequences of the soil adsorption required to match the observed water cycle and its relation to the stability of ground ice and other potential water reservoirs. Earth-related studies have concentrated on incorporating an efficient and realistic microphysical model into the Ames Stratospheric General Circulation Model used to simulate the spread of the ML Pinatubo and other volcanic clouds in the stratosphere. In addition, visualizations of the simulations are being incorporated into a video describing the UARS mission. A paper describing the new stratospheric aerosol microphysics package (and its consequences for volcanic cloud evolution) will be submitted in the near future. The paper will discuss the relative importance of condensation and coagulation to early particle growth and the separation of the cloud by sedimentation of the larger particles. A more general paper which highlights the observation that particle number densities did not increase dramatically after the ML Pinatubo eruption is planned. Simulations of atmospheric transport will be extended to include studies of terrestrial tropospheric tracers using the Fifth-Generation Penn State/NCAR Mesoscale Model.

Virulence as a model for interplanetary and interstellar colonization - parasitism or mutualism?

NASA Astrophysics Data System (ADS)

Starling, Jonathan; Forgan, Duncan H.

2014-01-01

In the light of current scientific assessments of human-induced climate change, we investigate an experimental model to inform how resource-use strategies may influence interplanetary and interstellar colonization by intelligent civilizations. In doing so, we seek to provide an additional aspect for refining the famed Fermi Paradox. The model described is necessarily simplistic, and the intent is to simply obtain some general insights to inform and inspire additional models. We model the relationship between an intelligent civilization and its host planet as symbiotic, where the relationship between the symbiont and the host species (the civilization and the planet's ecology, respectively) determines the fitness and ultimate survival of both organisms. We perform a series of Monte Carlo Realization simulations, where civilizations pursue a variety of different relationships/strategies with their host planet, from mutualism to parasitism, and can consequently `infect' other planets/hosts. We find that parasitic civilizations are generally less effective at survival than mutualist civilizations, provided that interstellar colonization is inefficient (the maximum velocity of colonization/infection is low). However, as the colonization velocity is increased, the strategy of parasitism becomes more successful, until they dominate the `population'. This is in accordance with predictions based on island biogeography and r/K selection theory. While heavily assumption dependent, we contend that this provides a fertile approach for further application of insights from theoretical ecology for extraterrestrial colonization - while also potentially offering insights for understanding the human-Earth relationship and the potential for extraterrestrial human colonization.

Estimating V̄s(30) (or NEHRP site classes) from shallow velocity models (depths < 30 m)

USGS Publications Warehouse

Boore, David M.

2004-01-01

The average velocity to 30 m [V??s(30)] is a widely used parameter for classifying sites to predict their potential to amplify seismic shaking. In many cases, however, models of shallow shear-wave velocities, from which V??s(30) can be computed, do not extend to 30 m. If the data for these cases are to be used, some method of extrapolating the velocities must be devised. Four methods for doing this are described here and are illustrated using data from 135 boreholes in California for which the velocity model extends to at least 30 m. Methods using correlations between shallow velocity and V??s(30) result in significantly less bias for shallow models than the simplest method of assuming that the lowermost velocity extends to 30 m. In addition, for all methods the percent of sites misclassified is generally less than 10% and falls to negligible values for velocity models extending to at least 25 m. Although the methods using correlations do a better job on average of estimating V??s(30), the simplest method will generally result in a lower value of V??s(30) and thus yield a more conservative estimate of ground motion [which generally increases as V??s(30) decreases].

A powerful and flexible approach to the analysis of RNA sequence count data.

PubMed

Zhou, Yi-Hui; Xia, Kai; Wright, Fred A

2011-10-01

A number of penalization and shrinkage approaches have been proposed for the analysis of microarray gene expression data. Similar techniques are now routinely applied to RNA sequence transcriptional count data, although the value of such shrinkage has not been conclusively established. If penalization is desired, the explicit modeling of mean-variance relationships provides a flexible testing regimen that 'borrows' information across genes, while easily incorporating design effects and additional covariates. We describe BBSeq, which incorporates two approaches: (i) a simple beta-binomial generalized linear model, which has not been extensively tested for RNA-Seq data and (ii) an extension of an expression mean-variance modeling approach to RNA-Seq data, involving modeling of the overdispersion as a function of the mean. Our approaches are flexible, allowing for general handling of discrete experimental factors and continuous covariates. We report comparisons with other alternate methods to handle RNA-Seq data. Although penalized methods have advantages for very small sample sizes, the beta-binomial generalized linear model, combined with simple outlier detection and testing approaches, appears to have favorable characteristics in power and flexibility. An R package containing examples and sample datasets is available at http://www.bios.unc.edu/research/genomic_software/BBSeq yzhou@bios.unc.edu; fwright@bios.unc.edu Supplementary data are available at Bioinformatics online.

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

PubMed Central

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

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

Nieves-Chinchilla, T.; Linton, M. G.; Hidalgo, M. A.

We present an analytical model to describe magnetic flux-rope topologies. When these structures are observed embedded in Interplanetary Coronal Mass Ejections (ICMEs) with a depressed proton temperature, they are called Magnetic Clouds (MCs). Our model extends the circular-cylindrical concept of Hidalgo et al. by introducing a general form for the radial dependence of the current density. This generalization provides information on the force distribution inside the flux rope in addition to the usual parameters of MC geometrical information and orientation. The generalized model provides flexibility for implementation in 3D MHD simulations. Here, we evaluate its performance in the reconstruction ofmore » MCs in in situ observations. Four Earth-directed ICME events, observed by the Wind spacecraft, are used to validate the technique. The events are selected from the ICME Wind list with the magnetic obstacle boundaries chosen consistently with the magnetic field and plasma in situ observations and with a new parameter (EPP, the Electron Pitch angle distribution Parameter) which quantifies the bidirectionally of the plasma electrons. The goodness of the fit is evaluated with a single correlation parameter to enable comparative analysis of the events. In general, at first glance, the model fits the selected events very well. However, a detailed analysis of events with signatures of significant compression indicates the need to explore geometries other than the circular-cylindrical. An extension of our current modeling framework to account for such non-circular CMEs will be presented in a forthcoming publication.« less

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

PubMed

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.

Restricted DCJ-indel model: sorting linear genomes with DCJ and indels

PubMed Central

2012-01-01

Background The double-cut-and-join (DCJ) is a model that is able to efficiently sort a genome into another, generalizing the typical mutations (inversions, fusions, fissions, translocations) to which genomes are subject, but allowing the existence of circular chromosomes at the intermediate steps. In the general model many circular chromosomes can coexist in some intermediate step. However, when the compared genomes are linear, it is more plausible to use the so-called restricted DCJ model, in which we proceed the reincorporation of a circular chromosome immediately after its creation. These two consecutive DCJ operations, which create and reincorporate a circular chromosome, mimic a transposition or a block-interchange. When the compared genomes have the same content, it is known that the genomic distance for the restricted DCJ model is the same as the distance for the general model. If the genomes have unequal contents, in addition to DCJ it is necessary to consider indels, which are insertions and deletions of DNA segments. Linear time algorithms were proposed to compute the distance and to find a sorting scenario in a general, unrestricted DCJ-indel model that considers DCJ and indels. Results In the present work we consider the restricted DCJ-indel model for sorting linear genomes with unequal contents. We allow DCJ operations and indels with the following constraint: if a circular chromosome is created by a DCJ, it has to be reincorporated in the next step (no other DCJ or indel can be applied between the creation and the reincorporation of a circular chromosome). We then develop a sorting algorithm and give a tight upper bound for the restricted DCJ-indel distance. Conclusions We have given a tight upper bound for the restricted DCJ-indel distance. The question whether this bound can be reduced so that both the general and the restricted DCJ-indel distances are equal remains open. PMID:23281630

Strong CP and SUZ2

NASA Astrophysics Data System (ADS)

Albaid, Abdelhamid; Dine, Michael; Draper, Patrick

2015-12-01

Solutions to the strong CP problem typically introduce new scales associated with the spontaneous breaking of symmetries. Absent any anthropic argument for small overline{θ} , these scales require stabilization against ultraviolet corrections. Supersymmetry offers a tempting stabilization mechanism, since it can solve the "big" electroweak hierarchy problem at the same time. One family of solutions to strong CP, including generalized parity models, heavy axion models, and heavy η' models, introduces {Z}_2 copies of (part of) the Standard Model and an associated scale of {Z}_2 -breaking. We review why, without additional structure such as supersymmetry, the {Z}_2 -breaking scale is unacceptably tuned. We then study "SUZ2" models, supersymmetric theories with {Z}_2 copies of the MSSM. We find that the addition of SUSY typically destroys the {Z}_2 protection of overline{θ}=0 , even at tree level, once SUSY and {Z}_2 are broken. In theories like supersymmetric completions of the twin Higgs, where {Z}_2 addresses the little hierarchy problem but not strong CP, two axions can be used to relax overline{θ}.

Empirical Estimation of Local Dielectric Constants: Toward Atomistic Design of Collagen Mimetic Peptides

PubMed Central

Pike, Douglas H.; Nanda, Vikas

2017-01-01

One of the key challenges in modeling protein energetics is the treatment of solvent interactions. This is particularly important in the case of peptides, where much of the molecule is highly exposed to solvent due to its small size. In this study, we develop an empirical method for estimating the local dielectric constant based on an additive model of atomic polarizabilities. Calculated values match reported apparent dielectric constants for a series of Staphylococcus aureus nuclease mutants. Calculated constants are used to determine screening effects on Coulombic interactions and to determine solvation contributions based on a modified Generalized Born model. These terms are incorporated into the protein modeling platform protCAD, and benchmarked on a data set of collagen mimetic peptides for which experimentally determined stabilities are available. Computing local dielectric constants using atomistic protein models and the assumption of additive atomic polarizabilities is a rapid and potentially useful method for improving electrostatics and solvation calculations that can be applied in the computational design of peptides. PMID:25784456

Analysis of the Best-Fit Sky Model Produced Through Redundant Calibration of Interferometers

NASA Astrophysics Data System (ADS)

Storer, Dara; Pober, Jonathan

2018-01-01

21 cm cosmology provides unique insights into the formation of stars and galaxies in the early universe, and particularly the Epoch of Reionization. Detection of the 21 cm line is challenging because it is generally 4-5 magnitudes weaker than the emission from foreground sources, and therefore the instruments used for detection must be carefully designed and calibrated. 21 cm cosmology is primarily conducted using interferometers, which are difficult to calibrate because of their complex structure. Here I explore the relationship between sky-based calibration, which relies on an accurate and comprehensive sky model, and redundancy-based calibration, which makes use of redundancies in the orientation of the interferometer's dishes. In addition to producing calibration parameters, redundant calibration also produces a best fit model of the sky. In this work I examine that sky model and explore the possibility of using that best fit model as an additional input to improve on sky-based calibration.

Safety behavior: Job demands, job resources, and perceived management commitment to safety.

PubMed

Hansez, Isabelle; Chmiel, Nik

2010-07-01

The job demands-resources model posits that job demands and resources influence outcomes through job strain and work engagement processes. We test whether the model can be extended to effort-related "routine" safety violations and "situational" safety violations provoked by the organization. In addition we test more directly the involvement of job strain than previous studies which have used burnout measures. Structural equation modeling provided, for the first time, evidence of predicted relationships between job strain and "routine" violations and work engagement with "routine" and "situational" violations, thereby supporting the extension of the job demands-resources model to safety behaviors. In addition our results showed that a key safety-specific construct 'perceived management commitment to safety' added to the explanatory power of the job demands-resources model. A predicted path from job resources to perceived management commitment to safety was highly significant, supporting the view that job resources can influence safety behavior through both general motivational involvement in work (work engagement) and through safety-specific processes.

Using additive manufacturing in accuracy evaluation of reconstructions from computed tomography.

PubMed

Smith, Erin J; Anstey, Joseph A; Venne, Gabriel; Ellis, Randy E

2013-05-01

Bone models derived from patient imaging and fabricated using additive manufacturing technology have many potential uses including surgical planning, training, and research. This study evaluated the accuracy of bone surface reconstruction of two diarthrodial joints, the hip and shoulder, from computed tomography. Image segmentation of the tomographic series was used to develop a three-dimensional virtual model, which was fabricated using fused deposition modelling. Laser scanning was used to compare cadaver bones, printed models, and intermediate segmentations. The overall bone reconstruction process had a reproducibility of 0.3 ± 0.4 mm. Production of the model had an accuracy of 0.1 ± 0.1 mm, while the segmentation had an accuracy of 0.3 ± 0.4 mm, indicating that segmentation accuracy was the key factor in reconstruction. Generally, the shape of the articular surfaces was reproduced accurately, with poorer accuracy near the periphery of the articular surfaces, particularly in regions with periosteum covering and where osteophytes were apparent.

Offspring Size and Reproductive Allocation in Harvester Ants.

PubMed

Wiernasz, Diane C; Cole, Blaine J

2018-01-01

A fundamental decision that an organism must make is how to allocate resources to offspring, with respect to both size and number. The two major theoretical approaches to this problem, optimal offspring size and optimistic brood size models, make different predictions that may be reconciled by including how offspring fitness is related to size. We extended the reasoning of Trivers and Willard (1973) to derive a general model of how parents should allocate additional resources with respect to the number of males and females produced, and among individuals of each sex, based on the fitness payoffs of each. We then predicted how harvester ant colonies should invest additional resources and tested three hypotheses derived from our model, using data from 3 years of food supplementation bracketed by 6 years without food addition. All major results were predicted by our model: food supplementation increased the number of reproductives produced. Male, but not female, size increased with food addition; the greatest increases in male size occurred in colonies that made small females. We discuss how use of a fitness landscape improves quantitative predictions about allocation decisions. When parents can invest differentially in offspring of different types, the best strategy will depend on parental state as well as the effect of investment on offspring fitness.

Nonequilibrium phase diagram of a one-dimensional quasiperiodic system with a single-particle mobility edge

NASA Astrophysics Data System (ADS)

Purkayastha, Archak; Dhar, Abhishek; Kulkarni, Manas

2017-11-01

We investigate and map out the nonequilibrium phase diagram of a generalization of the well known Aubry-André-Harper (AAH) model. This generalized AAH (GAAH) model is known to have a single-particle mobility edge which also has an additional self-dual property akin to that of the critical point of the AAH model. By calculating the population imbalance, we get hints of a rich phase diagram. We also find a fascinating connection between single particle wave functions near the mobility edge of the GAAH model and the wave functions of the critical AAH model. By placing this model far from equilibrium with the aid of two baths, we investigate the open system transport via system size scaling of nonequilibrium steady state (NESS) current, calculated by fully exact nonequilibrium Green's function (NEGF) formalism. The critical point of the AAH model now generalizes to a `critical' line separating regions of ballistic and localized transport. Like the critical point of the AAH model, current scales subdiffusively with system size on the `critical' line (I ˜N-2 ±0.1 ). However, remarkably, the scaling exponent on this line is distinctly different from that obtained for the critical AAH model (where I ˜N-1.4 ±0.05 ). All these results can be understood from the above-mentioned connection between states near the mobility edge of the GAAH model and those of the critical AAH model. A very interesting high temperature nonequilibrium phase diagram of the GAAH model emerges from our calculations.

Spatial Distribution of the Risk of Dengue and the Entomological Indicators in Sumaré, State of São Paulo, Brazil

PubMed Central

Barbosa, Gerson Laurindo; Donalísio, Maria Rita; Stephan, Celso; Lourenço, Roberto Wagner; Andrade, Valmir Roberto; Arduino, Marylene de Brito; de Lima, Virgilia Luna Castor

2014-01-01

Dengue fever is a major public health problem worldwide, caused by any of four virus (DENV-1, DENV-2, DENV-3 and DENV-4; Flaviviridae: Flavivirus), transmitted by Aedes aegypti mosquito. Reducing the levels of infestation by A. aegypti is one of the few current strategies to control dengue fever. Entomological indicators are used by dengue national control program to measure the infestation of A. aegypti, but little is known about predictive power of these indicators to measure dengue risk. In this spatial case-control study, we analyzed the spatial distribution of the risk of dengue and the influence of entomological indicators of A. aegypti in its egg, larva-pupa and adult stages occurring in a mid-size city in the state of São Paulo. The dengue cases were those confirmed by the city's epidemiological surveillance system and the controls were obtained through random selection of points within the perimeter of the inhabited area. The values of the entomological indicators were extrapolated for the entire study area through the geostatistical ordinary kriging technique. For each case and control, the respective indicator values were obtained, according with its geographical coordinates and analyzed by using a generalized additive model. Dengue incidence demonstrated a seasonal behavior, as well as the entomological indicators of all mosquito's evolutionary stages. The infestation did not present a significant variation in intensity and was not a limiting or determining factor of the occurrence of cases in the municipality. The risk maps of the disease from crude and adjusted generalized additive models did not present differences, suggesting that areas with the highest values of entomological indicators were not associated with the incidence of dengue. The inclusion of other variables in the generalized additive models may reveal the modulatory effect for the risk of the disease, which is not found in this study. PMID:24831806

Spatial distribution of the risk of dengue and the entomological indicators in Sumaré, state of São Paulo, Brazil.

PubMed

Barbosa, Gerson Laurindo; Donalísio, Maria Rita; Stephan, Celso; Lourenço, Roberto Wagner; Andrade, Valmir Roberto; Arduino, Marylene de Brito; de Lima, Virgilia Luna Castor

2014-05-01

Dengue fever is a major public health problem worldwide, caused by any of four virus (DENV-1, DENV-2, DENV-3 and DENV-4; Flaviviridae: Flavivirus), transmitted by Aedes aegypti mosquito. Reducing the levels of infestation by A. aegypti is one of the few current strategies to control dengue fever. Entomological indicators are used by dengue national control program to measure the infestation of A. aegypti, but little is known about predictive power of these indicators to measure dengue risk. In this spatial case-control study, we analyzed the spatial distribution of the risk of dengue and the influence of entomological indicators of A. aegypti in its egg, larva-pupa and adult stages occurring in a mid-size city in the state of São Paulo. The dengue cases were those confirmed by the city's epidemiological surveillance system and the controls were obtained through random selection of points within the perimeter of the inhabited area. The values of the entomological indicators were extrapolated for the entire study area through the geostatistical ordinary kriging technique. For each case and control, the respective indicator values were obtained, according with its geographical coordinates and analyzed by using a generalized additive model. Dengue incidence demonstrated a seasonal behavior, as well as the entomological indicators of all mosquito's evolutionary stages. The infestation did not present a significant variation in intensity and was not a limiting or determining factor of the occurrence of cases in the municipality. The risk maps of the disease from crude and adjusted generalized additive models did not present differences, suggesting that areas with the highest values of entomological indicators were not associated with the incidence of dengue. The inclusion of other variables in the generalized additive models may reveal the modulatory effect for the risk of the disease, which is not found in this study.

A flexible count data regression model for risk analysis.

PubMed

Guikema, Seth D; Coffelt, Jeremy P; Goffelt, Jeremy P

2008-02-01

In many cases, risk and reliability analyses involve estimating the probabilities of discrete events such as hardware failures and occurrences of disease or death. There is often additional information in the form of explanatory variables that can be used to help estimate the likelihood of different numbers of events in the future through the use of an appropriate regression model, such as a generalized linear model. However, existing generalized linear models (GLM) are limited in their ability to handle the types of variance structures often encountered in using count data in risk and reliability analysis. In particular, standard models cannot handle both underdispersed data (variance less than the mean) and overdispersed data (variance greater than the mean) in a single coherent modeling framework. This article presents a new GLM based on a reformulation of the Conway-Maxwell Poisson (COM) distribution that is useful for both underdispersed and overdispersed count data and demonstrates this model by applying it to the assessment of electric power system reliability. The results show that the proposed COM GLM can provide as good of fits to data as the commonly used existing models for overdispered data sets while outperforming these commonly used models for underdispersed data sets.

Challenges for Cloud Modeling in the Context of Aerosol–Cloud–Precipitation Interactions

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

Lebo, Zachary J.; Shipway, Ben J.; Fan, Jiwen

The International Cloud Modeling Workshop (CMW) has been a longstanding tradition in the cloud microphysics modeling community and is typically held the week prior to the International Conference on Clouds and Precipitation (ICCP). For the Ninth CMW, more than 40 participants from 10 countries convened at the Met Office in Exeter, United Kingdom. The workshop included 4 detailed case studies (described in more detail below) rooted in recent field campaigns. The overarching objective of these cases was to utilize new observations to better understand inter-model differences and model deficiencies, explore new modeling techniques, and gain physical insight into the behaviormore » of clouds. As was the case at the Eighth CMW, there was a general theme of understanding the role of aerosol impacts in the context of cloud-precipitation interactions. However, an additional objective was the focal point of several cases at the most recent workshop: microphysical-dynamical interactions. Many of the cases focused less on idealized small-domain simulations (as was the general focus of previous workshops) and more on large-scale nested configurations examining effects at various scales.« less

On the stability of the exact solutions of the dual-phase lagging model of heat conduction.

PubMed

Ordonez-Miranda, Jose; Alvarado-Gil, Juan Jose

2011-04-13

The dual-phase lagging (DPL) model has been considered as one of the most promising theoretical approaches to generalize the classical Fourier law for heat conduction involving short time and space scales. Its applicability, potential, equivalences, and possible drawbacks have been discussed in the current literature. In this study, the implications of solving the exact DPL model of heat conduction in a three-dimensional bounded domain solution are explored. Based on the principle of causality, it is shown that the temperature gradient must be always the cause and the heat flux must be the effect in the process of heat transfer under the dual-phase model. This fact establishes explicitly that the single- and DPL models with different physical origins are mathematically equivalent. In addition, taking into account the properties of the Lambert W function and by requiring that the temperature remains stable, in such a way that it does not go to infinity when the time increases, it is shown that the DPL model in its exact form cannot provide a general description of the heat conduction phenomena.

Behavior of the maximum likelihood in quantum state tomography

NASA Astrophysics Data System (ADS)

Scholten, Travis L.; Blume-Kohout, Robin

2018-02-01

Quantum state tomography on a d-dimensional system demands resources that grow rapidly with d. They may be reduced by using model selection to tailor the number of parameters in the model (i.e., the size of the density matrix). Most model selection methods typically rely on a test statistic and a null theory that describes its behavior when two models are equally good. Here, we consider the loglikelihood ratio. Because of the positivity constraint ρ ≥ 0, quantum state space does not generally satisfy local asymptotic normality (LAN), meaning the classical null theory for the loglikelihood ratio (the Wilks theorem) should not be used. Thus, understanding and quantifying how positivity affects the null behavior of this test statistic is necessary for its use in model selection for state tomography. We define a new generalization of LAN, metric-projected LAN, show that quantum state space satisfies it, and derive a replacement for the Wilks theorem. In addition to enabling reliable model selection, our results shed more light on the qualitative effects of the positivity constraint on state tomography.

Behavior of the maximum likelihood in quantum state tomography

DOE PAGES

Blume-Kohout, Robin J; Scholten, Travis L.

2018-02-22

Quantum state tomography on a d-dimensional system demands resources that grow rapidly with d. They may be reduced by using model selection to tailor the number of parameters in the model (i.e., the size of the density matrix). Most model selection methods typically rely on a test statistic and a null theory that describes its behavior when two models are equally good. Here, we consider the loglikelihood ratio. Because of the positivity constraint ρ ≥ 0, quantum state space does not generally satisfy local asymptotic normality (LAN), meaning the classical null theory for the loglikelihood ratio (the Wilks theorem) shouldmore » not be used. Thus, understanding and quantifying how positivity affects the null behavior of this test statistic is necessary for its use in model selection for state tomography. We define a new generalization of LAN, metric-projected LAN, show that quantum state space satisfies it, and derive a replacement for the Wilks theorem. In addition to enabling reliable model selection, our results shed more light on the qualitative effects of the positivity constraint on state tomography.« less

Behavior of the maximum likelihood in quantum state tomography

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

Blume-Kohout, Robin J; Scholten, Travis L.

Quantum state tomography on a d-dimensional system demands resources that grow rapidly with d. They may be reduced by using model selection to tailor the number of parameters in the model (i.e., the size of the density matrix). Most model selection methods typically rely on a test statistic and a null theory that describes its behavior when two models are equally good. Here, we consider the loglikelihood ratio. Because of the positivity constraint ρ ≥ 0, quantum state space does not generally satisfy local asymptotic normality (LAN), meaning the classical null theory for the loglikelihood ratio (the Wilks theorem) shouldmore » not be used. Thus, understanding and quantifying how positivity affects the null behavior of this test statistic is necessary for its use in model selection for state tomography. We define a new generalization of LAN, metric-projected LAN, show that quantum state space satisfies it, and derive a replacement for the Wilks theorem. In addition to enabling reliable model selection, our results shed more light on the qualitative effects of the positivity constraint on state tomography.« less

Estimating organ doses from tube current modulated CT examinations using a generalized linear model.

PubMed

Bostani, Maryam; McMillan, Kyle; Lu, Peiyun; Kim, Grace Hyun J; Cody, Dianna; Arbique, Gary; Greenberg, S Bruce; DeMarco, John J; Cagnon, Chris H; McNitt-Gray, Michael F

2017-04-01

Currently, available Computed Tomography dose metrics are mostly based on fixed tube current Monte Carlo (MC) simulations and/or physical measurements such as the size specific dose estimate (SSDE). In addition to not being able to account for Tube Current Modulation (TCM), these dose metrics do not represent actual patient dose. The purpose of this study was to generate and evaluate a dose estimation model based on the Generalized Linear Model (GLM), which extends the ability to estimate organ dose from tube current modulated examinations by incorporating regional descriptors of patient size, scanner output, and other scan-specific variables as needed. The collection of a total of 332 patient CT scans at four different institutions was approved by each institution's IRB and used to generate and test organ dose estimation models. The patient population consisted of pediatric and adult patients and included thoracic and abdomen/pelvis scans. The scans were performed on three different CT scanner systems. Manual segmentation of organs, depending on the examined anatomy, was performed on each patient's image series. In addition to the collected images, detailed TCM data were collected for all patients scanned on Siemens CT scanners, while for all GE and Toshiba patients, data representing z-axis-only TCM, extracted from the DICOM header of the images, were used for TCM simulations. A validated MC dosimetry package was used to perform detailed simulation of CT examinations on all 332 patient models to estimate dose to each segmented organ (lungs, breasts, liver, spleen, and kidneys), denoted as reference organ dose values. Approximately 60% of the data were used to train a dose estimation model, while the remaining 40% was used to evaluate performance. Two different methodologies were explored using GLM to generate a dose estimation model: (a) using the conventional exponential relationship between normalized organ dose and size with regional water equivalent diameter (WED) and regional CTDI vol as variables and (b) using the same exponential relationship with the addition of categorical variables such as scanner model and organ to provide a more complete estimate of factors that may affect organ dose. Finally, estimates from generated models were compared to those obtained from SSDE and ImPACT. The Generalized Linear Model yielded organ dose estimates that were significantly closer to the MC reference organ dose values than were organ doses estimated via SSDE or ImPACT. Moreover, the GLM estimates were better than those of SSDE or ImPACT irrespective of whether or not categorical variables were used in the model. While the improvement associated with a categorical variable was substantial in estimating breast dose, the improvement was minor for other organs. The GLM approach extends the current CT dose estimation methods by allowing the use of additional variables to more accurately estimate organ dose from TCM scans. Thus, this approach may be able to overcome the limitations of current CT dose metrics to provide more accurate estimates of patient dose, in particular, dose to organs with considerable variability across the population. © 2017 American Association of Physicists in Medicine.

Models for small-scale structure on cosmic strings. II. Scaling and its stability

NASA Astrophysics Data System (ADS)

Vieira, J. P. P.; Martins, C. J. A. P.; Shellard, E. P. S.

2016-11-01

We make use of the formalism described in a previous paper [Martins et al., Phys. Rev. D 90, 043518 (2014)] to address general features of wiggly cosmic string evolution. In particular, we highlight the important role played by poorly understood energy loss mechanisms and propose a simple Ansatz which tackles this problem in the context of an extended velocity-dependent one-scale model. We find a general procedure to determine all the scaling solutions admitted by a specific string model and study their stability, enabling a detailed comparison with future numerical simulations. A simpler comparison with previous Goto-Nambu simulations supports earlier evidence that scaling is easier to achieve in the matter era than in the radiation era. In addition, we also find that the requirement that a scaling regime be stable seems to notably constrain the allowed range of energy loss parameters.

An introduction to analyzing dichotomous outcomes in a longitudinal setting: a NIDRR traumatic brain injury model systems communication.

PubMed

Pretz, Christopher R; Ketchum, Jessica M; Cuthbert, Jeffery P

2014-01-01

An untapped wealth of temporal information is captured within the Traumatic Brain Injury Model Systems National Database. Utilization of appropriate longitudinal analyses can provide an avenue toward unlocking the value of this information. This article highlights 2 statistical methods used for assessing change over time when examination of noncontinuous outcomes is of interest where this article focuses on investigation of dichotomous responses. Specifically, the intent of this article is to familiarize the rehabilitation community with the application of generalized estimating equations and generalized linear mixed models as used in longitudinal studies. An introduction to each method is provided where similarities and differences between the 2 are discussed. In addition, to reinforce the ideas and concepts embodied in each approach, we highlight each method, using examples based on data from the Rocky Mountain Regional Brain Injury System.

Gene expression during blow fly development: improving the precision of age estimates in forensic entomology.

PubMed

Tarone, Aaron M; Foran, David R

2011-01-01

Forensic entomologists use size and developmental stage to estimate blow fly age, and from those, a postmortem interval. Since such estimates are generally accurate but often lack precision, particularly in the older developmental stages, alternative aging methods would be advantageous. Presented here is a means of incorporating developmentally regulated gene expression levels into traditional stage and size data, with a goal of more precisely estimating developmental age of immature Lucilia sericata. Generalized additive models of development showed improved statistical support compared to models that did not include gene expression data, resulting in an increase in estimate precision, especially for postfeeding third instars and pupae. The models were then used to make blind estimates of development for 86 immature L. sericata raised on rat carcasses. Overall, inclusion of gene expression data resulted in increased precision in aging blow flies. © 2010 American Academy of Forensic Sciences.

Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions.

PubMed

Meesters, Stephan; Ossenblok, Pauly; Colon, Albert; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Fuster, Andrea

2018-06-01

The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. A network approach is promising in case of complex epilepsies. Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Fault zone structure determined through the analysis of earthquake arrival times

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

Michelini, A.

1991-10-01

This thesis develops and applies a technique for the simultaneous determination of P and S wave velocity models and hypocenters from a set of arrival times. The velocity models are parameterized in terms of cubic B-splines basis functions which permit the retrieval of smooth models that can be used directly for generation of synthetic seismograms using the ray method. In addition, this type of smoothing limits the rise of instabilities related to the poor resolving power of the data. V{sub P}/V{sub S} ratios calculated from P and S models display generally instabilities related to the different ray-coverages of compressional andmore » shear waves. However, V{sub P}/V{sub S} ratios are important for correct identification of rock types and this study introduces a new methodology based on adding some coupling (i.e., proportionality) between P and S models which stabilizes the V{sub P}/V{sub S} models around some average preset value determined from the data. Tests of the technique with synthetic data show that this additional coupling regularizes effectively the resulting models.« less

Fault zone structure determined through the analysis of earthquake arrival times

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

Michelini, Alberto

1991-10-01

This thesis develops and applies a technique for the simultaneous determination of P and S wave velocity models and hypocenters from a set of arrival times. The velocity models are parameterized in terms of cubic B-splines basis functions which permit the retrieval of smooth models that can be used directly for generation of synthetic seismograms using the ray method. In addition, this type of smoothing limits the rise of instabilities related to the poor resolving power of the data. V P/V S ratios calculated from P and S models display generally instabilities related to the different ray-coverages of compressional andmore » shear waves. However, V P/V S ratios are important for correct identification of rock types and this study introduces a new methodology based on adding some coupling (i.e., proportionality) between P and S models which stabilizes the V P/V S models around some average preset value determined from the data. Tests of the technique with synthetic data show that this additional coupling regularizes effectively the resulting models.« less

Diffusion in different models of active Brownian motion

NASA Astrophysics Data System (ADS)

Lindner, B.; Nicola, E. M.

2008-04-01

Active Brownian particles (ABP) have served as phenomenological models of self-propelled motion in biology. We study the effective diffusion coefficient of two one-dimensional ABP models (simplified depot model and Rayleigh-Helmholtz model) differing in their nonlinear friction functions. Depending on the choice of the friction function the diffusion coefficient does or does not attain a minimum as a function of noise intensity. We furthermore discuss the case of an additional bias breaking the left-right symmetry of the system. We show that this bias induces a drift and that it generally reduces the diffusion coefficient. For a finite range of values of the bias, both models can exhibit a maximum in the diffusion coefficient vs. noise intensity.

USING MULTIPLE-EXEMPLAR TRAINING TO TEACH A GENERALIZED REPERTOIRE OF SHARING TO CHILDREN WITH AUTISM

PubMed Central

Marzullo-Kerth, Denise; Reeve, Sharon A; Reeve, Kenneth F; Townsend, Dawn B

2011-01-01

The current study examined the utility of multiple-exemplar training to teach children with autism to share. Stimuli from 3 of 4 categories were trained using a treatment package of video modeling, prompting, and reinforcement. Offers to share increased for all 3 children following the introduction of treatment, with evidence of skill maintenance. In addition, within-stimulus-category generalization of sharing was evident for all participants, although only 1 participant demonstrated across-category generalization of sharing. Offers to share occurred in a novel setting, with familiar and novel stimuli, and in the presence of novel adults and peers for all participants during posttreatment probes. PMID:21709784

Supersymmetric solutions of N =(1 ,1 ) general massive supergravity

NASA Astrophysics Data System (ADS)

Deger, N. S.; Nazari, Z.; Sarıoǧlu, Ö.

2018-05-01

We construct supersymmetric solutions of three-dimensional N =(1 ,1 ) general massive supergravity (GMG). Solutions with a null Killing vector are, in general, pp-waves. We identify those that appear at critical points of the model, some of which do not exist in N =(1 ,1 ) new massive supergravity (NMG). In the timelike case, we find that many solutions are common with NMG, but there is a new class that is genuine to GMG, two members of which are stationary Lifshitz and timelike squashed AdS spacetimes. We also show that in addition to the fully supersymmetric AdS vacuum, there is a second AdS background with a nonzero vector field that preserves 1 /4 supersymmetry.

Science engagement and science achievement in the context of science instruction: a multilevel analysis of U.S. students and schools

NASA Astrophysics Data System (ADS)

Grabau, Larry J.; Ma, Xin

2017-05-01

Using data from the 2006 Program for International Student Assessment (PISA), we explored nine aspects of science engagement (science self-efficacy, science self-concept, enjoyment of science, general interest in learning science, instrumental motivation for science, future-oriented science motivation, general value of science, personal value of science, and science-related activities) as outcomes and predictors of science achievement. Based on results from multilevel modelling with 4456 students nested within 132 schools, we found that all aspects of science engagement were statistically significantly and positively related to science achievement, and nearly all showed medium or large effect sizes. Each aspect was positively associated with one of the (four) practices (strategies) of science teaching. Focus on applications or models was positively related to the most aspects of science engagement (science self-concept, enjoyment of science, instrumental motivation for science, general value of science, and personal value of science). Hands-on activities were positively related to additional aspects of science engagement (science self-efficacy and general interest in learning science) and also showed a positive relationship with science achievement.

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

PubMed

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.

A soil-canopy scheme for use in a numerical model of the atmosphere: 1D stand-alone model

NASA Astrophysics Data System (ADS)

Kowalczyk, E. A.; Garratt, J. R.; Krummel, P. B.

We provide a detailed description of a soil-canopy scheme for use in the CSIRO general circulation models (GCMs) (CSIRO-4 and CSIRO-9), in the form of a one-dimensional stand-alone model. In addition, the paper documents the model's ability to simulate realistic surface fluxes by comparison with mesoscale model simulations (involving more sophisticated soil and boundary-layer treatments) and observations, and the diurnal range in surface quantities, including extreme maximum surface temperatures. The sensitivity of the model to values of the surface resistance is also quantified. The model represents phase 1 of a longer-term plan to improve the atmospheric boundary layer (ABL) and surface schemes in the CSIRO GCMs.

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.

PubMed

Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola

2016-07-01

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.

Comprehensive silicon solar cell computer modeling

NASA Technical Reports Server (NTRS)

Lamorte, M. F.

1984-01-01

The development of an efficient, comprehensive Si solar cell modeling program that has the capability of simulation accuracy of 5 percent or less is examined. A general investigation of computerized simulation is provided. Computer simulation programs are subdivided into a number of major tasks: (1) analytical method used to represent the physical system; (2) phenomena submodels that comprise the simulation of the system; (3) coding of the analysis and the phenomena submodels; (4) coding scheme that results in efficient use of the CPU so that CPU costs are low; and (5) modularized simulation program with respect to structures that may be analyzed, addition and/or modification of phenomena submodels as new experimental data become available, and the addition of other photovoltaic materials.

Freezing Transition Studies Through Constrained Cell Model Simulation

NASA Astrophysics Data System (ADS)

Nayhouse, Michael; Kwon, Joseph Sang-Il; Heng, Vincent R.; Amlani, Ankur M.; Orkoulas, G.

2014-10-01

In the present work, a simulation method based on cell models is used to deduce the fluid-solid transition of a system of particles that interact via a pair potential, , which is of the form with . The simulations are implemented under constant-pressure conditions on a generalized version of the constrained cell model. The constrained cell model is constructed by dividing the volume into Wigner-Seitz cells and confining each particle in a single cell. This model is a special case of a more general cell model which is formed by introducing an additional field variable that controls the number of particles per cell and, thus, the relative stability of the solid against the fluid phase. High field values force configurations with one particle per cell and thus favor the solid phase. Fluid-solid coexistence on the isotherm that corresponds to a reduced temperature of 2 is determined from constant-pressure simulations of the generalized cell model using tempering and histogram reweighting techniques. The entire fluid-solid phase boundary is determined through a thermodynamic integration technique based on histogram reweighting, using the previous coexistence point as a reference point. The vapor-liquid phase diagram is obtained from constant-pressure simulations of the unconstrained system using tempering and histogram reweighting. The phase diagram of the system is found to contain a stable critical point and a triple point. The phase diagram of the corresponding constrained cell model is also found to contain both a stable critical point and a triple point.

Phylogenetic analysis accounting for age-dependent death and sampling with applications to epidemics.

PubMed

Lambert, Amaury; Alexander, Helen K; Stadler, Tanja

2014-07-07

The reconstruction of phylogenetic trees based on viral genetic sequence data sequentially sampled from an epidemic provides estimates of the past transmission dynamics, by fitting epidemiological models to these trees. To our knowledge, none of the epidemiological models currently used in phylogenetics can account for recovery rates and sampling rates dependent on the time elapsed since transmission, i.e. age of infection. Here we introduce an epidemiological model where infectives leave the epidemic, by either recovery or sampling, after some random time which may follow an arbitrary distribution. We derive an expression for the likelihood of the phylogenetic tree of sampled infectives under our general epidemiological model. The analytic concept developed in this paper will facilitate inference of past epidemiological dynamics and provide an analytical framework for performing very efficient simulations of phylogenetic trees under our model. The main idea of our analytic study is that the non-Markovian epidemiological model giving rise to phylogenetic trees growing vertically as time goes by can be represented by a Markovian "coalescent point process" growing horizontally by the sequential addition of pairs of coalescence and sampling times. As examples, we discuss two special cases of our general model, described in terms of influenza and HIV epidemics. Though phrased in epidemiological terms, our framework can also be used for instance to fit macroevolutionary models to phylogenies of extant and extinct species, accounting for general species lifetime distributions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Learning abstract visual concepts via probabilistic program induction in a Language of Thought.

PubMed

Overlan, Matthew C; Jacobs, Robert A; Piantadosi, Steven T

2017-11-01

The ability to learn abstract concepts is a powerful component of human cognition. It has been argued that variable binding is the key element enabling this ability, but the computational aspects of variable binding remain poorly understood. Here, we address this shortcoming by formalizing the Hierarchical Language of Thought (HLOT) model of rule learning. Given a set of data items, the model uses Bayesian inference to infer a probability distribution over stochastic programs that implement variable binding. Because the model makes use of symbolic variables as well as Bayesian inference and programs with stochastic primitives, it combines many of the advantages of both symbolic and statistical approaches to cognitive modeling. To evaluate the model, we conducted an experiment in which human subjects viewed training items and then judged which test items belong to the same concept as the training items. We found that the HLOT model provides a close match to human generalization patterns, significantly outperforming two variants of the Generalized Context Model, one variant based on string similarity and the other based on visual similarity using features from a deep convolutional neural network. Additional results suggest that variable binding happens automatically, implying that binding operations do not add complexity to peoples' hypothesized rules. Overall, this work demonstrates that a cognitive model combining symbolic variables with Bayesian inference and stochastic program primitives provides a new perspective for understanding people's patterns of generalization. Copyright © 2017 Elsevier B.V. All rights reserved.

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

PubMed Central

Shen, Li; Qi, Yuan; Kim, Sungeun; Nho, Kwangsik; Wan, Jing; Risacher, Shannon L.; Saykin, Andrew J.

2010-01-01

We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accurate prediction and identify critical imaging markers relevant to AD at the same time. ARD is one of the most successful Bayesian feature selection methods. PARD is a powerful Bayesian feature selection method, and provides sparse models that is easy to interpret. PARD selects the model with the best estimate of the predictive performance instead of choosing the one with the largest marginal model likelihood. Comparative study with support vector machine (SVM) shows that ARD/PARD in general outperform SVM in terms of prediction accuracy. Additional comparison with surface-based general linear model (GLM) analysis shows that regions with strongest signals are identified by both GLM and ARD/PARD. While GLM P-map returns significant regions all over the cortex, ARD/PARD provide a small number of relevant and meaningful imaging markers with predictive power, including both cortical and subcortical measures. PMID:20879451

Exponential inflation with F (R ) gravity

NASA Astrophysics Data System (ADS)

Oikonomou, V. K.

2018-03-01

In this paper, we shall consider an exponential inflationary model in the context of vacuum F (R ) gravity. By using well-known reconstruction techniques, we shall investigate which F (R ) gravity can realize the exponential inflation scenario at leading order in terms of the scalar curvature, and we shall calculate the slow-roll indices and the corresponding observational indices, in the context of slow-roll inflation. We also provide some general formulas of the slow-roll and the corresponding observational indices in terms of the e -foldings number. In addition, for the calculation of the slow-roll and of the observational indices, we shall consider quite general formulas, for which it is not necessary for the assumption that all the slow-roll indices are much smaller than unity to hold true. Finally, we investigate the phenomenological viability of the model by comparing it with the latest Planck and BICEP2/Keck-Array observational data. As we demonstrate, the model is compatible with the current observational data for a wide range of the free parameters of the model.

From Family Violence Exposure to Violent Offending: Examining Effects of Race and Mental Health in a Moderated Mediation Model Among Confined Male Juveniles.

PubMed

Fix, Rebecca L; Alexander, Apryl A; Burkhart, Barry R

2017-09-01

Depression, substance use, and impulsivity have been linked to family violence exposure and to the development of violent offending during adolescence. Additionally, the indirect effects associated with these factors may not generalize across different racial/ethnic adolescent populations. The present study tested whether race/ethnicity moderated the mediated relationship between family violence exposure and violent offending, with depression, substance use, and impulsivity as mediators. A sample of 1,359 male adolescents was obtained from a juvenile correctional program. Between-racial/ethnic group comparisons were generally consistent with previous findings. The overall moderated mediation model was significant in predicting violence for both racial/ethnic groups. Different factors influenced violent offending among African Americans and European Americans in the tested model. Furthermore, race/ethnicity moderated the relationship between family violence exposure and impulsivity and substance use. Implications and future directions resolving issues are discussed concerning whether race/ethnicity should be included as a moderator in models of violence.

Generalized Galileons: instabilities of bouncing and Genesis cosmologies and modified Genesis

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

Libanov, M.; Moscow Institute of Physics and Technology,Institutskii per. 9, 141700 Dolgoprudny, Moscow Region; Mironov, S.

2016-08-18

We study spatially flat bouncing cosmologies and models with the early-time Genesis epoch in a popular class of generalized Galileon theories. We ask whether there exist solutions of these types which are free of gradient and ghost instabilities. We find that irrespectively of the forms of the Lagrangian functions, the bouncing models either are plagued with these instabilities or have singularities. The same result holds for the original Genesis model and its variants in which the scale factor tends to a constant as t→−∞. The result remains valid in theories with additional matter that obeys the Null Energy Condition andmore » interacts with the Galileon only gravitationally. We propose a modified Genesis model which evades our no-go argument and give an explicit example of healthy cosmology that connects the modified Genesis epoch with kination (the epoch still driven by the Galileon field, which is a conventional massless scalar field at that stage).« less

Evolutionary design of a generalized polynomial neural network for modelling sediment transport in clean pipes

NASA Astrophysics Data System (ADS)

Ebtehaj, Isa; Bonakdari, Hossein; Khoshbin, Fatemeh

2016-10-01

To determine the minimum velocity required to prevent sedimentation, six different models were proposed to estimate the densimetric Froude number (Fr). The dimensionless parameters of the models were applied along with a combination of the group method of data handling (GMDH) and the multi-target genetic algorithm. Therefore, an evolutionary design of the generalized GMDH was developed using a genetic algorithm with a specific coding scheme so as not to restrict connectivity configurations to abutting layers only. In addition, a new preserving mechanism by the multi-target genetic algorithm was utilized for the Pareto optimization of GMDH. The results indicated that the most accurate model was the one that used the volumetric concentration of sediment (CV), relative hydraulic radius (d/R), dimensionless particle number (Dgr) and overall sediment friction factor (λs) in estimating Fr. Furthermore, the comparison between the proposed method and traditional equations indicated that GMDH is more accurate than existing equations.

A systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs).

PubMed

Kuang, Qifan; Wang, MinQi; Li, Rong; Dong, YongCheng; Li, Yizhou; Li, Menglong

2014-01-01

Early and accurate identification of adverse drug reactions (ADRs) is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs. In the current study, the main work is to compare and analyze the performance of existing computational methods to predict ADRs, by implementing and evaluating additional algorithms that have been earlier used for predicting drug targets. Our results indicated that topological and intrinsic features were complementary to an extent and the Jaccard coefficient had an important and general effect on the prediction of drug-ADR associations. By comparing the structure of each algorithm, final formulas of these algorithms were all converted to linear model in form, based on this finding we propose a new algorithm called the general weighted profile method and it yielded the best overall performance among the algorithms investigated in this paper. Several meaningful conclusions and useful findings regarding the prediction of ADRs are provided for selecting optimal features and algorithms.

Examining the ethnoracial invariance of a bifactor model of anxiety sensitivity and the incremental validity of the physical domain-specific factor in a primary-care patient sample.

PubMed

Fergus, Thomas A; Kelley, Lance P; Griggs, Jackson O

2017-10-01

There is growing support for a bifactor conceptualization of the Anxiety Sensitivity Index-3 (ASI-3; Taylor et al., 2007), consisting of a General factor and 3 domain-specific factors (i.e., Physical, Cognitive, Social). Earlier studies supporting a bifactor model of the ASI-3 used samples that consisted of predominantly White respondents. In addition, extant research has yet to support the incremental validity of the Physical domain-specific factor while controlling for the General factor. The present study is an examination of a bifactor model of the ASI-3 and the measurement invariance of that model among an ethnoracially diverse sample of primary-care patients (N = 533). Results from multiple-group confirmatory factor analysis supported the configural and metric/scalar invariance of the bifactor model of the ASI-3 across self-identifying Black, Latino, and White respondents. The Physical domain-specific factor accounted for unique variance in an index of health anxiety beyond the General factor. These results provide support for the generalizability of a bifactor model of the ASI-3 across 3 ethnoracial groups, as well as indication of the incremental explanatory power of the Physical domain-specific factor. Study implications are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

Code of Federal Regulations, 2013 CFR

2013-04-01

... 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...

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

Code of Federal Regulations, 2010 CFR

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...

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

Code of Federal Regulations, 2011 CFR

2011-04-01

... 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...

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

Code of Federal Regulations, 2012 CFR

2012-04-01

... 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...

Specialty hospitals emulating focused factories: a case study.

PubMed

Kumar, Sameer

2010-01-01

For 15 years general hospital managers faced new competition from for-profit specialty hospitals that operate on a "focused factory" model, which threaten to siphon-off the most profitable patients. This paper aims to discuss North American specialty hospitals and to review rising costs impact on general hospital operations. The focus is to discover whether specialty hospitals are more efficient than general hospitals; if so, how significant is the difference and also what can general hospitals do in light of the rising specialty hospitals. The case study involves stochastic frontier regression analysis using Cobb-Douglas and Translog cost functions to compare Minnesota general and specialty hospital efficiency. Analysis is based on data from 117 general and 19 specialty hospitals. The results suggest that specialty hospitals are significantly more efficient than general hospitals. Overall, general hospitals were found to be more than twice as inefficient compared with specialty hospitals in the sample. Some cost-cutting factors highlighted can be implemented to trim rising costs. The case study highlights some managerial levers that general hospital operational managers might use to control rising costs. This also helps them compete with specialty hospitals by reducing overheads and other major costs. The study is based on empirical modeling for an important healthcare operational challenge and provides additional in-depth information that has health policy implications. The analysis and findings enable healthcare managers to guide their institutions in a new direction during a time of change within the industry.

Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.

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

PubMed Central

Gasparrini, Antonio

2014-01-01

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

21 CFR 170.30 - Eligibility for classification as generally recognized as safe (GRAS).

Code of Federal Regulations, 2013 CFR

2013-04-01

... HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) FOOD ADDITIVES Food Additive... obtain approval of a food additive regulation for the ingredient. General recognition of safety through... of scientific procedures required for approval of a food additive regulation. General recognition of...

21 CFR 170.30 - Eligibility for classification as generally recognized as safe (GRAS).

Code of Federal Regulations, 2011 CFR

2011-04-01

... HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) FOOD ADDITIVES Food Additive... obtain approval of a food additive regulation for the ingredient. General recognition of safety through... of scientific procedures required for approval of a food additive regulation. General recognition of...

21 CFR 170.30 - Eligibility for classification as generally recognized as safe (GRAS).

Code of Federal Regulations, 2012 CFR

2012-04-01

... HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) FOOD ADDITIVES Food Additive... obtain approval of a food additive regulation for the ingredient. General recognition of safety through... of scientific procedures required for approval of a food additive regulation. General recognition of...

21 CFR 170.30 - Eligibility for classification as generally recognized as safe (GRAS).

Code of Federal Regulations, 2010 CFR

2010-04-01

... HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) FOOD ADDITIVES Food Additive... obtain approval of a food additive regulation for the ingredient. General recognition of safety through... of scientific procedures required for approval of a food additive regulation. General recognition of...

Influence of Blended Learning on Outcomes of Students Attending a General Chemistry Course: Summary of a Five-Year-Long Study

ERIC Educational Resources Information Center

Bernard, P.; Bros, P.; Migdal-Mikuli, A.

2017-01-01

The development of the Internet, communication technologies and teaching methods creates new opportunities for the modernisation of academic classes. Many studies on the application of new educational models indicate that they are both more effective and preferred by students over classical approaches. Additionally, combining various education…

General Electromagnetic Model for the Analysis of Complex Systems (GEMACS) Engineering Manual (Version 3). Volume 3.

DTIC Science & Technology

1983-09-01

processor. How- ever, upon completion of the restart initialization, additional commands may be added or original commands deleted with normal input...written IOSI Scratch logical unit designator IOS1SV Saved value of lOS1 IOS2 Scratch logical unit designator IR Index pointer to upper triangular matrix

Alternative Fuels Data Center: Memorandums of Understanding-Broadening

Science.gov Websites

to more affordable NGVs for government fleets. In Oklahoma, for example, the post-RFP cost of a Dodge commented. In another example, the Oklahoma Secretary of Energy and Environment held a series of town hall releasing NGV models and providing additional options for consumers and fleets alike. For example, General

40 CFR 80.50 - General test procedure requirements for augmentation of the emission models.

Code of Federal Regulations, 2014 CFR

2014-07-01

... § 80.45. (1) VOC, NOX, CO, and CO2 emissions must be measured for all fuel-vehicle combinations tested. (2) Toxics emissions must be measured when testing the extension fuels per the requirements of § 80... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated...

40 CFR 80.50 - General test procedure requirements for augmentation of the emission models.

Code of Federal Regulations, 2010 CFR

2010-07-01

... § 80.45. (1) VOC, NOX, CO, and CO2 emissions must be measured for all fuel-vehicle combinations tested. (2) Toxics emissions must be measured when testing the extension fuels per the requirements of § 80... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated...

40 CFR 80.50 - General test procedure requirements for augmentation of the emission models.

Code of Federal Regulations, 2012 CFR

2012-07-01

... § 80.45. (1) VOC, NOX, CO, and CO2 emissions must be measured for all fuel-vehicle combinations tested. (2) Toxics emissions must be measured when testing the extension fuels per the requirements of § 80... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated...

40 CFR 80.50 - General test procedure requirements for augmentation of the emission models.

Code of Federal Regulations, 2011 CFR

2011-07-01

... § 80.45. (1) VOC, NOX, CO, and CO2 emissions must be measured for all fuel-vehicle combinations tested. (2) Toxics emissions must be measured when testing the extension fuels per the requirements of § 80... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Reformulated...

Improving Demographic Diversity in the U.S. Air Force Officer Corps

DTIC Science & Technology

2014-01-01

40   v Career Success Is Cumulative...early markers of career success , such as high USAFA order of merit scores, than whites. The reasons for this are not clear, but the effect builds over...for each of women, African Americans, and Hispanics. 42 Career Success Is Cumulative Methodology: Generalized Boosted Models In addition to

Reducing the Gap between Research and Practice in School Psychology

ERIC Educational Resources Information Center

Kehle, Thomas J.; Bray, Melissa A.

2005-01-01

We argue that the existence of the gap is perhaps a result of an overallegiance to the medical model and the lack of measurable criteria regarding the definition of an educated and psychologically healthy student. Further, an additional and equally daunting problem for school psychological practice is that it is influenced by general education…

Using Generalized Additive Modeling to Empirically Identify Thresholds within the ITERS in Relation to Toddlers' Cognitive Development

ERIC Educational Resources Information Center

Setodji, Claude Messan; Le, Vi-Nhuan; Schaack, Diana

2013-01-01

Research linking high-quality child care programs and children's cognitive development has contributed to the growing popularity of child care quality benchmarking efforts such as quality rating and improvement systems (QRIS). Consequently, there has been an increased interest in and a need for approaches to identifying thresholds, or cutpoints,…

The Effects of Floods on the Incidence of Bacillary Dysentery in Baise (Guangxi Province, China) from 2004 to 2012.

PubMed

Liu, Xuena; Liu, Zhidong; Zhang, Ying; Jiang, Baofa

2017-02-12

Research shows potential effects of floods on intestinal infections. Baise, a city in Guangxi Province (China) had experienced several floods between 2004 and 2012 due to heavy and constant precipitation. This study aimed to examine the relationship between floods and the incidence of bacillary dysentery in Baise. A mixed generalized additive model and Spearman correlation were applied to analyze the relationship between monthly incidence of bacillary dysentery and 14 flood events with two severity levels. Data collected from 2004 to 2010 were utilized to estimate the parameters, whereas data from 2011 to 2012 were used to validate the model. There were in total 9255 cases of bacillary dysentery included in our analyses. According to the mixed generalized additive model, the relative risks (RR) of moderate and severe floods on the incidence of bacillary dysentery were 1.40 (95% confidence interval (CI): 1.16-1.69) and 1.78 (95% CI: 1.61-1.97), respectively. The regression analysis also indicated that the flood duration was negatively associated with the incidence of bacillary dysentery (with RR: 0.57, 95% CI: 0.40-0.86). Therfore, this research suggests that floods exert a significant part in enhancing the risk of bacillary dysentery in Baise. Moreover, severe floods have a higher proportional contribution to the incidence of bacillary dysentery than moderate floods. In addition, short-term floods may contribute more to the incidence of bacillary dysentery than a long-term flood. The findings from this research will provide more evidence to reduce health risks related to floods.

The Effects of Floods on the Incidence of Bacillary Dysentery in Baise (Guangxi Province, China) from 2004 to 2012

PubMed Central

Liu, Xuena; Liu, Zhidong; Zhang, Ying; Jiang, Baofa

2017-01-01

Research shows potential effects of floods on intestinal infections. Baise, a city in Guangxi Province (China) had experienced several floods between 2004 and 2012 due to heavy and constant precipitation. This study aimed to examine the relationship between floods and the incidence of bacillary dysentery in Baise. A mixed generalized additive model and Spearman correlation were applied to analyze the relationship between monthly incidence of bacillary dysentery and 14 flood events with two severity levels. Data collected from 2004 to 2010 were utilized to estimate the parameters, whereas data from 2011 to 2012 were used to validate the model. There were in total 9255 cases of bacillary dysentery included in our analyses. According to the mixed generalized additive model, the relative risks (RR) of moderate and severe floods on the incidence of bacillary dysentery were 1.40 (95% confidence interval (CI): 1.16–1.69) and 1.78 (95% CI: 1.61–1.97), respectively. The regression analysis also indicated that the flood duration was negatively associated with the incidence of bacillary dysentery (with RR: 0.57, 95% CI: 0.40–0.86). Therfore, this research suggests that floods exert a significant part in enhancing the risk of bacillary dysentery in Baise. Moreover, severe floods have a higher proportional contribution to the incidence of bacillary dysentery than moderate floods. In addition, short-term floods may contribute more to the incidence of bacillary dysentery than a long-term flood. The findings from this research will provide more evidence to reduce health risks related to floods. PMID:28208681

Using generalized additive modeling to empirically identify thresholds within the ITERS in relation to toddlers' cognitive development.

PubMed

Setodji, Claude Messan; Le, Vi-Nhuan; Schaack, Diana

2013-04-01

Research linking high-quality child care programs and children's cognitive development has contributed to the growing popularity of child care quality benchmarking efforts such as quality rating and improvement systems (QRIS). Consequently, there has been an increased interest in and a need for approaches to identifying thresholds, or cutpoints, in the child care quality measures used in these benchmarking efforts that differentiate between different levels of children's cognitive functioning. To date, research has provided little guidance to policymakers as to where these thresholds should be set. Using the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) data set, this study explores the use of generalized additive modeling (GAM) as a method of identifying thresholds on the Infant/Toddler Environment Rating Scale (ITERS) in relation to toddlers' performance on the Mental Development subscale of the Bayley Scales of Infant Development (the Bayley Mental Development Scale Short Form-Research Edition, or BMDSF-R). The present findings suggest that simple linear models do not always correctly depict the relationships between ITERS scores and BMDSF-R scores and that GAM-derived thresholds were more effective at differentiating among children's performance levels on the BMDSF-R. Additionally, the present findings suggest that there is a minimum threshold on the ITERS that must be exceeded before significant improvements in children's cognitive development can be expected. There may also be a ceiling threshold on the ITERS, such that beyond a certain level, only marginal increases in children's BMDSF-R scores are observed. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Intercomparison of hydrologic processes in global climate models

NASA Technical Reports Server (NTRS)

Lau, W. K.-M.; Sud, Y. C.; Kim, J.-H.

1995-01-01

In this report, we address the intercomparison of precipitation (P), evaporation (E), and surface hydrologic forcing (P-E) for 23 Atmospheric Model Intercomparison Project (AMIP) general circulation models (GCM's) including relevant observations, over a variety of spatial and temporal scales. The intercomparison includes global and hemispheric means, latitudinal profiles, selected area means for the tropics and extratropics, ocean and land, respectively. In addition, we have computed anomaly pattern correlations among models and observations for different seasons, harmonic analysis for annual and semiannual cycles, and rain-rate frequency distribution. We also compare the joint influence of temperature and precipitation on local climate using the Koeppen climate classification scheme.

Parameter Estimation for Viscoplastic Material Modeling

NASA Technical Reports Server (NTRS)

Saleeb, Atef F.; Gendy, Atef S.; Wilt, Thomas E.

1997-01-01

A key ingredient in the design of engineering components and structures under general thermomechanical loading is the use of mathematical constitutive models (e.g. in finite element analysis) capable of accurate representation of short and long term stress/deformation responses. In addition to the ever-increasing complexity of recent viscoplastic models of this type, they often also require a large number of material constants to describe a host of (anticipated) physical phenomena and complicated deformation mechanisms. In turn, the experimental characterization of these material parameters constitutes the major factor in the successful and effective utilization of any given constitutive model; i.e., the problem of constitutive parameter estimation from experimental measurements.

User's manual for master: Modeling of aerodynamic surfaces by 3-dimensional explicit representation. [input to three dimensional computational fluid dynamics

NASA Technical Reports Server (NTRS)

Gibson, S. G.

1983-01-01

A system of computer programs was developed to model general three dimensional surfaces. Surfaces are modeled as sets of parametric bicubic patches. There are also capabilities to transform coordinates, to compute mesh/surface intersection normals, and to format input data for a transonic potential flow analysis. A graphical display of surface models and intersection normals is available. There are additional capabilities to regulate point spacing on input curves and to compute surface/surface intersection curves. Input and output data formats are described; detailed suggestions are given for user input. Instructions for execution are given, and examples are shown.

A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models

PubMed Central

Rolls, David A.; Wang, Peng; McBryde, Emma; Pattison, Philippa; Robins, Garry

2015-01-01

We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a “hidden population”. In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure. PMID:26555701

An information maximization model of eye movements

NASA Technical Reports Server (NTRS)

Renninger, Laura Walker; Coughlan, James; Verghese, Preeti; Malik, Jitendra

2005-01-01

We propose a sequential information maximization model as a general strategy for programming eye movements. The model reconstructs high-resolution visual information from a sequence of fixations, taking into account the fall-off in resolution from the fovea to the periphery. From this framework we get a simple rule for predicting fixation sequences: after each fixation, fixate next at the location that minimizes uncertainty (maximizes information) about the stimulus. By comparing our model performance to human eye movement data and to predictions from a saliency and random model, we demonstrate that our model is best at predicting fixation locations. Modeling additional biological constraints will improve the prediction of fixation sequences. Our results suggest that information maximization is a useful principle for programming eye movements.

Effective field theory of integrating out sfermions in the MSSM: Complete one-loop analysis

NASA Astrophysics Data System (ADS)

Huo, Ran

2018-04-01

We apply the covariant derivative expansion of the Coleman-Weinberg potential to the sfermion sector in the minimal supersymmetric standard model, matching it to the relevant dimension-6 operators in the standard model effective field theory at one-loop level. Emphasis is paid to nondegenerate large soft supersymmetry breaking mass squares, and the most general analytical Wilson coefficients are obtained for all pure bosonic dimension-6 operators. In addition to the non-logarithmic contributions, they generally have another logarithmic contributions. Various numerical results are shown, in particular the constraints in the large Xt branch reproducing the 125 GeV Higgs mass can be pushed to high values to almost completely probe the low stop mass region at the future FCC-ee experiment, even given the Higgs mass calculation uncertainty.

On classical and quantum dynamics of tachyon-like fields and their cosmological implications

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

Dimitrijević, Dragoljub D., E-mail: ddrag@pmf.ni.ac.rs; Djordjević, Goran S., E-mail: ddrag@pmf.ni.ac.rs; Milošević, Milan, E-mail: ddrag@pmf.ni.ac.rs

2014-11-24

We consider a class of tachyon-like potentials, motivated by string theory, D-brane dynamics and inflation theory in the context of classical and quantum mechanics. A formalism for describing dynamics of tachyon fields in spatially homogenous and one-dimensional - classical and quantum mechanical limit is proposed. A few models with concrete potentials are considered. Additionally, possibilities for p-adic and adelic generalization of these models are discussed. Classical actions and corresponding quantum propagators, in the Feynman path integral approach, are calculated in a form invariant on a change of the background number fields, i.e. on both archimedean and nonarchimedean spaces. Looking formore » a quantum origin of inflation, relevance of p-adic and adelic generalizations are briefly discussed.« less

Teaching Functional Play Skills to a Young Child with Autism Spectrum Disorder through Video Self-Modeling.

PubMed

Lee, Sharon Y; Lo, Ya-Yu; Lo, Yafen

2017-08-01

The researchers used a single-case, multiple probe design across three sets of toys (i.e., farm toy, doctor's clinic toy, and rescue toy) to examine the effects of video self-modeling (VSM) on the functional play skills of a 5-year-old child with autism spectrum disorder. The findings showed a functional relation between VSM and increased percentages of functional play actions across the toy sets. The participant's percentages of the targeted functional play skills for the intervention toys remained high 1 week and 2 weeks after the intervention ceased. Additionally, preliminary generalization results showed slight improvement in the percentages of functional play actions with the generalization toys that were not directly taught. Limitations, practical implications, and directions for future research are discussed.

Automatic liver segmentation in computed tomography using general-purpose shape modeling methods.

PubMed

Spinczyk, Dominik; Krasoń, Agata

2018-05-29

Liver segmentation in computed tomography is required in many clinical applications. The segmentation methods used can be classified according to a number of criteria. One important criterion for method selection is the shape representation of the segmented organ. The aim of the work is automatic liver segmentation using general purpose shape modeling methods. As part of the research, methods based on shape information at various levels of advancement were used. The single atlas based segmentation method was used as the simplest shape-based method. This method is derived from a single atlas using the deformable free-form deformation of the control point curves. Subsequently, the classic and modified Active Shape Model (ASM) was used, using medium body shape models. As the most advanced and main method generalized statistical shape models, Gaussian Process Morphable Models was used, which are based on multi-dimensional Gaussian distributions of the shape deformation field. Mutual information and sum os square distance were used as similarity measures. The poorest results were obtained for the single atlas method. For the ASM method in 10 analyzed cases for seven test images, the Dice coefficient was above 55[Formula: see text], of which for three of them the coefficient was over 70[Formula: see text], which placed the method in second place. The best results were obtained for the method of generalized statistical distribution of the deformation field. The DICE coefficient for this method was 88.5[Formula: see text] CONCLUSIONS: This value of 88.5 [Formula: see text] Dice coefficient can be explained by the use of general-purpose shape modeling methods with a large variance of the shape of the modeled object-the liver and limitations on the size of our training data set, which was limited to 10 cases. The obtained results in presented fully automatic method are comparable with dedicated methods for liver segmentation. In addition, the deforamtion features of the model can be modeled mathematically by using various kernel functions, which allows to segment the liver on a comparable level using a smaller learning set.

Modelling the standing timber volume of Baden-Württemberg-A large-scale approach using a fusion of Landsat, airborne LiDAR and National Forest Inventory data

NASA Astrophysics Data System (ADS)

Maack, Joachim; Lingenfelder, Marcus; Weinacker, Holger; Koch, Barbara

2016-07-01

Remote sensing-based timber volume estimation is key for modelling the regional potential, accessibility and price of lignocellulosic raw material for an emerging bioeconomy. We used a unique wall-to-wall airborne LiDAR dataset and Landsat 7 satellite images in combination with terrestrial inventory data derived from the National Forest Inventory (NFI), and applied generalized additive models (GAM) to estimate spatially explicit timber distribution and volume in forested areas. Since the NFI data showed an underlying structure regarding size and ownership, we additionally constructed a socio-economic predictor to enhance the accuracy of the analysis. Furthermore, we balanced the training dataset with a bootstrap method to achieve unbiased regression weights for interpolating timber volume. Finally, we compared and discussed the model performance of the original approach (r2 = 0.56, NRMSE = 9.65%), the approach with balanced training data (r2 = 0.69, NRMSE = 12.43%) and the final approach with balanced training data and the additional socio-economic predictor (r2 = 0.72, NRMSE = 12.17%). The results demonstrate the usefulness of remote sensing techniques for mapping timber volume for a future lignocellulose-based bioeconomy.

Effective Simulation Strategy of Multiscale Flows using a Lattice Boltzmann model with a Stretched Lattice

NASA Astrophysics Data System (ADS)

Yahia, Eman; Premnath, Kannan

2017-11-01

Resolving multiscale flow physics (e.g. for boundary layer or mixing layer flows) effectively generally requires the use of different grid resolutions in different coordinate directions. Here, we present a new formulation of a multiple relaxation time (MRT)-lattice Boltzmann (LB) model for anisotropic meshes. It is based on a simpler and more stable non-orthogonal moment basis while the use of MRT introduces additional flexibility, and the model maintains a stream-collide procedure; its second order moment equilibria are augmented with additional velocity gradient terms dependent on grid aspect ratio that fully restores the required isotropy of the transport coefficients of the normal and shear stresses. Furthermore, by introducing additional cubic velocity corrections, it maintains Galilean invariance. The consistency of this stretched lattice based LB scheme with the Navier-Stokes equations is shown via a Chapman-Enskog expansion. Numerical study for a variety of benchmark flow problems demonstrate its ability for accurate and effective simulations at relatively high Reynolds numbers. The MRT-LB scheme is also shown to be more stable compared to prior LB models for rectangular grids, even for grid aspect ratios as small as 0.1 and for Reynolds numbers of 10000.

Modeling mountain pine beetle habitat suitability within Sequoia National Park

NASA Astrophysics Data System (ADS)

Nguyen, Andrew

Understanding significant changes in climate and their effects on timber resources can help forest managers make better decisions regarding the preservation of natural resources and land management. These changes may to alter natural ecosystems dependent on historical and current climate conditions. Increasing mountain pine beetle (MBP) outbreaks within the southern Sierra Nevada are the result of these alterations. This study better understands MPB behavior within Sequoia National Park (SNP) and model its current and future habitat distribution. Variables contributing to MPB spread are vegetation stress, soil moisture, temperature, precipitation, disturbance, and presence of Ponderosa (Pinus ponderosa) and Lodgepole (Pinus contorta) pine trees. These variables were obtained using various modeled, insitu, and remotely sensed sources. The generalized additive model (GAM) was used to calculate the statistical significance of each variable contributing to MPB spread and also created maps identifying habitat suitability. Results indicate vegetation stress and forest disturbance to be variables most indicative of MPB spread. Additionally, the model was able to detect habitat suitability of MPB with a 45% accuracy concluding that a geospatial driven modeling approach can be used to delineate potential MPB spread within SNP.

Do Responses to Different Anthropogenic Forcings Add Linearly in Climate Models?

NASA Technical Reports Server (NTRS)

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; Bonfils, Celine; LeGrande, Allegra N.; Nazarenko, Larissa; Tsigaridis, Kostas

2015-01-01

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings; however, we demonstrate that there are significant nonlinearities in precipitation responses to di?erent forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to di?erences in ozone forcing arising from interactions between forcing agents. Our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.

Do responses to different anthropogenic forcings add linearly in climate models?

DOE PAGES

Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; ...

2015-10-14

Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM4) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings. However,more » we demonstrate that there are significant nonlinearities in precipitation responses to different forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to differences in ozone forcing arising from interactions between forcing agents. Lastly, our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.« less

Global dust model intercomparison in AeroCom phase I

NASA Astrophysics Data System (ADS)

Huneeus, N.; Schulz, M.; Balkanski, Y.; Griesfeller, J.; Prospero, J.; Kinne, S.; Bauer, S.; Boucher, O.; Chin, M.; Dentener, F.; Diehl, T.; Easter, R.; Fillmore, D.; Ghan, S.; Ginoux, P.; Grini, A.; Horowitz, L.; Koch, D.; Krol, M. C.; Landing, W.; Liu, X.; Mahowald, N.; Miller, R.; Morcrette, J.-J.; Myhre, G.; Penner, J.; Perlwitz, J.; Stier, P.; Takemura, T.; Zender, C. S.

2011-08-01

This study presents the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations related to desert dust aerosols, their direct radiative effect, and their impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angström exponent (AE), coarse mode AOD and dust surface concentrations are included to extend the assessment of model performance and to identify common biases present in models. These data comprise a benchmark dataset that is proposed for model inspection and future dust model development. There are large differences among the global models that simulate the dust cycle and its impact on climate. In general, models simulate the climatology of vertically integrated parameters (AOD and AE) within a factor of two whereas the total deposition and surface concentration are reproduced within a factor of 10. In addition, smaller mean normalized bias and root mean square errors are obtained for the climatology of AOD and AE than for total deposition and surface concentration. Characteristics of the datasets used and their uncertainties may influence these differences. Large uncertainties still exist with respect to the deposition fluxes in the southern oceans. Further measurements and model studies are necessary to assess the general model performance to reproduce dust deposition in ocean regions sensible to iron contributions. Models overestimate the wet deposition in regions dominated by dry deposition. They generally simulate more realistic surface concentration at stations downwind of the main sources than at remote ones. Most models simulate the gradient in AOD and AE between the different dusty regions. However the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models simulate the offshore transport of West Africa throughout the year but they overestimate the AOD and they transport too fine particles. The models also reproduce the dust transport across the Atlantic in the summer in terms of both AOD and AE but not so well in winter-spring nor the southward displacement of the dust cloud that is responsible of the dust transport into South America. Based on the dependency of AOD on aerosol burden and size distribution we use model bias with respect to AOD and AE to infer the bias of the dust emissions in Africa and the Middle East. According to this analysis we suggest that a range of possible emissions for North Africa is 400 to 2200 Tg yr-1 and in the Middle East 26 to 526 Tg yr-1.

Adaptability-what it is and what it is not: Comment on Chandra and Leong (2016).

PubMed

Martin, Andrew J

2017-10-01

Chandra and Leong (2016) propose a new model of adaptability: the diversified portfolio model (DPM) of adaptability. Further thought and research on adaptability is a welcome addition to the limited body of work conducted on this topic to date. However, in their discussion there is a lack of definitional clarity, and there is frequent conflation of adaptability and resilience. It is also the case that the hypothesized adaptability model is general and could apply to many psychological constructs and processes (not just adaptability). In addition, there are gaps in research suggested by the authors that have been addressed by other researchers and there is a good deal of contemporary adaptability research that is not cited. Addressing these limitations in future work is vital to the further development of theory, research, and practice in the area of adaptability. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Connections between survey calibration estimators and semiparametric models for incomplete data

PubMed Central

Lumley, Thomas; Shaw, Pamela A.; Dai, James Y.

2012-01-01

Survey calibration (or generalized raking) estimators are a standard approach to the use of auxiliary information in survey sampling, improving on the simple Horvitz–Thompson estimator. In this paper we relate the survey calibration estimators to the semiparametric incomplete-data estimators of Robins and coworkers, and to adjustment for baseline variables in a randomized trial. The development based on calibration estimators explains the ‘estimated weights’ paradox and provides useful heuristics for constructing practical estimators. We present some examples of using calibration to gain precision without making additional modelling assumptions in a variety of regression models. PMID:23833390

Stability of a general mixed additive-cubic functional equation in non-Archimedean fuzzy normed spaces

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

Xu Tianzhou; Rassias, John Michael; Xu Wanxin

2010-09-15

We establish some stability results concerning the general mixed additive-cubic functional equation in non-Archimedean fuzzy normed spaces. In addition, we establish some results of approximately general mixed additive-cubic mappings in non-Archimedean fuzzy normed spaces. The results improve and extend some recent results.

Development and validation of age-dependent FE human models of a mid-sized male thorax.

PubMed

El-Jawahri, Raed E; Laituri, Tony R; Ruan, Jesse S; Rouhana, Stephen W; Barbat, Saeed D

2010-11-01

The increasing number of people over 65 years old (YO) is an important research topic in the area of impact biomechanics, and finite element (FE) modeling can provide valuable support for related research. There were three objectives of this study: (1) Estimation of the representative age of the previously-documented Ford Human Body Model (FHBM) -- an FE model which approximates the geometry and mass of a mid-sized male, (2) Development of FE models representing two additional ages, and (3) Validation of the resulting three models to the extent possible with respect to available physical tests. Specifically, the geometry of the model was compared to published data relating rib angles to age, and the mechanical properties of different simulated tissues were compared to a number of published aging functions. The FHBM was determined to represent a 53-59 YO mid-sized male. The aforementioned aging functions were used to develop FE models representing two additional ages: 35 and 75 YO. The rib model was validated against human rib specimens and whole rib tests, under different loading conditions, with and without modeled fracture. In addition, the resulting three age-dependent models were validated by simulating cadaveric tests of blunt and sled impacts. The responses of the models, in general, were within the cadaveric response corridors. When compared to peak responses from individual cadavers similar in size and age to the age-dependent models, some responses were within one standard deviation of the test data. All the other responses, but one, were within two standard deviations.

Non Abelian T-duality in Gauged Linear Sigma Models

NASA Astrophysics Data System (ADS)

Bizet, Nana Cabo; Martínez-Merino, Aldo; Zayas, Leopoldo A. Pando; Santos-Silva, Roberto

2018-04-01

Abelian T-duality in Gauged Linear Sigma Models (GLSM) forms the basis of the physical understanding of Mirror Symmetry as presented by Hori and Vafa. We consider an alternative formulation of Abelian T-duality on GLSM's as a gauging of a global U(1) symmetry with the addition of appropriate Lagrange multipliers. For GLSMs with Abelian gauge groups and without superpotential we reproduce the dual models introduced by Hori and Vafa. We extend the construction to formulate non-Abelian T-duality on GLSMs with global non-Abelian symmetries. The equations of motion that lead to the dual model are obtained for a general group, they depend in general on semi-chiral superfields; for cases such as SU(2) they depend on twisted chiral superfields. We solve the equations of motion for an SU(2) gauged group with a choice of a particular Lie algebra direction of the vector superfield. This direction covers a non-Abelian sector that can be described by a family of Abelian dualities. The dual model Lagrangian depends on twisted chiral superfields and a twisted superpotential is generated. We explore some non-perturbative aspects by making an Ansatz for the instanton corrections in the dual theories. We verify that the effective potential for the U(1) field strength in a fixed configuration on the original theory matches the one of the dual theory. Imposing restrictions on the vector superfield, more general non-Abelian dual models are obtained. We analyze the dual models via the geometry of their susy vacua.

Effects of anisotropy on the two-dimensional inversion procedure

NASA Astrophysics Data System (ADS)

Heise, Wiebke; Pous, Jaume

2001-12-01

In this paper we show some of the effects that appear in magnetotelluric measurements over 2-D anisotropic structures, and propose a procedure to recover the anisotropy using 2-D inversion algorithms for isotropic models. First, we see how anisotropy affects the usual interpretation steps: dimensionality analysis and 2-D inversion. Two models containing general 2-D azimuthal anisotropic features were chosen to illustrate this approach: an anisotropic block and an anisotropic layer, both forming part of general 2-D models. In addition, a third model with dipping anisotropy was studied. For each model we examined the influence of various anisotropy strikes and resistivity contrasts on the dimensionality analysis and on the behaviour of the induction arrows. We found that, when the anisotropy ratio is higher than five, even if the strike is frequency-dependent it is possible to decide on a direction close to the direction of anisotropy. Then, if the data are rotated to this angle, a 2-D inversion reproduces the anisotropy reasonably well by means of macro-anisotropy. This strategy was tested on field data where anisotropy had been previously recognized.

Combined sphere-spheroid particle model for the retrieval of the microphysical aerosol parameters via regularized inversion of lidar data

NASA Astrophysics Data System (ADS)

Samaras, Stefanos; Böckmann, Christine; Nicolae, Doina

2016-06-01

In this work we propose a two-step advancement of the Mie spherical-particle model accounting for particle non-sphericity. First, a naturally two-dimensional (2D) generalized model (GM) is made, which further triggers analogous 2D re-definitions of microphysical parameters. We consider a spheroidal-particle approach where the size distribution is additionally dependent on aspect ratio. Second, we incorporate the notion of a sphere-spheroid particle mixture (PM) weighted by a non-sphericity percentage. The efficiency of these two models is investigated running synthetic data retrievals with two different regularization methods to account for the inherent instability of the inversion procedure. Our preliminary studies show that a retrieval with the PM model improves the fitting errors and the microphysical parameter retrieval and it has at least the same efficiency as the GM. While the general trend of the initial size distributions is captured in our numerical experiments, the reconstructions are subject to artifacts. Finally, our approach is applied to a measurement case yielding acceptable results.

Assessment of corneal properties based on statistical modeling of OCT speckle

PubMed Central

Jesus, Danilo A.; Iskander, D. Robert

2016-01-01

A new approach to assess the properties of the corneal micro-structure in vivo based on the statistical modeling of speckle obtained from Optical Coherence Tomography (OCT) is presented. A number of statistical models were proposed to fit the corneal speckle data obtained from OCT raw image. Short-term changes in corneal properties were studied by inducing corneal swelling whereas age-related changes were observed analyzing data of sixty-five subjects aged between twenty-four and seventy-three years. Generalized Gamma distribution has shown to be the best model, in terms of the Akaike’s Information Criterion, to fit the OCT corneal speckle. Its parameters have shown statistically significant differences (Kruskal-Wallis, p < 0.001) for short and age-related corneal changes. In addition, it was observed that age-related changes influence the corneal biomechanical behaviour when corneal swelling is induced. This study shows that Generalized Gamma distribution can be utilized to modeling corneal speckle in OCT in vivo providing complementary quantified information where micro-structure of corneal tissue is of essence. PMID:28101409

Secondary Gravity Waves in the Winter Mesosphere: Results From a High-Resolution Global Circulation Model

NASA Astrophysics Data System (ADS)

Becker, Erich; Vadas, Sharon L.

2018-03-01

This study analyzes a new high-resolution general circulation model with regard to secondary gravity waves in the mesosphere during austral winter. The model resolves gravity waves down to horizontal and vertical wavelengths of 165 and 1.5 km, respectively. The resolved mean wave drag agrees well with that from a conventional model with parameterized gravity waves up to the midmesosphere in winter and up to the upper mesosphere in summer. About half of the zonal-mean vertical flux of westward momentum in the southern winter stratosphere is due to orographic gravity waves. The high intermittency of the primary orographic gravity waves gives rise to secondary waves that result in a substantial eastward drag in the winter mesopause region. This induces an additional eastward maximum of the mean zonal wind at z ˜ 100 km. Radar and lidar measurements at polar latitudes and results from other high-resolution global models are consistent with this finding. Hence, secondary gravity waves may play a significant role in the general circulation of the winter mesopause region.

An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

PubMed

Matsubara, Takashi; Torikai, Hiroyuki

2016-04-01

Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources.

Influence of Wind Model Performance on Wave Forecasts of the Naval Oceanographic Office

NASA Astrophysics Data System (ADS)

Gay, P. S.; Edwards, K. L.

2017-12-01

Significant discrepancies between the Naval Oceanographic Office's significant wave height (SWH) predictions and observations have been noted in some model domains. The goal of this study is to evaluate these discrepancies and identify to what extent inaccuracies in the wind predictions may explain inaccuracies in SWH predictions. A one-year time series of data is evaluated at various locations in Southern California and eastern Florida. Correlations are generally quite good, ranging from 73% at Pendleton to 88% at both Santa Barbara, California, and Cape Canaveral, Florida. Correlations for month-long periods off Southern California drop off significantly in late spring through early autumn - less so off eastern Florida - likely due to weaker local wind seas and generally smaller SWH in addition to the influence of remotely-generated swell, which may not propagate accurately into and through the wave models. The results of this study suggest that it is likely that a change in meteorological and/or oceanographic conditions explains the change in model performance, partially as a result of a seasonal reduction in wind model performance in the summer months.

PALM-USM v1.0: A new urban surface model integrated into the PALM large-eddy simulation model

NASA Astrophysics Data System (ADS)

Resler, Jaroslav; Krč, Pavel; Belda, Michal; Juruš, Pavel; Benešová, Nina; Lopata, Jan; Vlček, Ondřej; Damašková, Daša; Eben, Kryštof; Derbek, Přemysl; Maronga, Björn; Kanani-Sühring, Farah

2017-10-01

Urban areas are an important part of the climate system and many aspects of urban climate have direct effects on human health and living conditions. This implies that reliable tools for local urban climate studies supporting sustainable urban planning are needed. However, a realistic implementation of urban canopy processes still poses a serious challenge for weather and climate modelling for the current generation of numerical models. To address this demand, a new urban surface model (USM), describing the surface energy processes for urban environments, was developed and integrated as a module into the PALM large-eddy simulation model. The development of the presented first version of the USM originated from modelling the urban heat island during summer heat wave episodes and thus implements primarily processes important in such conditions. The USM contains a multi-reflection radiation model for shortwave and longwave radiation with an integrated model of absorption of radiation by resolved plant canopy (i.e. trees, shrubs). Furthermore, it consists of an energy balance solver for horizontal and vertical impervious surfaces, and thermal diffusion in ground, wall, and roof materials, and it includes a simple model for the consideration of anthropogenic heat sources. The USM was parallelized using the standard Message Passing Interface and performance testing demonstrates that the computational costs of the USM are reasonable on typical clusters for the tested configurations. The module was fully integrated into PALM and is available via its online repository under the GNU General Public License (GPL). The USM was tested on a summer heat-wave episode for a selected Prague crossroads. The general representation of the urban boundary layer and patterns of surface temperatures of various surface types (walls, pavement) are in good agreement with in situ observations made in Prague. Additional simulations were performed in order to assess the sensitivity of the results to uncertainties in the material parameters, the domain size, and the general effect of the USM itself. The first version of the USM is limited to the processes most relevant to the study of summer heat waves and serves as a basis for ongoing development which will address additional processes of the urban environment and lead to improvements to extend the utilization of the USM to other environments and conditions.

Mixture toxicity of six sulfonamides and their two transformation products to green algae Scenedesmus vacuolatus and duckweed Lemna minor.

PubMed

Białk-Bielińska, Anna; Caban, Magda; Pieczyńska, Aleksandra; Stepnowski, Piotr; Stolte, Stefan

2017-04-01

Since humans and ecosystems are continually exposed to a very complex and permanently changing mixture of chemicals, there is increasing concern in the general public about the potential adverse effects they may cause. Among all "emerging pollutants", pharmaceuticals in particular have raised great environmental concern. For these reasons the aim of our study was to evaluate the mixture toxicity of six antimicrobial sulfonamides (SAs) and their two most commonly identified degradation products - sulfanilic acid (SNA) and sulfanilamide (SN) - to limnic green algae Scenedesmus vacuolatus and duckweed Lemna minor. The ecotoxicological data for the single toxicity of SNA and SN towards selected organisms are presented. The concept of Concentration Addition (CA) was applied to estimate the effects, and less than additive effects were observed. In general terms, it seems sufficiently precautionary for the aquatic environment to consider the toxicity of a sulfonamide mixture as additive. The Concentration Addition model proves to be a reasonable worst-case estimation. Such a comparative study on the mixture toxicity of sulfonamides and their transformation products has been presented for the first time. Copyright © 2017 Elsevier Ltd. All rights reserved.

Equations of state for hydrogen and deuterium.

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

Kerley, Gerald Irwin

2003-12-01

This report describes the complete revision of a deuterium equation of state (EOS) model published in 1972. It uses the same general approach as the 1972 EOS, i.e., the so-called 'chemical model,' but incorporates a number of theoretical advances that have taken place during the past thirty years. Three phases are included: a molecular solid, an atomic solid, and a fluid phase consisting of both molecular and atomic species. Ionization and the insulator-metal transition are also included. The most important improvements are in the liquid perturbation theory, the treatment of molecular vibrations and rotations, and the ionization equilibrium and mixturemore » models. In addition, new experimental data and theoretical calculations are used to calibrate certain model parameters, notably the zero-Kelvin isotherms for the molecular and atomic solids, and the quantum corrections to the liquid phase. The report gives a general overview of the model, followed by detailed discussions of the most important theoretical issues and extensive comparisons with the many experimental data that have been obtained during the last thirty years. Questions about the validity of the chemical model are also considered. Implications for modeling the 'giant planets' are also discussed.« less

A general model to explore complex dominance patterns in plant sporophytic self-incompatibility systems.

PubMed

Billiard, Sylvain; Castric, Vincent; Vekemans, Xavier

2007-03-01

We developed a general model of sporophytic self-incompatibility under negative frequency-dependent selection allowing complex patterns of dominance among alleles. We used this model deterministically to investigate the effects on equilibrium allelic frequencies of the number of dominance classes, the number of alleles per dominance class, the asymmetry in dominance expression between pollen and pistil, and whether selection acts on male fitness only or both on male and on female fitnesses. We show that the so-called "recessive effect" occurs under a wide variety of situations. We found emerging properties of finite population models with several alleles per dominance class such as that higher numbers of alleles are maintained in more dominant classes and that the number of dominance classes can evolve. We also investigated the occurrence of homozygous genotypes and found that substantial proportions of those can occur for the most recessive alleles. We used the model for two species with complex dominance patterns to test whether allelic frequencies in natural populations are in agreement with the distribution predicted by our model. We suggest that the model can be used to test explicitly for additional, allele-specific, selective forces.

Exotic singularities and spatially curved loop quantum cosmology

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

Singh, Parampreet; Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Waterloo, Ontario N2L 2Y5; Vidotto, Francesca

2011-03-15

We investigate the occurrence of various exotic spacelike singularities in the past and the future evolution of k={+-}1 Friedmann-Robertson-Walker model and loop quantum cosmology using a sufficiently general phenomenological model for the equation of state. We highlight the nontrivial role played by the intrinsic curvature for these singularities and the new physics which emerges at the Planck scale. We show that quantum gravity effects generically resolve all strong curvature singularities including big rip and big freeze singularities. The weak singularities, which include sudden and big brake singularities, are ignored by quantum gravity when spatial curvature is negative, as was previouslymore » found for the spatially flat model. Interestingly, for the spatially closed model there exist cases where weak singularities may be resolved when they occur in the past evolution. The spatially closed model exhibits another novel feature. For a particular class of equation of state, this model also exhibits an additional physical branch in loop quantum cosmology, a baby universe separated from the parent branch. Our analysis generalizes previous results obtained on the resolution of strong curvature singularities in flat models to isotropic spacetimes with nonzero spatial curvature.« less

BUMPER: the Bayesian User-friendly Model for Palaeo-Environmental Reconstruction

NASA Astrophysics Data System (ADS)

Holden, Phil; Birks, John; Brooks, Steve; Bush, Mark; Hwang, Grace; Matthews-Bird, Frazer; Valencia, Bryan; van Woesik, Robert

2017-04-01

We describe the Bayesian User-friendly Model for Palaeo-Environmental Reconstruction (BUMPER), a Bayesian transfer function for inferring past climate and other environmental variables from microfossil assemblages. The principal motivation for a Bayesian approach is that the palaeoenvironment is treated probabilistically, and can be updated as additional data become available. Bayesian approaches therefore provide a reconstruction-specific quantification of the uncertainty in the data and in the model parameters. BUMPER is fully self-calibrating, straightforward to apply, and computationally fast, requiring 2 seconds to build a 100-taxon model from a 100-site training-set on a standard personal computer. We apply the model's probabilistic framework to generate thousands of artificial training-sets under ideal assumptions. We then use these to demonstrate both the general applicability of the model and the sensitivity of reconstructions to the characteristics of the training-set, considering assemblage richness, taxon tolerances, and the number of training sites. We demonstrate general applicability to real data, considering three different organism types (chironomids, diatoms, pollen) and different reconstructed variables. In all of these applications an identically configured model is used, the only change being the input files that provide the training-set environment and taxon-count data.

Decision-case mix model for analyzing variation in cesarean rates.

PubMed

Eldenburg, L; Waller, W S

2001-01-01

This article contributes a decision-case mix model for analyzing variation in c-section rates. Like recent contributions to the literature, the model systematically takes into account the effect of case mix. Going beyond past research, the model highlights differences in physician decision making in response to obstetric factors. Distinguishing the effects of physician decision making and case mix is important in understanding why c-section rates vary and in developing programs to effect change in physician behavior. The model was applied to a sample of deliveries at a hospital where physicians exhibited considerable variation in their c-section rates. Comparing groups with a low versus high rate, the authors' general conclusion is that the difference in physician decision tendencies (to perform a c-section), in response to specific obstetric factors, is at least as important as case mix in explaining variation in c-section rates. The exact effects of decision making versus case mix depend on how the model application defines the obstetric condition of interest and on the weighting of deliveries by their estimated "risk of Cesarean." The general conclusion is supported by an additional analysis that uses the model's elements to predict individual physicians' annual c-section rates.

Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model

NASA Astrophysics Data System (ADS)

Acevedo, Walter; Fallah, Bijan; Reich, Sebastian; Cubasch, Ulrich

2017-05-01

Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in the model. This result might help the dendrochronology community to optimize their sampling efforts.

A qualitative study of patient experiences of Type 2 Diabetes care delivered comparatively by General Practice Nurses and Medical Practitioners.

PubMed

Boyle, Eileen; Saunders, Rosemary; Drury, Vicki

2016-07-01

To explore patient experiences of type 2 diabetes mellitus care delivered by general practice nurses in collaboration with the general practitioner. Australian general practice nurses are expanding their role in multidisciplinary type 2 diabetes care with limited research on patient perceptions of care provision within this collaborative model. Qualitative interpretive. Purposeful sampling was used to invite the patients (n = 10). Data were collected from semi-structured face-to-face interviews. Braun and Clarke's () inductive coding thematic analysis process was used to interpret the data. All participants experienced their General Practice Nurse consultation as a clinical assessment for their General Practitioner. While they appreciated the extra time with the General Practice Nurse, they were unsure of the purpose of the consultation beyond clinical assessment. They described the ongoing challenge of living with T2DM and identified a need for additional information and advice. The results suggest that the model of general practice nurse type 2 diabetes care has an important role to play in the delivery of effective ongoing care of patients. However, this role requires further development to ensure that it is understood by the patients as a role that not only conducts clinical assessments but also provides relevant education and self-management support as part of a collaborative approach to care delivery with General Practitioners. The findings are relevant to primary health care clinicians providing diabetes care to inform more relevant supportive care by general practice nurses. © 2016 John Wiley & Sons Ltd.

Improvement in precipitation-runoff model simulations by recalibration with basin-specific data, and subsequent model applications, Onondaga Lake Basin, Onondaga County, New York

USGS Publications Warehouse

Coon, William F.

2011-01-01

Simulation of streamflows in small subbasins was improved by adjusting model parameter values to match base flows, storm peaks, and storm recessions more precisely than had been done with the original model. Simulated recessional and low flows were either increased or decreased as appropriate for a given stream, and simulated peak flows generally were lowered in the revised model. The use of suspended-sediment concentrations rather than concentrations of the surrogate constituent, total suspended solids, resulted in increases in the simulated low-flow sediment concentrations and, in most cases, decreases in the simulated peak-flow sediment concentrations. Simulated orthophosphate concentrations in base flows generally increased but decreased for peak flows in selected headwater subbasins in the revised model. Compared with the original model, phosphorus concentrations simulated by the revised model were comparable in forested subbasins, generally decreased in developed and wetland-dominated subbasins, and increased in agricultural subbasins. A final revision to the model was made by the addition of the simulation of chloride (salt) concentrations in the Onondaga Creek Basin to help water-resource managers better understand the relative contributions of salt from multiple sources in this particular tributary. The calibrated revised model was used to (1) compute loading rates for the various land types that were simulated in the model, (2) conduct a watershed-management analysis that estimated the portion of the total load that was likely to be transported to Onondaga Lake from each of the modeled subbasins, (3) compute and assess chloride loads to Onondaga Lake from the Onondaga Creek Basin, and (4) simulate precolonization (forested) conditions in the basin to estimate the probable minimum phosphorus loads to the lake.

Bayesian inference of uncertainties in precipitation-streamflow modeling in a snow affected catchment

NASA Astrophysics Data System (ADS)

Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.

2012-11-01

Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.

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

Frusciante, Noemi; Papadomanolakis, Georgios; Silvestri, Alessandra, E-mail: fruscian@iap.fr, E-mail: papadomanolakis@lorentz.leidenuniv.nl, E-mail: silvestri@lorentz.leidenuniv.nl

We present a generalization of the effective field theory (EFT) formalism for dark energy and modified gravity models to include operators with higher order spatial derivatives. This allows the extension of the EFT framework to a wider class of gravity theories such as Hořava gravity. We present the corresponding extended action, both in the EFT and the Arnowitt-Deser-Misner (ADM) formalism, and proceed to work out a convenient mapping between the two, providing a self contained and general procedure to translate a given model of gravity into the EFT language at the basis of the Einstein-Boltzmann solver EFTCAMB. Putting this mappingmore » at work, we illustrate, for several interesting models of dark energy and modified gravity, how to express them in the ADM notation and then map them into the EFT formalism. We also provide for the first time, the full mapping of GLPV models into the EFT framework. We next perform a thorough analysis of the physical stability of the generalized EFT action, in absence of matter components. We work out viability conditions that correspond to the absence of ghosts and modes that propagate with a negative speed of sound in the scalar and tensor sector, as well as the absence of tachyonic modes in the scalar sector. Finally, we extend and generalize the phenomenological basis in terms of α-functions introduced to parametrize Horndeski models, to cover all theories with higher order spatial derivatives included in our extended action. We elaborate on the impact of the additional functions on physical quantities, such as the kinetic term and the speeds of propagation for scalar and tensor modes.« less

Bifactor structure of the Wechsler Preschool and Primary Scale of Intelligence--Fourth Edition.

PubMed

Watkins, Marley W; Beaujean, A Alexander

2014-03-01

The Wechsler Preschool and Primary Scale of Intelligence--Fourth Edition (WPPSI-IV; Wechsler, 2012) represents a substantial departure from its predecessor, including omission of 4 subtests, addition of 5 new subtests, and modification of the contents of the 5 retained subtests. Wechsler (2012) explicitly assumed a higher-order structure with general intelligence (g) as the second-order factor that explained all the covariation of several first-order factors but failed to consider a bifactor model. The WPPSI-IV normative sample contains 1,700 children aged 2 years and 6 months through 7 years and 7 months, bifurcated into 2 age groups: 2:6-3:11 year olds (n = 600) and 4:0-7:7 year olds (n = 1,100). This study applied confirmatory factor analysis to the WPPSI-IV normative sample data to test the fit of a bifactor model and to determine the reliability of the resulting factors. The bifactor model fit the WPPSI-IV normative sample data as well as or better than the higher-order models favored by Wechsler (2012). In the bifactor model, the general factor accounted for more variance in every subtest than did its corresponding domain-specific factor and the general factor accounted for more total and common variance than all domain-specific factors combined. Further, the domain-specific factors exhibited poor reliability independent of g (i.e., ωh coefficients of .05 to .33). These results suggest that only the general intelligence dimension was sufficiently robust and precise for clinical use. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Generalization of the Förster resonance energy transfer theory for quantum mechanical modulation of the donor-acceptor coupling

NASA Astrophysics Data System (ADS)

Jang, Seogjoo

2007-11-01

The Förster resonance energy transfer theory is generalized for inelastic situations with quantum mechanical modulation of the donor-acceptor coupling. Under the assumption that the modulations are independent of the electronic excitation of the donor and the acceptor, a general rate expression is derived, which involves two dimensional frequency-domain convolution of the donor emission line shape, the acceptor absorption line shape, and the spectral density of the modulation of the donor-acceptor coupling. For two models of modulation, detailed rate expressions are derived. The first model is the fluctuation of the donor-acceptor distance, approximated as a quantum harmonic oscillator coupled to a bath of other quantum harmonic oscillators. The distance fluctuation results in additional terms in the rate, which in the small fluctuation limit depend on the inverse eighth power of the donor-acceptor distance. The second model is the fluctuation of the torsional angle between the two transition dipoles, which is modeled as a quantum harmonic oscillator coupled to a bath of quantum harmonic oscillators and causes sinusoidal modulation of the donor-acceptor coupling. The rate expression has new elastic and inelastic terms, depending sensitively on the value of the minimum energy torsional angle. Experimental implications of the present theory and some of the open theoretical issues are discussed.