The Semiparametric Normal Variance-Mean Mixture Model
DEFF Research Database (Denmark)
Korsholm, Lars
1997-01-01
We discuss the normal vairance-mean mixture model from a semi-parametric point of view, i.e. we let the mixing distribution belong to a non parametric family. The main results are consistency of the non parametric maximum likelihood estimat or in this case, and construction of an asymptotically...... normal and efficient estimator....
Dose-response curve estimation: a semiparametric mixture approach.
Yuan, Ying; Yin, Guosheng
2011-12-01
In the estimation of a dose-response curve, parametric models are straightforward and efficient but subject to model misspecifications; nonparametric methods are robust but less efficient. As a compromise, we propose a semiparametric approach that combines the advantages of parametric and nonparametric curve estimates. In a mixture form, our estimator takes a weighted average of the parametric and nonparametric curve estimates, in which a higher weight is assigned to the estimate with a better model fit. When the parametric model assumption holds, the semiparametric curve estimate converges to the parametric estimate and thus achieves high efficiency; when the parametric model is misspecified, the semiparametric estimate converges to the nonparametric estimate and remains consistent. We also consider an adaptive weighting scheme to allow the weight to vary according to the local fit of the models. We conduct extensive simulation studies to investigate the performance of the proposed methods and illustrate them with two real examples.
Analysis of Two-sample Censored Data Using a Semiparametric Mixture Model
Institute of Scientific and Technical Information of China (English)
Gang Li; Chien-tai Lin
2009-01-01
In this article we study a semiparametric mixture model for the two-sample problem with right censored data. The model implies that the densities for the continuous outcomes are related by a parametric tilt but otherwise unspecified. It provides a useful alternative to the Cox (1972) proportional hazards model for the comparison of treatments based on right censored survival data. We propose an iterative algorithm for the semiparametric maximum likelihood estimates of the parametric and nonparametric components of the model. The performance of the proposed method is studied using simulation. We illustrate our method in an application to melanoma.
Reliable single chip genotyping with semi-parametric log-concave mixtures.
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Ralph C A Rippe
Full Text Available The common approach to SNP genotyping is to use (model-based clustering per individual SNP, on a set of arrays. Genotyping all SNPs on a single array is much more attractive, in terms of flexibility, stability and applicability, when developing new chips. A new semi-parametric method, named SCALA, is proposed. It is based on a mixture model using semi-parametric log-concave densities. Instead of using the raw data, the mixture is fitted on a two-dimensional histogram, thereby making computation time almost independent of the number of SNPs. Furthermore, the algorithm is effective in low-MAF situations.Comparisons between SCALA and CRLMM on HapMap genotypes show very reliable calling of single arrays. Some heterozygous genotypes from HapMap are called homozygous by SCALA and to lesser extent by CRLMM too. Furthermore, HapMap's NoCalls (NN could be genotyped by SCALA, mostly with high probability. The software is available as R scripts from the website www.math.leidenuniv.nl/~rrippe.
Noma, Hisashi; Matsui, Shigeyuki
2013-05-20
The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression.
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2001-01-01
to suggest an iterated CEM scheme. Also the target constrained interference minimized filter (TCIMF) is described. Spectral angle mapping (SAM) is briefly described. Finally, semi-parametric unmixing (SPU) based on a combined linear and additive model with a non-linear, smooth function to represent end......As a supplement or an alternative to classification of hyperspectral image data linear and semi-parametric mixture models are considered in order to obtain estimates of abundance of each class or end-member in pixels with mixed membership. Full unmixing based on both ordinary least squares (OLS......) and non-negative least squares (NNLS), and the partial unmixing methods orthogonal subspace projection (OSP), constrained energy minimization (CEM) and an eigenvalue formulation alternative are dealt with. The solution to the eigenvalue formulation alternative proves to be identical to the CEM solution...
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2001-01-01
As a supplement or an alternative to classification of hyperspectral image data linear and semi-parametric mixture models are considered in order to obtain estimates of abundance of each class or end-member in pixels with mixed membership. Full unmixing based on both ordinary least squares (OLS......) and non-negative least squares (NNLS), and the partial unmixing methods orthogonal subspace projection (OSP), constrained energy minimization (CEM) and an eigenvalue formulation alternative are dealt with. The solution to the eigenvalue formulation alternative proves to be identical to the CEM solution...
Reliable Single Chip Genotyping with Semi-Parametric Log-Concave Mixtures
R.C.A. Rippe (Ralph); J.J. Meulman (Jacqueline); P.H.C. Eilers (Paul)
2012-01-01
textabstractThe common approach to SNP genotyping is to use (model-based) clustering per individual SNP, on a set of arrays. Genotyping all SNPs on a single array is much more attractive, in terms of flexibility, stability and applicability, when developing new chips. A new semi-parametric method, n
Jaspers, Stijn; Verbeke, Geert; Böhning, Dankmar; Aerts, Marc
2016-01-01
In the last decades, considerable attention has been paid to the collection of antimicrobial resistance data, with the aim of monitoring non-wild-type isolates. This monitoring is performed based on minimum inhibition concentration (MIC) values, which are collected through dilution experiments. We present a semi-parametric mixture model to estimate the entire MIC density on the continuous scale. The parametric first component is extended with a non-parametric second component and a new back-fitting algorithm, based on the Vertex Exchange Method, is proposed. Our data example shows how to estimate the MIC density for Escherichia coli tested for ampicillin and how to use this estimate for model-based classification. A simulation study was performed, showing the promising behavior of the new method, both in terms of density estimation as well as classification.
Semiparametric Gaussian copula classification
Zhao, Yue; Wegkamp, Marten
2014-01-01
This paper studies the binary classification of two distributions with the same Gaussian copula in high dimensions. Under this semiparametric Gaussian copula setting, we derive an accurate semiparametric estimator of the log density ratio, which leads to our empirical decision rule and a bound on its associated excess risk. Our estimation procedure takes advantage of the potential sparsity as well as the low noise condition in the problem, which allows us to achieve faster convergence rate of...
Semiparametric Regression and Model Refining
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
This paper presents a semiparametric adjustment method suitable for general cases.Assuming that the regularizer matrix is positive definite,the calculation method is discussed and the corresponding formulae are presented.Finally,a simulated adjustment problem is constructed to explain the method given in this paper.The results from the semiparametric model and G-M model are compared.The results demonstrate that the model errors or the systematic errors of the observations can be detected correctly with the semiparametric estimate method.
Bayesian non- and semi-parametric methods and applications
Rossi, Peter
2014-01-01
This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available, a natural desire to provide methods that relax these assumptions arises. Peter Rossi advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. The Bayesian approach can use either a large but fixed number
Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane
2015-01-01
Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…
Semiparametric regression during 2003–2007
Ruppert, David
2009-01-01
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.
Estimating Functions and Semiparametric Models
DEFF Research Database (Denmark)
Labouriau, Rodrigo
1996-01-01
The thesis is divided in two parts. The first part treats some topics of the estimation theory for semiparametric models in general. There the classic optimality theory is reviewed and exposed in a suitable way for the further developments given after. Further the theory of estimating functions...... contained in this part of the thesis constitutes an original contribution. There can be found the detailed characterization of the class of regular estimating functions, a calculation of efficient regular asymptotic linear estimating sequences (\\ie the classical optimality theory) and a discussion...... of the attainability of the bounds for the concentration of regular asymptotic linear estimating sequences by estimators derived from estimating functions. The main class of models considered in the second part of the thesis (chapter 5) are constructed by assuming that the expectation of a number of given square...
Directory of Open Access Journals (Sweden)
Silva-Aguilar Martín
2011-01-01
Full Text Available Metals are ubiquitous pollutants present as mixtures. In particular, mixture of arsenic-cadmium-lead is among the leading toxic agents detected in the environment. These metals have carcinogenic and cell-transforming potential. In this study, we used a two step cell transformation model, to determine the role of oxidative stress in transformation induced by a mixture of arsenic-cadmium-lead. Oxidative damage and antioxidant response were determined. Metal mixture treatment induces the increase of damage markers and the antioxidant response. Loss of cell viability and increased transforming potential were observed during the promotion phase. This finding correlated significantly with generation of reactive oxygen species. Cotreatment with N-acetyl-cysteine induces effect on the transforming capacity; while a diminution was found in initiation, in promotion phase a total block of the transforming capacity was observed. Our results suggest that oxidative stress generated by metal mixture plays an important role only in promotion phase promoting transforming capacity.
A Bayesian semiparametric factor analysis model for subtype identification.
Sun, Jiehuan; Warren, Joshua L; Zhao, Hongyu
2017-04-25
Disease subtype identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to infer disease subtypes, which often lead to biologically meaningful insights into disease. Despite many successes, existing clustering methods may not perform well when genes are highly correlated and many uninformative genes are included for clustering due to the high dimensionality. In this article, we introduce a novel subtype identification method in the Bayesian setting based on gene expression profiles. This method, called BCSub, adopts an innovative semiparametric Bayesian factor analysis model to reduce the dimension of the data to a few factor scores for clustering. Specifically, the factor scores are assumed to follow the Dirichlet process mixture model in order to induce clustering. Through extensive simulation studies, we show that BCSub has improved performance over commonly used clustering methods. When applied to two gene expression datasets, our model is able to identify subtypes that are clinically more relevant than those identified from the existing methods.
The semiparametric Bernstein-von Mises theorem
Bickel, P.J.; Kleijn, B.J.K.
2012-01-01
In a smooth semiparametric estimation problem, the marginal posterior for the parameter of interest is expected to be asymptotically normal and satisfy frequentist criteria of optimality if the model is endowed with a suitable prior. It is shown that, under certain straightforward and interpretable
Semi-Parametric Modelling of Correlation Dynamics
C.M. Hafner (Christian); D.J.C. van Dijk (Dick); Ph.H.B.F. Franses (Philip Hans)
2005-01-01
textabstractIn this paper we develop a new semi-parametric model for conditional correlations, which combines parametric univariate GARCH-type specifications for the individual conditional volatilities with nonparametric kernel regression for the conditional correlations. This approach not only
Bayesian semiparametric dynamic Nelson-Siegel model
C. Cakmakli
2011-01-01
This paper proposes the Bayesian semiparametric dynamic Nelson-Siegel model where the density of the yield curve factors and thereby the density of the yields are estimated along with other model parameters. This is accomplished by modeling the error distributions of the factors according to a Diric
Marginal longitudinal semiparametric regression via penalized splines
Al Kadiri, M.
2010-08-01
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.
Interregional Migration in Spain: A Semiparametric Analysis
Maza Fernández, Adolfo Jesús; Villaverde Castro, José
2004-01-01
This paper analyses the determinants of internal migration in Spain between 1995 and 2002. After a brief descriptive study, we present an analytical model of internal migration flows. Subsequently, we estimate this model by applying semiparametric techniques. The general conclusion that we come to is that net migration rates are influenced mainly by income and climatic condition differentials between the regions of origin and destination; in addition, unemployment and housin...
Marginal longitudinal semiparametric regression via penalized splines.
Kadiri, M Al; Carroll, R J; Wand, M P
2010-08-01
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.
Sinha, Samiran
2009-08-10
We propose a semiparametric Bayesian method for handling measurement error in nutritional epidemiological data. Our goal is to estimate nonparametrically the form of association between a disease and exposure variable while the true values of the exposure are never observed. Motivated by nutritional epidemiological data, we consider the setting where a surrogate covariate is recorded in the primary data, and a calibration data set contains information on the surrogate variable and repeated measurements of an unbiased instrumental variable of the true exposure. We develop a flexible Bayesian method where not only is the relationship between the disease and exposure variable treated semiparametrically, but also the relationship between the surrogate and the true exposure is modeled semiparametrically. The two nonparametric functions are modeled simultaneously via B-splines. In addition, we model the distribution of the exposure variable as a Dirichlet process mixture of normal distributions, thus making its modeling essentially nonparametric and placing this work into the context of functional measurement error modeling. We apply our method to the NIH-AARP Diet and Health Study and examine its performance in a simulation study.
SEMIPARAMETRIC VERSUS PARAMETRIC CLASSIFICATION MODELS - AN APPLICATION TO DIRECT MARKETING
BULT, [No Value
1993-01-01
In this paper we are concerned with estimation of a classification model using semiparametric and parametric methods. Benefits and limitations of semiparametric models in general, and of Manski's maximum score method in particular, are discussed. The maximum score method yields consistent estimates
Efficient estimation of semiparametric copula models for bivariate survival data
Cheng, Guang
2014-01-01
A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. In this paper, we obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data. We construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions. We show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2013 Elsevier Inc.
Testing Homogeneity in a Semiparametric Two-Sample Problem
Directory of Open Access Journals (Sweden)
Yukun Liu
2012-01-01
Full Text Available We study a two-sample homogeneity testing problem, in which one sample comes from a population with density f(x and the other is from a mixture population with mixture density (1−λf(x+λg(x. This problem arises naturally from many statistical applications such as test for partial differential gene expression in microarray study or genetic studies for gene mutation. Under the semiparametric assumption g(x=f(xeα+βx, a penalized empirical likelihood ratio test could be constructed, but its implementation is hindered by the fact that there is neither feasible algorithm for computing the test statistic nor available research results on its theoretical properties. To circumvent these difficulties, we propose an EM test based on the penalized empirical likelihood. We prove that the EM test has a simple chi-square limiting distribution, and we also demonstrate its competitive testing performances by simulations. A real-data example is used to illustrate the proposed methodology.
Group Based Interference Alignment
Ma, Yanjun; Chen, Rui; Yao, Junliang
2010-01-01
in $K$-user single-input single-output (SISO) frequency selective fading interference channels, it is shown that the achievable multiplexing gain is almost surely $K/2$ by using interference alignment (IA). However when the signaling dimensions is limited, allocating all the resource to all the users simultaneously is not optimal. According to this problem, a group based interference alignment (GIA) scheme is proposed and a search algorithm is designed to get the group patterns and the resource allocation among them. Analysis results show that our proposed scheme achieves a higher multiplexing gain when the resource is limited.
Semiparametric regression for the social sciences
Keele, Luke John
2008-01-01
An introductory guide to smoothing techniques, semiparametric estimators, and their related methods, this book describes the methodology via a selection of carefully explained examples and data sets. It also demonstrates the potential of these techniques using detailed empirical examples drawn from the social and political sciences. Each chapter includes exercises and examples and there is a supplementary website containing all the datasets used, as well as computer code, allowing readers to replicate every analysis reported in the book. Includes software for implementing the methods in S-Plus and R.
Multivariate semiparametric spatial methods for imaging data.
Chen, Huaihou; Cao, Guanqun; Cohen, Ronald A
2017-04-01
Univariate semiparametric methods are often used in modeling nonlinear age trajectories for imaging data, which may result in efficiency loss and lower power for identifying important age-related effects that exist in the data. As observed in multiple neuroimaging studies, age trajectories show similar nonlinear patterns for the left and right corresponding regions and for the different parts of a big organ such as the corpus callosum. To incorporate the spatial similarity information without assuming spatial smoothness, we propose a multivariate semiparametric regression model with a spatial similarity penalty, which constrains the variation of the age trajectories among similar regions. The proposed method is applicable to both cross-sectional and longitudinal region-level imaging data. We show the asymptotic rates for the bias and covariance functions of the proposed estimator and its asymptotic normality. Our simulation studies demonstrate that by borrowing information from similar regions, the proposed spatial similarity method improves the efficiency remarkably. We apply the proposed method to two neuroimaging data examples. The results reveal that accounting for the spatial similarity leads to more accurate estimators and better functional clustering results for visualizing brain atrophy pattern.Functional clustering; Longitudinal magnetic resonance imaging (MRI); Penalized B-splines; Region of interest (ROI); Spatial penalty.
Semiparametric Quantile Modelling of Hierarchical Data
Institute of Scientific and Technical Information of China (English)
Mao Zai TIAN; Man Lai TANG; Ping Shing CHAN
2009-01-01
The classic hierarchical linear model formulation provides a considerable flexibility for modelling the random effects structure and a powerful tool for analyzing nested data that arise in various areas such as biology, economics and education. However, it assumes the within-group errors to be independently and identically distributed (i.i.d.) and models at all levels to be linear. Most importantly, traditional hierarchical models (just like other ordinary mean regression methods) cannot characterize the entire conditional distribution of a dependent variable given a set of covariates and fail to yield robust estimators. In this article, we relax the aforementioned and normality assumptions, and develop a so-called Hierarchical Semiparametric Quantile Regression Models in which the within-group errors could be heteroscedastic and models at some levels are allowed to be nonparametric. We present the ideas with a 2-level model. The level-l model is specified as a nonparametric model whereas level-2 model is set as a parametric model. Under the proposed semiparametric setting the vector of partial derivatives of the nonparametric function in level-1 becomes the response variable vector in level 2. The proposed method allows us to model the fixed effects in the innermost level (i.e., level 2) as a function of the covariates instead of a constant effect. We outline some mild regularity conditions required for convergence and asymptotic normality for our estimators. We illustrate our methodology with a real hierarchical data set from a laboratory study and some simulation studies.
Gaussian semiparametric estimation of non-stationary time series
Velasco, Carlos
1998-01-01
Generalizing the definition of the memory parameter d in terms of the differentiated series, we showed in Velasco (Non-stationary log-periodogram regression, Forthcoming J. Economet., 1997) that it is possible to estimate consistently the memory of non-stationary processes using methods designed for stationary long-range-dependent time series. In this paper we consider the Gaussian semiparametric estimate analysed by Robinson (Gaussian semiparametric estimation of long range dependence. Ann. ...
Issues in claims reserving and credibility: a semiparametric approach with mixed models
Antonio, K.; Beirlant, J.
2008-01-01
Using the statistical methodology of semi-parametric regression and its connection with mixed models, this article revisits smoothing models for loss reserving and credibility. Apart from the flexibility inherent to all semiparametric methods, advantages of the semiparametric approach developed here
Semiparametric Bayesian Regression with Applications in Astronomy
Broadbent, Mary Elizabeth
In this thesis we describe a class of Bayesian semiparametric models, known as Levy Adaptive Regression Kernels (LARK); a novel method for posterior computation for those models; and the applications of these models in astronomy, in particular to the analysis of the photon fluence time series of gamma-ray bursts. Gamma-ray bursts are bursts of photons which arrive in a varying number of overlapping pulses with a distinctive "fast-rise, exponential decay" shape in the time domain. LARK models allow us to do inference both on the number of pulses, but also on the parameters which describe the pulses, such as incident time, or decay rate. In Chapter 2, we describe a novel method to aid posterior computation in infinitely-divisible models, of which LARK models are a special case, when the posterior is evaluated through Markov chain Monte Carlo. This is applied in Chapter 3, where time series representing the photon fluence in a single energy channel is analyzed using LARK methods. Due to the effect of the discriminators on BATSE and other instruments, it is important to model the gamma-ray bursts in the incident space. Chapter 4 describes the first to model bursts in the incident photon space, instead of after they have been distorted by the discriminators; since to model photons as they enter the detector is to model both the energy and the arrival time of the incident photon, this model is also the first to jointly model the time and energy domains.
Model and Variable Selection Procedures for Semiparametric Time Series Regression
Directory of Open Access Journals (Sweden)
Risa Kato
2009-01-01
Full Text Available Semiparametric regression models are very useful for time series analysis. They facilitate the detection of features resulting from external interventions. The complexity of semiparametric models poses new challenges for issues of nonparametric and parametric inference and model selection that frequently arise from time series data analysis. In this paper, we propose penalized least squares estimators which can simultaneously select significant variables and estimate unknown parameters. An innovative class of variable selection procedure is proposed to select significant variables and basis functions in a semiparametric model. The asymptotic normality of the resulting estimators is established. Information criteria for model selection are also proposed. We illustrate the effectiveness of the proposed procedures with numerical simulations.
Semiparametric maximum likelihood for nonlinear regression with measurement errors.
Suh, Eun-Young; Schafer, Daniel W
2002-06-01
This article demonstrates semiparametric maximum likelihood estimation of a nonlinear growth model for fish lengths using imprecisely measured ages. Data on the species corvina reina, found in the Gulf of Nicoya, Costa Rica, consist of lengths and imprecise ages for 168 fish and precise ages for a subset of 16 fish. The statistical problem may therefore be classified as nonlinear errors-in-variables regression with internal validation data. Inferential techniques are based on ideas extracted from several previous works on semiparametric maximum likelihood for errors-in-variables problems. The illustration of the example clarifies practical aspects of the associated computational, inferential, and data analytic techniques.
Time series analysis using semiparametric regression on oil palm production
Yundari, Pasaribu, U. S.; Mukhaiyar, U.
2016-04-01
This paper presents semiparametric kernel regression method which has shown its flexibility and easiness in mathematical calculation, especially in estimating density and regression function. Kernel function is continuous and it produces a smooth estimation. The classical kernel density estimator is constructed by completely nonparametric analysis and it is well reasonable working for all form of function. Here, we discuss about parameter estimation in time series analysis. First, we consider the parameters are exist, then we use nonparametrical estimation which is called semiparametrical. The selection of optimum bandwidth is obtained by considering the approximation of Mean Integrated Square Root Error (MISE).
Testing Parametric versus Semiparametric Modelling in Generalized Linear Models
Härdle, W.K.; Mammen, E.; Müller, M.D.
1996-01-01
We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known function, b is an unknown parameter vector, and m is an unknown function.The paper introduces a test statistic which allows to decide between a parametric and a semiparametric model: (i) m is linear, i.e. m(
Bootstrap consistency for general semiparametric M-estimation
Cheng, Guang
2010-10-01
Consider M-estimation in a semiparametric model that is characterized by a Euclidean parameter of interest and an infinite-dimensional nuisance parameter. As a general purpose approach to statistical inferences, the bootstrap has found wide applications in semiparametric M-estimation and, because of its simplicity, provides an attractive alternative to the inference approach based on the asymptotic distribution theory. The purpose of this paper is to provide theoretical justifications for the use of bootstrap as a semiparametric inferential tool. We show that, under general conditions, the bootstrap is asymptotically consistent in estimating the distribution of the M-estimate of Euclidean parameter; that is, the bootstrap distribution asymptotically imitates the distribution of the M-estimate. We also show that the bootstrap confidence set has the asymptotically correct coverage probability. These general onclusions hold, in particular, when the nuisance parameter is not estimable at root-n rate, and apply to a broad class of bootstrap methods with exchangeable ootstrap weights. This paper provides a first general theoretical study of the bootstrap in semiparametric models. © Institute of Mathematical Statistics, 2010.
Error-Bars in Semi-Parametric Estimation
Van Ormondt, D.; Van der Veen, J.W.C.; Sima, D.M.; Graveron-Demilly, D.
In in vivo metabolite-quantitation with a magnetic resonance spectroscopy (MRS) scanner, the model function of the attendant MRS signal is often only partly known. This unfavourable condition requires semi-parametric estimation. In the present study the unknown part is the form of the decay function
Coordinate descent methods for the penalized semiparametric additive hazards model
DEFF Research Database (Denmark)
Gorst-Rasmussen, Anders; Scheike, Thomas
. The semiparametric additive hazards model is a flexible alternative which is a natural survival analogue of the standard linear regression model. Building on this analogy, we develop a cyclic coordinate descent algorithm for fitting the lasso and elastic net penalized additive hazards model. The algorithm requires...
The Non- and Semiparametric Analysis of MS Models : Some Applications
Li, Y.; Donkers, A.C.D.; Melenberg, B.
2006-01-01
This paper illustrates how to compare different microscopic simulation (MS) models and how to compare a MS model with real data in case the parameters of interest are estimated non- or semiparametrically.As examples we investigate the marginal single-period probability density function of stock retu
Baldasaro, Ruth E; Bauer, Daniel J
2011-11-30
Many approaches have been proposed to estimate interactions among latent variables. These methods often assume a specific functional form for the interaction, such as a bilinear interaction. Theory is seldom specific enough to provide a functional form for an interaction, however, so a more exploratory, diagnostic approach may often be required. Bauer (2005) proposed a semiparametric approach that allows for the estimation of interaction effects of unknown functional form among latent variables. A structural equation mixture model (SEMM) is first fit to the data. Then an approximation of the interaction is obtained by aggregating over the mixing components. A simulation study is used to examine the performance of this semiparametric approach to two parametric approaches: the latent moderated structures approach (Klein & Moosbrugger, 2000) and the unconstrained product-indicator approach (Marsh, Wen, & Hau, 2004). Data were generated from four functional forms: main effects only, quadratic trend, bilinear interaction, and exponential interaction. Estimates of bias and root mean squared error of approximation were calculated by comparing the surface used to generate the data and the model-implied surface constructed from each approach. As expected, the parametric approaches were more efficient than the SEMM. For the main effects model, bias was similar for both the SEMM and parametric approaches. For the bilinear interaction, the parametric approaches provided nearly identical results, although the SEMM approach was slightly more biased. When the parametric approaches assumed a bilinear interaction and the data were generated from a quadratic trend or an exponential interaction, the parametric approaches generated biased estimates of the true surface. The SEMM approach approximated the true data generation surface with a similarly low level of bias for all the nonlinear surfaces. For example, Figure 1 shows the true surface for the bilinear interaction along with the
Semiparametric Additive Transformation Model under Current Status Data
Cheng, Guang
2011-01-01
We consider the efficient estimation of the semiparametric additive transformation model with current status data. A wide range of survival models and econometric models can be incorporated into this general transformation framework. We apply the B-spline approach to simultaneously estimate the linear regression vector, the nondecreasing transformation function, and a set of nonparametric regression functions. We show that the parametric estimate is semiparametric efficient in the presence of multiple nonparametric nuisance functions. An explicit consistent B-spline estimate of the asymptotic variance is also provided. All nonparametric estimates are smooth, and shown to be uniformly consistent and have faster than cubic rate of convergence. Interestingly, we observe the convergence rate interfere phenomenon, i.e., the convergence rates of B-spline estimators are all slowed down to equal the slowest one. The constrained optimization is not required in our implementation. Numerical results are used to illustra...
Explicit estimating equations for semiparametric generalized linear latent variable models
Ma, Yanyuan
2010-07-05
We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n consistency and asymptotic normality. We explain the computational implementation of our method and illustrate the numerical performance of the estimators in finite sample situations via extensive simulation studies. The advantage of our estimators over the existing likelihood approach is also shown via numerical comparison. We employ the method to analyse a real data example from economics. © 2010 Royal Statistical Society.
Semiparametric Inference in a GARCH-in-Mean Model
DEFF Research Database (Denmark)
Christensen, Bent Jesper; Dahl, Christian Møller; Iglesias, Emma M.
, such as the dividend yield. Using the profile likelihood approach, we show that our estimator under stated conditions is consistent, asymp- totically normal, and efficient, i.e. it achieves the semiparametric lower bound. A sampling experiment provides evidence on finite sample properties as well as comparisons......A new semiparametric estimator for an empirical asset pricing model with general nonpara- metric risk-return tradeoff and a GARCH process for the underlying volatility is introduced. The estimator does not rely on any initial parametric estimator of the conditional mean func- tion, and this feature...... facilitates the derivation of asymptotic theory under possible nonlinearity of unspecified form of the risk-return tradeoff. Besides the nonlinear GARCH-in-mean effect, our specification accommodates exogenous regressors that are typically used as conditioning variables entering linearly in the mean equation...
Semiparametric Inference in a GARCH-in-Mean Model
DEFF Research Database (Denmark)
Christensen, Bent Jesper; Dahl, Christian Møller; Iglesias, Emma M.
facilitates the derivation of asymptotic theory under possible nonlinearity of unspecified form of the risk-return tradeoff. Besides the nonlinear GARCH-in-mean effect, our specification accommodates exogenous regressors that are typically used as conditioning variables entering linearly in the mean equation......, such as the dividend yield. Using the profile likelihood approach, we show that our estimator under stated conditions is consistent, asymp- totically normal, and efficient, i.e. it achieves the semiparametric lower bound. A sampling experiment provides evidence on finite sample properties as well as comparisons...... with the fully parametric approach and the iterative semiparametric approach using a parametric initial esti- mate proposed by Conrad and Mammen (2008). An empirical application to the daily S&P 500 stock market returns suggests that the linear relation between conditional expected return and conditional...
Simultaneous confidence bands for Cox regression from semiparametric random censorship.
Mondal, Shoubhik; Subramanian, Sundarraman
2016-01-01
Cox regression is combined with semiparametric random censorship models to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined.
Local Influence Analysis for Semiparametric Reproductive Dispersion Nonlinear Models
Institute of Scientific and Technical Information of China (English)
Xue-dong CHEN; Nian-sheng TANG; Xue-ren WANG
2012-01-01
The present paper proposes a semiparametric reproductive dispersion nonlinear model (SRDNM)which is an extension of the nonlinear reproductive dispersion models and the semiparameter regression models.Maximum penalized likelihood estimates (MPLEs) of unknown parameters and nonparametric functions in SRDNM are presented.Assessment of local influence for various perturbation schemes are investigated.Some local influence diagnostics are given.A simulation study and a real example are used to illustrate the proposed methodologies.
Energy consumption and income. A semiparametric panel data analysis
Energy Technology Data Exchange (ETDEWEB)
Nguyen-Van, Phu [BETA, CNRS and Universite de Strasbourg, 61 avenue de la Foret Noire, F-67085 Strasbourg (France)
2010-05-15
This paper proposes a semiparametric analysis for the study of the relationship between energy consumption per capita and income per capita for an international panel dataset. It shows little evidence for the existence of an environmental Kuznets curve for energy consumption. Energy consumption increases with income for a majority of countries and then stabilizes for very high income countries. Neither changes in energy structure nor macroeconomic cycle/technological change have significant effect on energy consumption. (author)
Another Look at the Income Elasticity of Non-point Source Air Pollutants: A Semiparametric Approach
Roy, N.; Kooten, van G.C.
2004-01-01
In this paper, a semiparametric model is used to examine the relationship between pollution and income for three non-point source pollutants. Statistical tests reject the quadratic specification in favor of the semiparametric model in all cases. However, the results do not support the inverted-U hyp
Yu, Wen; Chen, Kani; Sobel, Michael E; Ying, Zhiliang
2015-03-01
We consider causal inference in randomized survival studies with right censored outcomes and all-or-nothing compliance, using semiparametric transformation models to estimate the distribution of survival times in treatment and control groups, conditional on covariates and latent compliance type. Estimands depending on these distributions, for example, the complier average causal effect (CACE), the complier effect on survival beyond time t, and the complier quantile effect are then considered. Maximum likelihood is used to estimate the parameters of the transformation models, using a specially designed expectation-maximization (EM) algorithm to overcome the computational difficulties created by the mixture structure of the problem and the infinite dimensional parameter in the transformation models. The estimators are shown to be consistent, asymptotically normal, and semiparametrically efficient. Inferential procedures for the causal parameters are developed. A simulation study is conducted to evaluate the finite sample performance of the estimated causal parameters. We also apply our methodology to a randomized study conducted by the Health Insurance Plan of Greater New York to assess the reduction in breast cancer mortality due to screening.
Sarkar, Abhra
2014-10-02
We consider the problem of estimating the density of a random variable when precise measurements on the variable are not available, but replicated proxies contaminated with measurement error are available for sufficiently many subjects. Under the assumption of additive measurement errors this reduces to a problem of deconvolution of densities. Deconvolution methods often make restrictive and unrealistic assumptions about the density of interest and the distribution of measurement errors, e.g., normality and homoscedasticity and thus independence from the variable of interest. This article relaxes these assumptions and introduces novel Bayesian semiparametric methodology based on Dirichlet process mixture models for robust deconvolution of densities in the presence of conditionally heteroscedastic measurement errors. In particular, the models can adapt to asymmetry, heavy tails and multimodality. In simulation experiments, we show that our methods vastly outperform a recent Bayesian approach based on estimating the densities via mixtures of splines. We apply our methods to data from nutritional epidemiology. Even in the special case when the measurement errors are homoscedastic, our methodology is novel and dominates other methods that have been proposed previously. Additional simulation results, instructions on getting access to the data set and R programs implementing our methods are included as part of online supplemental materials.
ASYMPTOTIC EFFICIENT ESTIMATION IN SEMIPARAMETRIC NONLINEAR REGRESSION MODELS
Institute of Scientific and Technical Information of China (English)
ZhuZhongyi; WeiBocheng
1999-01-01
In this paper, the estimation method based on the “generalized profile likelihood” for the conditionally parametric models in the paper given by Severini and Wong (1992) is extendedto fixed design semiparametrie nonlinear regression models. For these semiparametrie nonlinear regression models,the resulting estimator of parametric component of the model is shown to beasymptotically efficient and the strong convergence rate of nonparametric component is investigated. Many results (for example Chen (1988) ,Gao & Zhao (1993), Rice (1986) et al. ) are extended to fixed design semiparametric nonlinear regression models.
Model averaging for semiparametric additive partial linear models
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
To improve the prediction accuracy of semiparametric additive partial linear models(APLM) and the coverage probability of confidence intervals of the parameters of interest,we explore a focused information criterion for model selection among ALPM after we estimate the nonparametric functions by the polynomial spline smoothing,and introduce a general model average estimator.The major advantage of the proposed procedures is that iterative backfitting implementation is avoided,which thus results in gains in computational simplicity.The resulting estimators are shown to be asymptotically normal.A simulation study and a real data analysis are presented for illustrations.
A semiparametric approach to short-term oil price forecasting
Energy Technology Data Exchange (ETDEWEB)
Morana, C. [University of Piemonte Orientale, Facolta di Economia, Via Lanino 1, 28100 Novara (Italy)
2001-05-01
In this paper it is shown how the GARCH properties of oil price changes can be employed to forecast the oil price distribution over short-term horizons. The forecasting methodology is semiparametric and it is based on the bootstrap approach. The results of an out-of-sample forecasting exercise, carried out using the Brent oil price series, suggest that the forecasting approach can be used to obtain a performance measure for the forward price, in addition to compute interval forecasts for the oil price.
Smoothed Semiparametric Estimation on Multivariate Long Memory Processes
Pumi, Guilherme
2012-01-01
In this paper we propose and study a general class of Gaussian Semiparametric Estimators (GSE) of the fractional differencing parameter in the context of long-range dependent multivariate time series. We establish large sample properties of the estimator without assuming Gaussianity. The class of models considered here satisfies simple conditions on the spectral density function, restricted to a small neighborhood of the zero frequency and includes important class of VARFIMA processes. We also present a simulation study to assess the finite sample properties of the proposed estimator based on a smoothed version of the GSE which supports its competitiveness.
Determining of migraine prognosis using latent growth mixture models
Institute of Scientific and Technical Information of China (English)
Bahar Tasdelen; Aynur Ozge; Hakan Kaleagasi; Semra Erdogan; Tufan Mengi
2011-01-01
Background This paper presents a retrospective study to classify patients into subtypes of the treatment according to baseline and longitudinally observed values considering heterogenity in migraine prognosis. In the classical prospective clinical studies,participants are classified with respect to baseline status and followed within a certain time period.However,latent growth mixture model is the most suitable method,which considers the population heterogenity and is not affected drop-outs if they are missing at random. Hence,we planned this comprehensive study to identify prognostic factors in migraine.Methods The study data have been based on a 10-year computer-based follow-up data of Mersin University Headache Outpatient Department. The developmental trajectories within subgroups were described for the severity,frequency,and duration of headache separately and the probabilities of each subgroup were estimated by using latent growth mixture models. SAS PROC TRAJ procedures,semiparametric and group-based mixture modeling approach,were applied to define the developmental trajectories.Results While the three-group model for the severity (mild,moderate,severe) and frequency (low,medium,high) of headache appeared to be appropriate,the four-group model for the duration (low,medium,high,extremely high) was more suitable. The severity of headache increased in the patients with nausea,vomiting,photophobia and phonophobia.The frequency of headache was especially related with increasing age and unilateral pain. Nausea and photophobia were also related with headache duration.Conclusions Nausea,vomiting and photophobia were the most significant factors to identify developmental trajectories.The remission time was not the same for the severity,frequency,and duration of headache.
A Bayesian modeling approach for generalized semiparametric structural equation models.
Song, Xin-Yuan; Lu, Zhao-Hua; Cai, Jing-Heng; Ip, Edward Hak-Sing
2013-10-01
In behavioral, biomedical, and psychological studies, structural equation models (SEMs) have been widely used for assessing relationships between latent variables. Regression-type structural models based on parametric functions are often used for such purposes. In many applications, however, parametric SEMs are not adequate to capture subtle patterns in the functions over the entire range of the predictor variable. A different but equally important limitation of traditional parametric SEMs is that they are not designed to handle mixed data types-continuous, count, ordered, and unordered categorical. This paper develops a generalized semiparametric SEM that is able to handle mixed data types and to simultaneously model different functional relationships among latent variables. A structural equation of the proposed SEM is formulated using a series of unspecified smooth functions. The Bayesian P-splines approach and Markov chain Monte Carlo methods are developed to estimate the smooth functions and the unknown parameters. Moreover, we examine the relative benefits of semiparametric modeling over parametric modeling using a Bayesian model-comparison statistic, called the complete deviance information criterion (DIC). The performance of the developed methodology is evaluated using a simulation study. To illustrate the method, we used a data set derived from the National Longitudinal Survey of Youth.
bspmma: An R Package for Bayesian Semiparametric Models for Meta-Analysis
Directory of Open Access Journals (Sweden)
Deborah Burr
2012-07-01
Full Text Available We introduce an R package, bspmma, which implements a Dirichlet-based random effects model specific to meta-analysis. In meta-analysis, when combining effect estimates from several heterogeneous studies, it is common to use a random-effects model. The usual frequentist or Bayesian models specify a normal distribution for the true effects. However, in many situations, the effect distribution is not normal, e.g., it can have thick tails, be skewed, or be multi-modal. A Bayesian nonparametric model based on mixtures of Dirichlet process priors has been proposed in the literature, for the purpose of accommodating the non-normality. We review this model and then describe a competitor, a semiparametric version which has the feature that it allows for a well-defined centrality parameter convenient for determining whether the overall effect is significant. This second Bayesian model is based on a different version of the Dirichlet process prior, and we call it the "conditional Dirichlet model". The package contains functions to carry out analyses based on either the ordinary or the conditional Dirichlet model, functions for calculating certain Bayes factors that provide a check on the appropriateness of the conditional Dirichlet model, and functions that enable an empirical Bayes selection of the precision parameter of the Dirichlet process. We illustrate the use of the package on two examples, and give an interpretation of the results in these two different scenarios.
Das, Kiranmoy; Li, Jiahan; Fu, Guifang; Wang, Zhong; Li, Runze; Wu, Rongling
2013-02-10
Many phenomena of fundamental importance to biology and biomedicine arise as a dynamic curve, such as organ growth and HIV dynamics. The genetic mapping of these traits is challenged by longitudinal variables measured at irregular and possibly subject-specific time points, in which case nonnegative definiteness of the estimated covariance matrix needs to be guaranteed. We present a semiparametric approach for genetic mapping within the mixture-model setting by jointly modeling mean and covariance structures for irregular longitudinal data. Penalized spline is used to model the mean functions of individual quantitative trait locus (QTL) genotypes as latent variables, whereas an extended generalized linear model is used to approximate the covariance matrix. The parameters for modeling the mean-covariances are estimated by MCMC, using the Gibbs sampler and the Metropolis-Hastings algorithm. We derive the full conditional distributions for the mean and covariance parameters and compute Bayes factors to test the hypothesis about the existence of significant QTLs. We used the model to screen the existence of specific QTLs for age-specific change of body mass index with a sparse longitudinal data set. The new model provides powerful means for broadening the application of genetic mapping to reveal the genetic control of dynamic traits.
Semi-parametric regression: Efficiency gains from modeling the nonparametric part
Yu, Kyusang; Park, Byeong U; 10.3150/10-BEJ296
2011-01-01
It is widely admitted that structured nonparametric modeling that circumvents the curse of dimensionality is important in nonparametric estimation. In this paper we show that the same holds for semi-parametric estimation. We argue that estimation of the parametric component of a semi-parametric model can be improved essentially when more structure is put into the nonparametric part of the model. We illustrate this for the partially linear model, and investigate efficiency gains when the nonparametric part of the model has an additive structure. We present the semi-parametric Fisher information bound for estimating the parametric part of the partially linear additive model and provide semi-parametric efficient estimators for which we use a smooth backfitting technique to deal with the additive nonparametric part. We also present the finite sample performances of the proposed estimators and analyze Boston housing data as an illustration.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Semiparametric reproductive dispersion nonlinear model (SRDNM) is an extension of nonlinear reproductive dispersion models and semiparametric nonlinear regression models, and includes semiparametric nonlinear model and semiparametric generalized linear model as its special cases. Based on the local kernel estimate of nonparametric component, profile-kernel and backfitting estimators of parameters of interest are proposed in SRDNM, and theoretical comparison of both estimators is also investigated in this paper. Under some regularity conditions, strong consistency and asymptotic normality of two estimators are proved. It is shown that the backfitting method produces a larger asymptotic variance than that for the profile-kernel method. A simulation study and a real example are used to illustrate the proposed methodologies.
A semiparametric efficient estimator in case-control studies
Ma, Yanyuan
2010-01-01
We construct a semiparametric estimator in case-control studies where the gene and the environment are assumed to be independent. A discrete or continuous parametric distribution of the genes is assumed in the model. A discrete distribution of the genes can be used to model the mutation or presence of certain group of genes. A continuous distribution allows the distribution of the gene effects to be in a finite-dimensional parametric family and can hence be used to model the gene expression levels. We leave the distribution of the environment totally unspecified. The estimator is derived through calculating the efficiency score function in a hypothetical setting where a close approximation to the samples is random. The resulting estimator is proved to be efficient in the hypothetical situation. The efficiency of the estimator is further demonstrated to hold in the case-control setting as well.
Second-order analysis of semiparametric recurrent event processes.
Guan, Yongtao
2011-09-01
A typical recurrent event dataset consists of an often large number of recurrent event processes, each of which contains multiple event times observed from an individual during a follow-up period. Such data have become increasingly available in medical and epidemiological studies. In this article, we introduce novel procedures to conduct second-order analysis for a flexible class of semiparametric recurrent event processes. Such an analysis can provide useful information regarding the dependence structure within each recurrent event process. Specifically, we will use the proposed procedures to test whether the individual recurrent event processes are all Poisson processes and to suggest sensible alternative models for them if they are not. We apply these procedures to a well-known recurrent event dataset on chronic granulomatous disease and an epidemiological dataset on meningococcal disease cases in Merseyside, United Kingdom to illustrate their practical value.
Study on Semi-Parametric Statistical Model of Safety Monitoring of Cracks in Concrete Dams
Directory of Open Access Journals (Sweden)
Chongshi Gu
2013-01-01
Full Text Available Cracks are one of the hidden dangers in concrete dams. The study on safety monitoring models of concrete dam cracks has always been difficult. Using the parametric statistical model of safety monitoring of cracks in concrete dams, with the help of the semi-parametric statistical theory, and considering the abnormal behaviors of these cracks, the semi-parametric statistical model of safety monitoring of concrete dam cracks is established to overcome the limitation of the parametric model in expressing the objective model. Previous projects show that the semi-parametric statistical model has a stronger fitting effect and has a better explanation for cracks in concrete dams than the parametric statistical model. However, when used for forecast, the forecast capability of the semi-parametric statistical model is equivalent to that of the parametric statistical model. The modeling of the semi-parametric statistical model is simple, has a reasonable principle, and has a strong practicality, with a good application prospect in the actual project.
Phylogenetic invariants for group-based models
Donten-Bury, Maria
2010-01-01
In this paper we investigate properties of algebraic varieties representing group-based phylogenetic models. We give the (first) example of a nonnormal general group-based model for an abelian group. Following Kaie Kubjas we also determine some invariants of group-based models showing that the associated varieties do not have to be deformation equivalent. We propose a method of generating many phylogenetic invariants and in particular we show that our approach gives the whole ideal of the claw tree for 3-Kimura model under the assumption of the conjecture of Sturmfels and Sullivant. This, combined with the results of Sturmfels and Sullivant, would enable to determine all phylogenetic invariants for any tree for 3-Kimura model and possibly for other group-based models.
Investigating international new product diffusion speed: A semiparametric approach
Hartman, Brian M.
2012-06-01
Global marketing managers are interested in understanding the speed of the new product diffusion process and how the speed has changed in our ever more technologically advanced and global marketplace. Understanding the process allows firms to forecast the expected rate of return on their new products and develop effective marketing strategies. The most recent major study on this topic [Marketing Science 21 (2002) 97-114] investigated new product diffusions in the United States.We expand upon that study in three important ways. (1) Van den Bulte notes that a similar study is needed in the international context, especially in developing countries. Our study covers four new product diffusions across 31 developed and developing nations from 1980-2004. Our sample accounts for about 80% of the global economic output and 60% of the global population, allowing us to examine more general phenomena. (2) His model contains the implicit assumption that the diffusion speed parameter is constant throughout the diffusion life cycle of a product. Recognizing the likely effects on the speed parameter of recent changes in the marketplace, we model the parameter as a semiparametric function, allowing it the flexibility to change over time. (3) We perform a variable selection to determine that the number of internet users and the consumer price index are strongly associated with the speed of diffusion. © Institute of Mathematical Statistics, 2012.
Maximum likelihood estimation for semiparametric density ratio model.
Diao, Guoqing; Ning, Jing; Qin, Jing
2012-06-27
In the statistical literature, the conditional density model specification is commonly used to study regression effects. One attractive model is the semiparametric density ratio model, under which the conditional density function is the product of an unknown baseline density function and a known parametric function containing the covariate information. This model has a natural connection with generalized linear models and is closely related to biased sampling problems. Despite the attractive features and importance of this model, most existing methods are too restrictive since they are based on multi-sample data or conditional likelihood functions. The conditional likelihood approach can eliminate the unknown baseline density but cannot estimate it. We propose efficient estimation procedures based on the nonparametric likelihood. The nonparametric likelihood approach allows for general forms of covariates and estimates the regression parameters and the baseline density simultaneously. Therefore, the nonparametric likelihood approach is more versatile than the conditional likelihood approach especially when estimation of the conditional mean or other quantities of the outcome is of interest. We show that the nonparametric maximum likelihood estimators are consistent, asymptotically normal, and asymptotically efficient. Simulation studies demonstrate that the proposed methods perform well in practical settings. A real example is used for illustration.
Generalized Functional Linear Models With Semiparametric Single-Index Interactions
Li, Yehua
2010-06-01
We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.
Semiparametric Analysis of Heterogeneous Data Using Varying-Scale Generalized Linear Models.
Xie, Minge; Simpson, Douglas G; Carroll, Raymond J
2008-01-01
This article describes a class of heteroscedastic generalized linear regression models in which a subset of the regression parameters are rescaled nonparametrically, and develops efficient semiparametric inferences for the parametric components of the models. Such models provide a means to adapt for heterogeneity in the data due to varying exposures, varying levels of aggregation, and so on. The class of models considered includes generalized partially linear models and nonparametrically scaled link function models as special cases. We present an algorithm to estimate the scale function nonparametrically, and obtain asymptotic distribution theory for regression parameter estimates. In particular, we establish that the asymptotic covariance of the semiparametric estimator for the parametric part of the model achieves the semiparametric lower bound. We also describe bootstrap-based goodness-of-scale test. We illustrate the methodology with simulations, published data, and data from collaborative research on ultrasound safety.
Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang
2010-07-01
We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root-n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.
Institute of Scientific and Technical Information of China (English)
Ge-mai Chen; Jin-hong You
2005-01-01
Consider a repeated measurement partially linear regression model with an unknown vector pasemiparametric generalized least squares estimator (SGLSE) ofβ, we propose an iterative weighted semiparametric least squares estimator (IWSLSE) and show that it improves upon the SGLSE in terms of asymptotic covariance matrix. An adaptive procedure is given to determine the number of iterations. We also show that when the number of replicates is less than or equal to two, the IWSLSE can not improve upon the SGLSE.These results are generalizations of those in [2] to the case of semiparametric regressions.
A Semi-Parametric Bayesian Mixture Modeling Approach for the Analysis of Judge Mediated Data
Muckle, Timothy Joseph
2010-01-01
Existing methods for the analysis of ordinal-level data arising from judge ratings, such as the Multi-Facet Rasch model (MFRM, or the so-called Facets model) have been widely used in assessment in order to render fair examinee ability estimates in situations where the judges vary in their behavior or severity. However, this model makes certain…
Cameron, Ewan
2013-01-01
In the second paper of this series we extend our Bayesian reanalysis of the evidence for a cosmic variation of the fine structure constant to the semi-parametric modelling regime. By adopting a mixture of Dirichlet processes prior for the unexplained errors in each instrumental subgroup of the benchmark quasar dataset we go some way towards freeing our model selection procedure from the apparent subjectivity of a fixed distributional form. Despite the infinite-dimensional domain of the error hierarchy so constructed we are able to demonstrate a recursive scheme for marginal likelihood estimation with prior-sensitivity analysis directly analogous to that presented in Paper I, thereby allowing the robustness of our posterior Bayes factors to hyper-parameter choice and model specification to be readily verified. In the course of this work we elucidate various similarities between unexplained error problems in the seemingly disparate fields of astronomy and clinical meta-analysis, and we highlight a number of sop...
Sumantari, Y. D.; Slamet, I.; Sugiyanto
2017-06-01
Semiparametric regression is a statistical analysis method that consists of parametric and nonparametric regression. There are various approach techniques in nonparametric regression. One of the approach techniques is spline. Central Java is one of the most densely populated province in Indonesia. Population density in this province can be modeled by semiparametric regression because it consists of parametric and nonparametric component. Therefore, the purpose of this paper is to determine the factors that in uence population density in Central Java using the semiparametric spline regression model. The result shows that the factors which in uence population density in Central Java is Family Planning (FP) active participants and district minimum wage.
Gender Wage Gap : A Semi-Parametric Approach With Sample Selection Correction
Picchio, M.; Mussida, C.
2010-01-01
Sizeable gender differences in employment rates are observed in many countries. Sample selection into the workforce might therefore be a relevant issue when estimating gender wage gaps. This paper proposes a new semi-parametric estimator of densities in the presence of covariates which incorporates
Gender Wage Gap : A Semi-Parametric Approach With Sample Selection Correction
Picchio, M.; Mussida, C.
2010-01-01
Sizeable gender differences in employment rates are observed in many countries. Sample selection into the workforce might therefore be a relevant issue when estimating gender wage gaps. This paper proposes a new semi-parametric estimator of densities in the presence of covariates which incorporates
DEFF Research Database (Denmark)
Bennedsen, Mikkel
Using theory on (conditionally) Gaussian processes with stationary increments developed in Barndorff-Nielsen et al. (2009, 2011), this paper presents a general semiparametric approach to conducting inference on the fractal index, α, of a time series. Our setup encompasses a large class of Gaussian...
Kai, Bo; Li, Runze; Zou, Hui
2011-02-01
The complexity of semiparametric models poses new challenges to statistical inference and model selection that frequently arise from real applications. In this work, we propose new estimation and variable selection procedures for the semiparametric varying-coefficient partially linear model. We first study quantile regression estimates for the nonparametric varying-coefficient functions and the parametric regression coefficients. To achieve nice efficiency properties, we further develop a semiparametric composite quantile regression procedure. We establish the asymptotic normality of proposed estimators for both the parametric and nonparametric parts and show that the estimators achieve the best convergence rate. Moreover, we show that the proposed method is much more efficient than the least-squares-based method for many non-normal errors and that it only loses a small amount of efficiency for normal errors. In addition, it is shown that the loss in efficiency is at most 11.1% for estimating varying coefficient functions and is no greater than 13.6% for estimating parametric components. To achieve sparsity with high-dimensional covariates, we propose adaptive penalization methods for variable selection in the semiparametric varying-coefficient partially linear model and prove that the methods possess the oracle property. Extensive Monte Carlo simulation studies are conducted to examine the finite-sample performance of the proposed procedures. Finally, we apply the new methods to analyze the plasma beta-carotene level data.
Dustmann, C.; van Soest, A.H.O.
1999-01-01
We consider both a parametric and a semiparametric method to account for classification errors on the dependent variable in an ordered response model. The methods are applied to the analysis of self-reported speaking fluency of male immigrants in Germany. We find some substantial differences in para
Dustmann, C.; van Soest, A.H.O.
1999-01-01
We consider both a parametric and a semiparametric method to account for classification errors on the dependent variable in an ordered response model. The methods are applied to the analysis of self-reported speaking fluency of male immigrants in Germany. We find some substantial differences in
Fractional cointegration in the consumption and income relationship using semiparametric techniques
Gil-Alana, Luis A.
2004-01-01
This paper deals with the issue of the Permanent Income Hypothesis (PIH) and we show that consumption and income may be fractionally cointegrated. We use a semiparametric frequency domain procedure of Robinson (1995a), and the results show that the UK and the Japanese consumption and income are related in the long run throughout a fractional model.
Schörgendorfer, Angela; Branscum, Adam J; Hanson, Timothy E
2013-06-01
Logistic regression is a popular tool for risk analysis in medical and population health science. With continuous response data, it is common to create a dichotomous outcome for logistic regression analysis by specifying a threshold for positivity. Fitting a linear regression to the nondichotomized response variable assuming a logistic sampling model for the data has been empirically shown to yield more efficient estimates of odds ratios than ordinary logistic regression of the dichotomized endpoint. We illustrate that risk inference is not robust to departures from the parametric logistic distribution. Moreover, the model assumption of proportional odds is generally not satisfied when the condition of a logistic distribution for the data is violated, leading to biased inference from a parametric logistic analysis. We develop novel Bayesian semiparametric methodology for testing goodness of fit of parametric logistic regression with continuous measurement data. The testing procedures hold for any cutoff threshold and our approach simultaneously provides the ability to perform semiparametric risk estimation. Bayes factors are calculated using the Savage-Dickey ratio for testing the null hypothesis of logistic regression versus a semiparametric generalization. We propose a fully Bayesian and a computationally efficient empirical Bayesian approach to testing, and we present methods for semiparametric estimation of risks, relative risks, and odds ratios when parametric logistic regression fails. Theoretical results establish the consistency of the empirical Bayes test. Results from simulated data show that the proposed approach provides accurate inference irrespective of whether parametric assumptions hold or not. Evaluation of risk factors for obesity shows that different inferences are derived from an analysis of a real data set when deviations from a logistic distribution are permissible in a flexible semiparametric framework.
National Research Council Canada - National Science Library
L. MuhamadSafiih; A. A. Kamil; M. T. Abu Osman
2014-01-01
... this problem is through the use of semi-parametric method. However, the uncertainties and ambiguities exist in the models, particularly the relationship between the endogenous and exogenous variables...
Institute of Scientific and Technical Information of China (English)
TANG NianSheng; CHEN XueDong; WANG XueRen
2009-01-01
Semiparametric reproductive dispersion nonlinear model (SRDNM) is an extension of nonlinear reproductive dispersion models and semiparametric nonlinear regression models, and includes semiparametric nonlinear model and semiparametric generalized linear model as its special cases. Based on the local kernel estimate of nonparametric component, profile-kernel and backfitting estimators of parameters of interest are proposed in SRDNM, and theoretical comparison of both estimators is also investigated in this paper. Under some regularity conditions, strong consistency and asymptotic normality of two estimators are proved. It is shown that the backtitting method produces a larger asymptotic variance than that for the profile-kernel method. A simulation study and a real example are used to illustrate the proposed methodologies.
A semiparametric Wald statistic for testing logistic regression models based on case-control data
Institute of Scientific and Technical Information of China (English)
2008-01-01
We propose a semiparametric Wald statistic to test the validity of logistic regression models based on case-control data. The test statistic is constructed using a semiparametric ROC curve estimator and a nonparametric ROC curve estimator. The statistic has an asymptotic chi-squared distribution and is an alternative to the Kolmogorov-Smirnov-type statistic proposed by Qin and Zhang in 1997, the chi-squared-type statistic proposed by Zhang in 1999 and the information matrix test statistic proposed by Zhang in 2001. The statistic is easy to compute in the sense that it requires none of the following methods: using a bootstrap method to find its critical values, partitioning the sample data or inverting a high-dimensional matrix. We present some results on simulation and on analysis of two real examples. Moreover, we discuss how to extend our statistic to a family of statistics and how to construct its Kolmogorov-Smirnov counterpart.
DEFF Research Database (Denmark)
Czekaj, Tomasz Gerard; Henningsen, Arne
The estimation of the technical efficiency comprises a vast literature in the field of applied production economics. There are two predominant approaches: the non-parametric and non-stochastic Data Envelopment Analysis (DEA) and the parametric Stochastic Frontier Analysis (SFA). The DEA...... of specifying an unsuitable functional form and thus, model misspecification and biased parameter estimates. Given these problems of the DEA and the SFA, Fan, Li and Weersink (1996) proposed a semi-parametric stochastic frontier model that estimates the production function (frontier) by non-parametric......), Kumbhakar et al. (2007), and Henningsen and Kumbhakar (2009). The aim of this paper and its main contribution to the existing literature is the estimation semi-parametric stochastic frontier models using a different non-parametric estimation technique: spline regression (Ma et al. 2011). We apply...
DEFF Research Database (Denmark)
Nielsen, Morten Ø.; Frederiksen, Per Houmann
2005-01-01
In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods. The es...... the time domain parametric methods, and (4) without sufficient trimming of scales the wavelet-based estimators are heavily biased.......In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods....... The estimators are briefly introduced and compared, and the criteria adopted for measuring finite sample performance are bias and root mean squared error. Most importantly, the simulations reveal that (1) the frequency domain maximum likelihood procedure is superior to the time domain parametric methods, (2) all...
DEFF Research Database (Denmark)
Nielsen, Morten Ø.; Frederiksen, Per Houmann
2005-01-01
In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods....... The estimators are briefly introduced and compared, and the criteria adopted for measuring finite sample performance are bias and root mean squared error. Most importantly, the simulations reveal that (1) the frequency domain maximum likelihood procedure is superior to the time domain parametric methods, (2) all...... the estimators are fairly robust to conditionally heteroscedastic errors, (3) the local polynomial Whittle and bias-reduced log-periodogram regression estimators are shown to be more robust to short-run dynamics than other semiparametric (frequency domain and wavelet) estimators and in some cases even outperform...
Institute of Scientific and Technical Information of China (English)
Tao Hu; Heng-jian Cui; Xing-wei Tong
2009-01-01
This article considers a semiparametric varying-coefficient partially linear regression model with current status data. The semiparametric varying-coefficient partially linear regression model which is a gen-eralization of the partially linear regression model and varying-coefficient regression model that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable. A Sieve maximum likelihood estimation method is proposed and the asymptotic properties of the proposed estimators are discussed. Under some mild conditions, the estimators are shown to be strongly consistent. The convergence rate of the estima-tor for the unknown smooth function is obtained and the estimator for the unknown parameter is shown to be asymptotically efficient and normally distributed. Simulation studies are conducted to examine the small-sample properties of the proposed estimates and a real dataset is used to illustrate our approach.
Institute of Scientific and Technical Information of China (English)
孙孝前; 尤进红
2003-01-01
In this paper we consider the estimating problem of a semiparametric regression modelling whenthe data are longitudinal. An iterative weighted partial spline least squares estimator (IWPSLSE) for the para-metric component is proposed which is more efficient than the weighted partial spline least squares estimator(WPSLSE) with weights constructed by using the within-group partial spline least squares residuals in the senseof asymptotic variance. The asymptotic normality of this IWPSLSE is established. An adaptive procedure ispresented which ensures that the iterative process stops after a finite number of iterations and produces anestimator asymptotically equivalent to the best estimator that can be obtained by using the iterative proce-dure. These results are generalizations of those in heteroscedastic linear model to the case of semiparametric regression.
Tang, An-Min; Tang, Nian-Sheng
2015-02-28
We propose a semiparametric multivariate skew-normal joint model for multivariate longitudinal and multivariate survival data. One main feature of the posited model is that we relax the commonly used normality assumption for random effects and within-subject error by using a centered Dirichlet process prior to specify the random effects distribution and using a multivariate skew-normal distribution to specify the within-subject error distribution and model trajectory functions of longitudinal responses semiparametrically. A Bayesian approach is proposed to simultaneously obtain Bayesian estimates of unknown parameters, random effects and nonparametric functions by combining the Gibbs sampler and the Metropolis-Hastings algorithm. Particularly, a Bayesian local influence approach is developed to assess the effect of minor perturbations to within-subject measurement error and random effects. Several simulation studies and an example are presented to illustrate the proposed methodologies.
Nikulin, M; Mesbah, M; Limnios, N
2004-01-01
Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.
Institute of Scientific and Technical Information of China (English)
Xuemei HU; Feng LIU; Zhizhong WANG
2009-01-01
The authors propose a V_(N,P) test statistic for testing finite-order serial correlation in a semiparametric varying coefficient partially linear errors-in-variables model. The test statistic is shown to have asymptotic normal distribution under the null hypothesis of no serial correlation. Some Monte Carlo experiments are conducted to examine the finite sample performance of the proposed V_(N,P) test statistic. Simulation results confirm that the proposed test performs satisfactorily in estimated size and power.
Semiparametric Decomposition of the Gender Achievement Gap : An Application for Turkey
2012-01-01
Using the data from the 2006 Programme for International Student Assessment (PISA), this study sheds light on the gender gap in mathematics and science achievement of 15-year-olds in Turkey. We apply a semiparametric Oaxaca-Blinder (OB) decomposition to investigate the gap. This technique relaxes the parametric assumptions of the standard OB decomposition, accounts for the possible violation of the common support assumption and allows us to explore the gender test score gap not only at the me...
A Semiparametric Analysis of Gasoline Demand in the US: Reexamining The Impact of Price
Manzan, sebastiano; Zerom, Dawit
2008-01-01
The evaluation of the impact of an increase in gasoline tax on demand relies crucially on the estimate of the price elasticity. This paper presents an extended application of the Partially Linear Additive Model (PLAM) to the analysis of gasoline demand using a panel of US households, focusing mainly on the estimation of the price elasticity. Unlike previous semi-parametric studies that use household-level data, we work with vehicle-level data within households that can potentially add richer ...
Asymptotic Properties in Semiparametric Partially Linear Regression Models for Functional Data
Institute of Scientific and Technical Information of China (English)
Tao ZHANG
2013-01-01
We consider the semiparametric partially linear regression models with mean function xTβ+g(z),where X and z are functional data.The new estimators of β and g(z) are presented and some asymptotic results are given.The strong convergence rates of the proposed estimators are obtained.In our estimation,the observation number of each subject will be completely flexible.Some simulation study is conducted to investigate the finite sample performance of the proposed estimators.
Semiparametric modeling: Correcting low-dimensional model error in parametric models
Berry, Tyrus; Harlim, John
2016-03-01
In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consists of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.
2007-12-01
A mixture experiment involves combining two or more components in various proportions or amounts and then measuring one or more responses for the resulting end products. Other factors that affect the response(s), such as process variables and/or the total amount of the mixture, may also be studied in the experiment. A mixture experiment design specifies the combinations of mixture components and other experimental factors (if any) to be studied and the response variable(s) to be measured. Mixture experiment data analyses are then used to achieve the desired goals, which may include (i) understanding the effects of components and other factors on the response(s), (ii) identifying components and other factors with significant and nonsignificant effects on the response(s), (iii) developing models for predicting the response(s) as functions of the mixture components and any other factors, and (iv) developing end-products with desired values and uncertainties of the response(s). Given a mixture experiment problem, a practitioner must consider the possible approaches for designing the experiment and analyzing the data, and then select the approach best suited to the problem. Eight possible approaches include 1) component proportions, 2) mathematically independent variables, 3) slack variable, 4) mixture amount, 5) component amounts, 6) mixture process variable, 7) mixture of mixtures, and 8) multi-factor mixture. The article provides an overview of the mixture experiment designs, models, and data analyses for these approaches.
Crash risk analysis for Shanghai urban expressways: A Bayesian semi-parametric modeling approach.
Yu, Rongjie; Wang, Xuesong; Yang, Kui; Abdel-Aty, Mohamed
2016-10-01
Urban expressway systems have been developed rapidly in recent years in China; it has become one key part of the city roadway networks as carrying large traffic volume and providing high traveling speed. Along with the increase of traffic volume, traffic safety has become a major issue for Chinese urban expressways due to the frequent crash occurrence and the non-recurrent congestions caused by them. For the purpose of unveiling crash occurrence mechanisms and further developing Active Traffic Management (ATM) control strategies to improve traffic safety, this study developed disaggregate crash risk analysis models with loop detector traffic data and historical crash data. Bayesian random effects logistic regression models were utilized as it can account for the unobserved heterogeneity among crashes. However, previous crash risk analysis studies formulated random effects distributions in a parametric approach, which assigned them to follow normal distributions. Due to the limited information known about random effects distributions, subjective parametric setting may be incorrect. In order to construct more flexible and robust random effects to capture the unobserved heterogeneity, Bayesian semi-parametric inference technique was introduced to crash risk analysis in this study. Models with both inference techniques were developed for total crashes; semi-parametric models were proved to provide substantial better model goodness-of-fit, while the two models shared consistent coefficient estimations. Later on, Bayesian semi-parametric random effects logistic regression models were developed for weekday peak hour crashes, weekday non-peak hour crashes, and weekend non-peak hour crashes to investigate different crash occurrence scenarios. Significant factors that affect crash risk have been revealed and crash mechanisms have been concluded.
Adaptivity Assessment of Regional Semi-Parametric VTEC Modeling to Different Data Distributions
Durmaz, Murat; Onur Karslıoǧlu, Mahmut
2014-05-01
Semi-parametric modelling of Vertical Total Electron Content (VTEC) combines parametric and non-parametric models into a single regression model for estimating the parameters and functions from Global Positioning System (GPS) observations. The parametric part is related to the Differential Code Biases (DCBs), which are fixed unknown parameters of the geometry-free linear combination (or the so called ionospheric observable). On the other hand, the non-parametric component is referred to the spatio-temporal distribution of VTEC which is estimated by applying the method of Multivariate Adaptive Regression B-Splines (BMARS). BMARS algorithm builds an adaptive model by using tensor product of univariate B-splines that are derived from the data. The algorithm searches for best fitting B-spline basis functions in a scale by scale strategy, where it starts adding large scale B-splines to the model and adaptively decreases the scale for including smaller scale features through a modified Gram-Schmidt ortho-normalization process. Then, the algorithm is extended to include the receiver DCBs where the estimates of the receiver DCBs and the spatio-temporal VTEC distribution can be obtained together in an adaptive semi-parametric model. In this work, the adaptivity of regional semi-parametric modelling of VTEC based on BMARS is assessed in different ground-station and data distribution scenarios. To evaluate the level of adaptivity the resulting DCBs and VTEC maps from different scenarios are compared not only with each other but also with CODE distributed GIMs and DCB estimates .
Adaptive semiparametric wavelet estimator and goodness-of-fit test for long memory linear processes
Bardet, Jean-Marc
2010-01-01
This paper is first devoted to study an adaptive wavelet based estimator of the long memory parameter for linear processes in a general semi-parametric frame. This is an extension of Bardet {\\it et al.} (2008) which only concerned Gaussian processes. Moreover, the definition of the long memory parameter estimator is modified and asymptotic results are improved even in the Gaussian case. Finally an adaptive goodness-of-fit test is also built and easy to be employed: it is a chi-square type test. Simulations confirm the interesting properties of consistency and robustness of the adaptive estimator and test.
Modelling asset correlations during the recent financial crisis: A semiparametric approach
DEFF Research Database (Denmark)
Aslanidis, Nektarios; Casas, Isabel
This article proposes alternatives to the Dynamic Conditional Correlation (DCC) model to study assets' correlations during the recent financial crisis. In particular, we adopt a semiparametric and nonparametric approach to estimate the conditional correlations for two interesting portfolios....... The first portfolio consists of equity sectors SPDRs and the S&P 500 composite, while the second one contains major currencies that are actively traded in the foreign exchange market. Methodologically, our contribution is two fold. First, we propose the Local Linear (LL) estimator for the correlations...
Generalized Empirical Likelihood Inference in Semiparametric Regression Model for Longitudinal Data
Institute of Scientific and Technical Information of China (English)
Gao Rong LI; Ping TIAN; Liu Gen XUE
2008-01-01
In this paper, we consider the semiparametric regression model for longitudinal data. Due to the correlation within groups, a generalized empirical log-likelihood ratio statistic for the unknown parameters in the model is suggested by introducing the working covariance matrix. It is proved that the proposed statistic is asymptotically standard chi-squared under some suitable conditions, and hence it can be used to construct the confidence regions of the parameters. A simulation study is conducted to compare the proposed method with the generalized least squares method in terms of coverage accuracy and average lengths of the confidence intervals.
Institute of Scientific and Technical Information of China (English)
Pei Xin ZHAO; Liu Gen XUE
2011-01-01
In this paper,we present a variable selection procedure by combining basis function approximations with penalized estimating equations for semiparametric varying-coefficient partially linear models with missing response at random.The proposed procedure simultaneously selects significant variables in parametric components and nonparametric components.With appropriate selection of the tuning parameters,we establish the consistency of the variable selection procedure and the convergence rate of the regularized estimators.A simulation study is undertaken to assess the finite sample performance of the proposed variable selection procedure.
Distributed Nonparametric and Semiparametric Regression on SPARK for Big Data Forecasting
Directory of Open Access Journals (Sweden)
Jelena Fiosina
2017-01-01
Full Text Available Forecasting in big datasets is a common but complicated task, which cannot be executed using the well-known parametric linear regression. However, nonparametric and semiparametric methods, which enable forecasting by building nonlinear data models, are computationally intensive and lack sufficient scalability to cope with big datasets to extract successful results in a reasonable time. We present distributed parallel versions of some nonparametric and semiparametric regression models. We used MapReduce paradigm and describe the algorithms in terms of SPARK data structures to parallelize the calculations. The forecasting accuracy of the proposed algorithms is compared with the linear regression model, which is the only forecasting model currently having parallel distributed realization within the SPARK framework to address big data problems. The advantages of the parallelization of the algorithm are also provided. We validate our models conducting various numerical experiments: evaluating the goodness of fit, analyzing how increasing dataset size influences time consumption, and analyzing time consumption by varying the degree of parallelism (number of workers in the distributed realization.
A semiparametric Wald statistic for testing logistic regression models based on case-control data
Institute of Scientific and Technical Information of China (English)
WAN ShuWen
2008-01-01
We propose a semiparametric Wald statistic to test the validity of logistic regression models based on case-control data.The test statistic is constructed using a semiparametric ROC curve estimator and a nonparametric ROC curve estimator.The statistic has an asymptotic chi-squared distribution and is an alternative to the Kolmogorov-Smirnov-type statistic proposed by Qin and Zhang in 1997,the chi-squared-type statistic proposed by Zhang in 1999 and the information matrix test statistic proposed by Zhang in 2001.The statistic is easy to compute in the sense that it requires none of the following methods:using a bootstrap method to find its critical values,partitioning the sample data or inverting a high-dimensional matrix.We present some results on simulation and on analysis of two real examples.Moreover,we discuss how to extend our statistic to a family of statistics and how to construct its Kolmogorov-Smirnov counterpart.
Sieve M-estimation for semiparametric varying-coefficient partially linear regression model
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
This article considers a semiparametric varying-coefficient partially linear regression model.The semiparametric varying-coefficient partially linear regression model which is a generalization of the partially linear regression model and varying-coefficient regression model that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable.A sieve M-estimation method is proposed and the asymptotic properties of the proposed estimators are discussed.Our main object is to estimate the nonparametric component and the unknown parameters simultaneously.It is easier to compute and the required computation burden is much less than the existing two-stage estimation method.Furthermore,the sieve M-estimation is robust in the presence of outliers if we choose appropriate ρ(·).Under some mild conditions,the estimators are shown to be strongly consistent;the convergence rate of the estimator for the unknown nonparametric component is obtained and the estimator for the unknown parameter is shown to be asymptotically normally distributed.Numerical experiments are carried out to investigate the performance of the proposed method.
Ilmonen, Pauliina; 10.1214/11-AOS906
2012-01-01
We consider semiparametric location-scatter models for which the $p$-variate observation is obtained as $X=\\Lambda Z+\\mu$, where $\\mu$ is a $p$-vector, $\\Lambda$ is a full-rank $p\\times p$ matrix and the (unobserved) random $p$-vector $Z$ has marginals that are centered and mutually independent but are otherwise unspecified. As in blind source separation and independent component analysis (ICA), the parameter of interest throughout the paper is $\\Lambda$. On the basis of $n$ i.i.d. copies of $X$, we develop, under a symmetry assumption on $Z$, signed-rank one-sample testing and estimation procedures for $\\Lambda$. We exploit the uniform local and asymptotic normality (ULAN) of the model to define signed-rank procedures that are semiparametrically efficient under correctly specified densities. Yet, as is usual in rank-based inference, the proposed procedures remain valid (correct asymptotic size under the null, for hypothesis testing, and root-$n$ consistency, for point estimation) under a very broad range of ...
Cheng, Guang
2014-02-01
We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based on a spline approximation of the nonparametric part of the model and the generalized estimating equations (GEE). Although the model in consideration is natural and useful in many practical applications, the literature on this model is very limited because of challenges in dealing with dependent data for nonparametric additive models. We show that the proposed estimators are consistent and asymptotically normal even if the covariance structure is misspecified. An explicit consistent estimate of the asymptotic variance is also provided. Moreover, we derive the semiparametric efficiency score and information bound under general moment conditions. By showing that our estimators achieve the semiparametric information bound, we effectively establish their efficiency in a stronger sense than what is typically considered for GEE. The derivation of our asymptotic results relies heavily on the empirical processes tools that we develop for the longitudinal/clustered data. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2014 ISI/BS.
DEFF Research Database (Denmark)
Grislain-Letrémy, Céline; Katossky, Arthur
2014-01-01
on the housing values strongly differs among these three areas, even if the areas all surround chemical and petrochemical industries. We compare the results from both standard parametric and more flexible, semiparametric models of hedonic property. We show that the parametric model might structurally lead...
Network Applications for Group-Based Learning: Is More Better?
Veen, Jan; Collis, Betty; Jones, Val
2003-01-01
Group-based learning is being introduced into many settings in higher education. Is this a sustainable development with respect to the resources required? Under what conditions can group-based learning be applied successfully in distance education and in increasingly flexible campus-based learning? Can networked support facilitate and enrich…
A Robbins-Monro procedure for estimation in semiparametric regression models
Bercu, Bernard
2011-01-01
This paper is devoted to the parametric estimation of a shift together with the nonparametric estimation of a regression function in a semiparametric regression model. We implement a Robbins-Monro procedure very efficient and easy to handle. On the one hand, we propose a stochastic algorithm similar to that of Robbins-Monro in order to estimate the shift parameter. A preliminary evaluation of the regression function is not necessary for estimating the shift parameter. On the other hand, we make use of a recursive Nadaraya-Watson estimator for the estimation of the regression function. This kernel estimator takes in account the previous estimation of the shift parameter. We establish the almost sure convergence for both Robbins-Monro and Nadaraya-Watson estimators. The asymptotic normality of our estimates is also provided.
Zhao, Tuo; Liu, Han
2016-01-01
We propose an accelerated path-following iterative shrinkage thresholding algorithm (APISTA) for solving high dimensional sparse nonconvex learning problems. The main difference between APISTA and the path-following iterative shrinkage thresholding algorithm (PISTA) is that APISTA exploits an additional coordinate descent subroutine to boost the computational performance. Such a modification, though simple, has profound impact: APISTA not only enjoys the same theoretical guarantee as that of PISTA, i.e., APISTA attains a linear rate of convergence to a unique sparse local optimum with good statistical properties, but also significantly outperforms PISTA in empirical benchmarks. As an application, we apply APISTA to solve a family of nonconvex optimization problems motivated by estimating sparse semiparametric graphical models. APISTA allows us to obtain new statistical recovery results which do not exist in the existing literature. Thorough numerical results are provided to back up our theory. PMID:28133430
Asymptotic properties for the semiparametric regression model with randomly censored data
Institute of Scientific and Technical Information of China (English)
王启华; 郑忠国
1997-01-01
Suppose that the patients’ survival times,Y,are random variables following the semiparametric regression model Y=Xβ+g(T)+ε,where (X,T) is a radom vector taking values in R×[0,1],β is an unknown parameter,g(·) is an unknown smooth regression function and εis the random error with zero mean and variance σ2.It is assumed that (X,T) is independent of ε.The estimators βn and gm(·) ofβ and g(·) are defined,respectively,when the observations are randomly censored on the right and the censoring distribution is unknown.Moreover,it isshown that βm is asymptotically normal and gm(·) is weak consistence with rate Op(n-1/3).
Penalized variable selection procedure for Cox models with semiparametric relative risk
Du, Pang; Liang, Hua; 10.1214/09-AOS780
2010-01-01
We study the Cox models with semiparametric relative risk, which can be partially linear with one nonparametric component, or multiple additive or nonadditive nonparametric components. A penalized partial likelihood procedure is proposed to simultaneously estimate the parameters and select variables for both the parametric and the nonparametric parts. Two penalties are applied sequentially. The first penalty, governing the smoothness of the multivariate nonlinear covariate effect function, provides a smoothing spline ANOVA framework that is exploited to derive an empirical model selection tool for the nonparametric part. The second penalty, either the smoothly-clipped-absolute-deviation (SCAD) penalty or the adaptive LASSO penalty, achieves variable selection in the parametric part. We show that the resulting estimator of the parametric part possesses the oracle property, and that the estimator of the nonparametric part achieves the optimal rate of convergence. The proposed procedures are shown to work well i...
Estimation in semi-parametric regression with non-stationary regressors
Chen, Jia; Li, Degui; 10.3150/10-BEJ344
2012-01-01
In this paper, we consider a partially linear model of the form $Y_t=X_t^{\\tau}\\theta_0+g(V_t)+\\epsilon_t$, $t=1,...,n$, where $\\{V_t\\}$ is a $\\beta$ null recurrent Markov chain, $\\{X_t\\}$ is a sequence of either strictly stationary or non-stationary regressors and $\\{\\epsilon_t\\}$ is a stationary sequence. We propose to estimate both $\\theta_0$ and $g(\\cdot)$ by a semi-parametric least-squares (SLS) estimation method. Under certain conditions, we then show that the proposed SLS estimator of $\\theta_0$ is still asymptotically normal with the same rate as for the case of stationary time series. In addition, we also establish an asymptotic distribution for the nonparametric estimator of the function $g(\\cdot)$. Some numerical examples are provided to show that our theory and estimation method work well in practice.
Institute of Scientific and Technical Information of China (English)
2009-01-01
In this paper, we study the local asymptotic behavior of the regression spline estimator in the framework of marginal semiparametric model. Similarly to Zhu, Fung and He (2008), we give explicit expression for the asymptotic bias of regression spline estimator for nonparametric function f. Our results also show that the asymptotic bias of the regression spline estimator does not depend on the working covariance matrix, which distinguishes the regression splines from the smoothing splines and the seemingly unrelated kernel. To understand the local bias result of the regression spline estimator, we show that the regression spline estimator can be obtained iteratively by applying the standard weighted least squares regression spline estimator to pseudo-observations. At each iteration, the bias of the estimator is unchanged and only the variance is updated.
[download] (1035Coordinate Descent Methods for the Penalized Semiparametric Additive Hazards Model
Directory of Open Access Journals (Sweden)
Anders Gorst-Rasmussen
2012-04-01
Full Text Available For survival data with a large number of explanatory variables, lasso penalized Cox regression is a popular regularization strategy. However, a penalized Cox model may not always provide the best fit to data and can be difficult to estimate in high dimension because of its intrinsic nonlinearity. The semiparametric additive hazards model is a flexible alternative which is a natural survival analogue of the standard linear regression model. Building on this analogy, we develop a cyclic coordinate descent algorithm for fitting the lasso and elastic net penalized additive hazards model. The algorithm requires no nonlinear optimization steps and offers excellent performance and stability. An implementation is available in the R package ahaz. We demonstrate this implementation in a small timing study and in an application to real data.
Bayesian semiparametric power spectral density estimation in gravitational wave data analysis
Edwards, Matthew C; Christensen, Nelson
2015-01-01
The standard noise model in gravitational wave (GW) data analysis assumes detector noise is stationary and Gaussian distributed, with a known power spectral density (PSD) that is usually estimated using clean off-source data. Real GW data often depart from these assumptions, and misspecified parametric models of the PSD could result in misleading inferences. We propose a Bayesian semiparametric approach to improve this. We use a nonparametric Bernstein polynomial prior on the PSD, with weights attained via a Dirichlet process distribution, and update this using the Whittle likelihood. Posterior samples are obtained using a Metropolis-within-Gibbs sampler. We simultaneously estimate the reconstruction parameters of a rotating core collapse supernova GW burst that has been embedded in simulated Advanced LIGO noise. We also discuss an approach to deal with non-stationary data by breaking longer data streams into smaller and locally stationary components.
Convergence Rates of Wavelet Estimators in Semiparametric Regression Models Under NA Samples
Institute of Scientific and Technical Information of China (English)
Hongchang HU; Li WU
2012-01-01
Consider the following heteroscedastic semiparametric regression model:yi =XTiβ + g(ti) + σiei, 1 ＜ i ≤ n,where {Xi,1 ＜ i ＜ n} are random design points,errors {ei,1 ＜ i ＜ n} are negatively associated (NA) random variables,σ2i =h(ui),and {ui} and {ti} are two nonrandom sequences on [0,1].Some wavelet estimators of the parametric component β,the nonparametric component g(t) and the variance function h(u) are given.Under some general conditions,the strong convergence rate of these wavelet estimators is O(n -1/3 log n).Hence our results are extensions of those results on independent random error settings.
Johnson, Lynn M; Strawderman, Robert L
2012-09-20
This paper proposes an estimation procedure for the semiparametric accelerated failure time frailty model that combines smoothing with an Expectation and Maximization-like algorithm for estimating equations. The resulting algorithm permits simultaneous estimation of the regression parameter, the baseline cumulative hazard, and the parameter indexing a general frailty distribution. We develop novel moment-based estimators for the frailty parameter, including a generalized method of moments estimator. Standard error estimates for all parameters are easily obtained using a randomly weighted bootstrap procedure. For the commonly used gamma frailty distribution, the proposed algorithm is very easy to implement using widely available numerical methods. Simulation results demonstrate that the algorithm performs very well in this setting. We re-analyz several previously analyzed data sets for illustrative purposes.
Testing the trajectory difference in a semi-parametric longitudinal model.
Niu, Feiyang; Zhou, Jianhui; Le, Thu H; Ma, Jennie Z
2017-06-01
Motivated by a genetic investigation on the progressive decline in renal function in a clinical trial study of kidney disease, we develop a practical test for evaluating the group difference in trajectories under a semi-parametric modeling framework. For the temporal patterns or trajectories of longitudinal data, B-splines are used to approximate the function non-parametrically. Such approximation asymptotically converts the problem of testing trajectory difference into the significance test of regression coefficients that can be simply estimated by generalized estimating equations. To select the optimal number of inner knots for B-splines, a cross-validation procedure is performed using the criterion of the generalized residual sum of squares. The new proposed test successfully detects a significant difference of underlying genetic impact on the progression of renal disease, which is not captured by the parametric approach.
A Semi-parametric Bayesian Approach for Differential Expression Analysis of RNA-seq Data.
Liu, Fangfang; Wang, Chong; Liu, Peng
2015-12-01
RNA-sequencing (RNA-seq) technologies have revolutionized the way agricultural biologists study gene expression as well as generated a tremendous amount of data waiting for analysis. Detecting differentially expressed genes is one of the fundamental steps in RNA-seq data analysis. In this paper, we model the count data from RNA-seq experiments with a Poisson-Gamma hierarchical model, or equivalently, a negative binomial (NB) model. We derive a semi-parametric Bayesian approach with a Dirichlet process as the prior model for the distribution of fold changes between the two treatment means. An inference strategy using Gibbs algorithm is developed for differential expression analysis. The results of several simulation studies show that our proposed method outperforms other methods including the popularly applied edgeR and DESeq methods. We also discuss an application of our method to a dataset that compares gene expression between bundle sheath and mesophyll cells in maize leaves.
Directory of Open Access Journals (Sweden)
Zhike Lv
2014-01-01
Full Text Available A large body of literature studies on the relationship between health care expenditure (HCE and GDP have been analyzed using data intensively from developed countries, but little is known for other regions. This paper considers a semiparametric panel data analysis for the study of the relationship between per capita HCE and per capita GDP for 42 African countries over the period 1995–2009. We found that infant mortality rate per 1,000 live births has a negative effect on per capita HCE, while the proportion of the population aged 65 is statistically insignificant in African countries. Furthermore, we found that the income elasticity is not constant but varies with income level, and health care is a necessity rather than a luxury for African countries.
DEFF Research Database (Denmark)
Scheike, Thomas Harder
2002-01-01
We use the additive risk model of Aalen (Aalen, 1980) as a model for the rate of a counting process. Rather than specifying the intensity, that is the instantaneous probability of an event conditional on the entire history of the relevant covariates and counting processes, we present a model...... for the rate function, i.e., the instantaneous probability of an event conditional on only a selected set of covariates. When the rate function for the counting process is of Aalen form we show that the usual Aalen estimator can be used and gives almost unbiased estimates. The usual martingale based variance...... estimator is incorrect and an alternative estimator should be used. We also consider the semi-parametric version of the Aalen model as a rate model (McKeague and Sasieni, 1994) and show that the standard errors that are computed based on an assumption of intensities are incorrect and give a different...
truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models
Directory of Open Access Journals (Sweden)
Maria Karlsson
2014-05-01
Full Text Available Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use. Alternative estimators, designed for the estimation of truncated regression models, have been developed. This paper presents the R package truncSP. The package contains functions for the estimation of semi-parametric truncated linear regression models using three different estimators: the symmetrically trimmed least squares, quadratic mode, and left truncated estimators, all of which have been shown to have good asymptotic and ?nite sample properties. The package also provides functions for the analysis of the estimated models. Data from the environmental sciences are used to illustrate the functions in the package.
New Inference Procedures for Semiparametric Varying-Coefficient Partially Linear Cox Models
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Yunbei Ma
2014-01-01
Full Text Available In biomedical research, one major objective is to identify risk factors and study their risk impacts, as this identification can help clinicians to both properly make a decision and increase efficiency of treatments and resource allocation. A two-step penalized-based procedure is proposed to select linear regression coefficients for linear components and to identify significant nonparametric varying-coefficient functions for semiparametric varying-coefficient partially linear Cox models. It is shown that the penalized-based resulting estimators of the linear regression coefficients are asymptotically normal and have oracle properties, and the resulting estimators of the varying-coefficient functions have optimal convergence rates. A simulation study and an empirical example are presented for illustration.
Ma, Yanyuan
2013-09-01
We propose semiparametric methods to estimate the center and shape of a symmetric population when a representative sample of the population is unavailable due to selection bias. We allow an arbitrary sample selection mechanism determined by the data collection procedure, and we do not impose any parametric form on the population distribution. Under this general framework, we construct a family of consistent estimators of the center that is robust to population model misspecification, and we identify the efficient member that reaches the minimum possible estimation variance. The asymptotic properties and finite sample performance of the estimation and inference procedures are illustrated through theoretical analysis and simulations. A data example is also provided to illustrate the usefulness of the methods in practice. © 2013 American Statistical Association.
Bayesian spatial semi-parametric modeling of HIV variation in Kenya.
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Oscar Ngesa
Full Text Available Spatial statistics has seen rapid application in many fields, especially epidemiology and public health. Many studies, nonetheless, make limited use of the geographical location information and also usually assume that the covariates, which are related to the response variable, have linear effects. We develop a Bayesian semi-parametric regression model for HIV prevalence data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (McMC. The model is applied to HIV prevalence data among men in Kenya, derived from the Kenya AIDS indicator survey, with n = 3,662. Past studies have concluded that HIV infection has a nonlinear association with age. In this study a smooth function based on penalized regression splines is used to estimate this nonlinear effect. Other covariates were assumed to have a linear effect. Spatial references to the counties were modeled as both structured and unstructured spatial effects. We observe that circumcision reduces the risk of HIV infection. The results also indicate that men in the urban areas were more likely to be infected by HIV as compared to their rural counterpart. Men with higher education had the lowest risk of HIV infection. A nonlinear relationship between HIV infection and age was established. Risk of HIV infection increases with age up to the age of 40 then declines with increase in age. Men who had STI in the last 12 months were more likely to be infected with HIV. Also men who had ever used a condom were found to have higher likelihood to be infected by HIV. A significant spatial variation of HIV infection in Kenya was also established. The study shows the practicality and flexibility of Bayesian semi-parametric regression model in analyzing epidemiological data.
Point Groups Based on Methane and Adamantane (Td) Skeletons.
Fujita, Shinsaku
1986-01-01
Describes a procedure for constructing point groups based on the symmetric parent molecules of methane and adamantane. Intended for use in teaching concepts such as subgroups and cosets to beginners in group theory. (TW)
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GUSTI AYU RATIH ASTARI
2013-11-01
Full Text Available Dropout number is one of the important indicators to measure the human progress resources in education sector. This research uses the approaches of Semi-parametric Geographically Weighted Poisson Regression to get the best model and to determine the influencing factors of dropout number for primary education in Bali. The analysis results show that there are no significant differences between the Poisson regression model with GWPR and Semi-parametric GWPR. Factors which significantly influence the dropout number for primary education in Bali are the ratio of students to school, ratio of students to teachers, the number of families with the latest educational fathers is elementary or junior high school, illiteracy rates, and the average number of family members.
Reducing Social Loafing in Group-Based Projects
Perron, Brian E.
2011-01-01
Social loafing in group-based projects is a common problem for college teachers. This problem has received great attention, including a Quick Fix article by Stevens (2007), whose recommendations remain useful today, particularly the mechanism for peer evaluations--a key strategy for reducing social loafing. Since the publication of Stevens's…
Semiparametric models of time-dependent predictive values of prognostic biomarkers.
Zheng, Yingye; Cai, Tianxi; Stanford, Janet L; Feng, Ziding
2010-03-01
Rigorous statistical evaluation of the predictive values of novel biomarkers is critical prior to applying novel biomarkers into routine standard care. It is important to identify factors that influence the performance of a biomarker in order to determine the optimal conditions for test performance. We propose a covariate-specific time-dependent positive predictive values curve to quantify the predictive accuracy of a prognostic marker measured on a continuous scale and with censored failure time outcome. The covariate effect is accommodated with a semiparametric regression model framework. In particular, we adopt a smoothed survival time regression technique (Dabrowska, 1997, The Annals of Statistics 25, 1510-1540) to account for the situation where risk for the disease occurrence and progression is likely to change over time. In addition, we provide asymptotic distribution theory and resampling-based procedures for making statistical inference on the covariate-specific positive predictive values. We illustrate our approach with numerical studies and a dataset from a prostate cancer study.
A Robust Semi-Parametric Test for Detecting Trait-Dependent Diversification.
Rabosky, Daniel L; Huang, Huateng
2016-03-01
Rates of species diversification vary widely across the tree of life and there is considerable interest in identifying organismal traits that correlate with rates of speciation and extinction. However, it has been challenging to develop methodological frameworks for testing hypotheses about trait-dependent diversification that are robust to phylogenetic pseudoreplication and to directionally biased rates of character change. We describe a semi-parametric test for trait-dependent diversification that explicitly requires replicated associations between character states and diversification rates to detect effects. To use the method, diversification rates are reconstructed across a phylogenetic tree with no consideration of character states. A test statistic is then computed to measure the association between species-level traits and the corresponding diversification rate estimates at the tips of the tree. The empirical value of the test statistic is compared to a null distribution that is generated by structured permutations of evolutionary rates across the phylogeny. The test is applicable to binary discrete characters as well as continuous-valued traits and can accommodate extremely sparse sampling of character states at the tips of the tree. We apply the test to several empirical data sets and demonstrate that the method has acceptable Type I error rates. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Characteristic function-based semiparametric inference for skew-symmetric models
Potgieter, Cornelis J.
2012-12-26
Skew-symmetric models offer a very flexible class of distributions for modelling data. These distributions can also be viewed as selection models for the symmetric component of the specified skew-symmetric distribution. The estimation of the location and scale parameters corresponding to the symmetric component is considered here, with the symmetric component known. Emphasis is placed on using the empirical characteristic function to estimate these parameters. This is made possible by an invariance property of the skew-symmetric family of distributions, namely that even transformations of random variables that are skew-symmetric have a distribution only depending on the symmetric density. A distance metric between the real components of the empirical and true characteristic functions is minimized to obtain the estimators. The method is semiparametric, in that the symmetric component is specified, but the skewing function is assumed unknown. Furthermore, the methodology is extended to hypothesis testing. Two tests for a hypothesis of specific parameter values are considered, as well as a test for the hypothesis that the symmetric component has a specific parametric form. A resampling algorithm is described for practical implementation of these tests. The outcomes of various numerical experiments are presented. © 2012 Board of the Foundation of the Scandinavian Journal of Statistics.
Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach
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Oliveira Rui
2010-09-01
Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.
Semiparametric approach for non-monotone missing covariates in a parametric regression model
Sinha, Samiran
2014-02-26
Missing covariate data often arise in biomedical studies, and analysis of such data that ignores subjects with incomplete information may lead to inefficient and possibly biased estimates. A great deal of attention has been paid to handling a single missing covariate or a monotone pattern of missing data when the missingness mechanism is missing at random. In this article, we propose a semiparametric method for handling non-monotone patterns of missing data. The proposed method relies on the assumption that the missingness mechanism of a variable does not depend on the missing variable itself but may depend on the other missing variables. This mechanism is somewhat less general than the completely non-ignorable mechanism but is sometimes more flexible than the missing at random mechanism where the missingness mechansim is allowed to depend only on the completely observed variables. The proposed approach is robust to misspecification of the distribution of the missing covariates, and the proposed mechanism helps to nullify (or reduce) the problems due to non-identifiability that result from the non-ignorable missingness mechanism. The asymptotic properties of the proposed estimator are derived. Finite sample performance is assessed through simulation studies. Finally, for the purpose of illustration we analyze an endometrial cancer dataset and a hip fracture dataset.
Conditional maximum likelihood estimation in semiparametric transformation model with LTRC data.
Chen, Chyong-Mei; Shen, Pao-Sheng
2017-02-06
Left-truncated data often arise in epidemiology and individual follow-up studies due to a biased sampling plan since subjects with shorter survival times tend to be excluded from the sample. Moreover, the survival time of recruited subjects are often subject to right censoring. In this article, a general class of semiparametric transformation models that include proportional hazards model and proportional odds model as special cases is studied for the analysis of left-truncated and right-censored data. We propose a conditional likelihood approach and develop the conditional maximum likelihood estimators (cMLE) for the regression parameters and cumulative hazard function of these models. The derived score equations for regression parameter and infinite-dimensional function suggest an iterative algorithm for cMLE. The cMLE is shown to be consistent and asymptotically normal. The limiting variances for the estimators can be consistently estimated using the inverse of negative Hessian matrix. Intensive simulation studies are conducted to investigate the performance of the cMLE. An application to the Channing House data is given to illustrate the methodology.
Testing Serial Correlation in Semiparametric Varying-Coefficient Partially Linear EV Models
Institute of Scientific and Technical Information of China (English)
Xue-mei Hu; Zhi-zhong Wang; Feng Liu
2008-01-01
This paper studies estimation and serial correlation test of a semiparametric varying-coefficient partially linear EV model of the form Y = Xτβ + Zτα(T) + ε,ξ = X + η with the identifying condition E[(ε,ητ)τ] = 0, Cov[(ε,ητ)τ] = σ2Iρ+1. The estimators of interested regression parameters β, and the model error variance σ2, as well as the nonparametric components α(T), are constructed. Under some regular conditions, we show that the estimators of the unknown vector β and the unknown parameter σ2 are strongly consistent and asymptotically normal and that the estimator of α(T) achieves the optimal strong convergence rate of the usual nonparametric regression. Based on these estimators and asymptotic properties, we propose the VN,p test statistic and empirical log-likelihood ratio statistic for testing serial correlation in the model. The proposed statistics are shown to have asymptotic normal or chi-square distributions under the null hypothesis of no serial correlation. Some simulation studies are conducted to illustrate the finite sample performance of the proposed tests.
Semiparametric approach for non-monotone missing covariates in a parametric regression model.
Sinha, Samiran; Saha, Krishna K; Wang, Suojin
2014-06-01
Missing covariate data often arise in biomedical studies, and analysis of such data that ignores subjects with incomplete information may lead to inefficient and possibly biased estimates. A great deal of attention has been paid to handling a single missing covariate or a monotone pattern of missing data when the missingness mechanism is missing at random. In this article, we propose a semiparametric method for handling non-monotone patterns of missing data. The proposed method relies on the assumption that the missingness mechanism of a variable does not depend on the missing variable itself but may depend on the other missing variables. This mechanism is somewhat less general than the completely non-ignorable mechanism but is sometimes more flexible than the missing at random mechanism where the missingness mechansim is allowed to depend only on the completely observed variables. The proposed approach is robust to misspecification of the distribution of the missing covariates, and the proposed mechanism helps to nullify (or reduce) the problems due to non-identifiability that result from the non-ignorable missingness mechanism. The asymptotic properties of the proposed estimator are derived. Finite sample performance is assessed through simulation studies. Finally, for the purpose of illustration we analyze an endometrial cancer dataset and a hip fracture dataset.
Wei, Jiawei
2011-07-01
We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work was originally motivated by a unique testing problem in genetic epidemiology (Chatterjee, et al., 2006) that involved a typical generalized linear model but with an additional term reminiscent of the Tukey one-degree-of-freedom formulation, and their interest was in testing for main effects of the genetic variables, while gaining statistical power by allowing for a possible interaction between genes and the environment. Later work (Maity, et al., 2009) involved the possibility of modeling the environmental variable nonparametrically, but they focused on whether there was a parametric main effect for the genetic variables. In this paper, we consider the complementary problem, where the interest is in testing for the main effect of the nonparametrically modeled environmental variable. We derive a generalized likelihood ratio test for this hypothesis, show how to implement it, and provide evidence that our method can improve statistical power when compared to standard partially linear models with main effects only. We use the method for the primary purpose of analyzing data from a case-control study of colorectal adenoma.
Semiparametric analysis of incomplete current status outcome data under transformation models.
Wen, Chi-Chung; Chen, Yi-Hau
2014-06-01
This work, motivated by an osteoporosis survey study, considers regression analysis with incompletely observed current status data. Here the current status data, including an examination time and an indicator for whether or not the event of interest has occurred by the examination time, is not observed for all subjects. Instead, a surrogate outcome subject to misclassification of the current status is available for all subjects. We focus on semiparametric regression under transformation models, including the proportional hazards and proportional odds models as special cases. Under the missing at random mechanism where the missingness of the current status outcome can depend only on the observed surrogate outcome and covariates, we propose an approach of validation likelihood based on the likelihood from the validation subsample where the data are fully observed, with adjustments of the probability of observing the current status outcome, as well as the distribution of the surrogate outcome in the validation subsample. We propose an efficient computation algorithm for implementation, and derive consistency and asymptotic normality for inference with the proposed estimator. The application to the osteoporosis survey data and simulations reveal that the validation likelihood performs well; it removes the bias from the "complete case" analysis discarding subjects with missing data, and achieves higher efficiency than the inverse probability weighting analysis.
A Bayesian Semi-parametric Approach for the Differential Analysis of Sequence Counts Data.
Guindani, Michele; Sepúlveda, Nuno; Paulino, Carlos Daniel; Müller, Peter
2014-04-01
Data obtained using modern sequencing technologies are often summarized by recording the frequencies of observed sequences. Examples include the analysis of T cell counts in immunological research and studies of gene expression based on counts of RNA fragments. In both cases the items being counted are sequences, of proteins and base pairs, respectively. The resulting sequence-abundance distribution is usually characterized by overdispersion. We propose a Bayesian semi-parametric approach to implement inference for such data. Besides modeling the overdispersion, the approach takes also into account two related sources of bias that are usually associated with sequence counts data: some sequence types may not be recorded during the experiment and the total count may differ from one experiment to another. We illustrate our methodology with two data sets, one regarding the analysis of CD4+ T cell counts in healthy and diabetic mice and another data set concerning the comparison of mRNA fragments recorded in a Serial Analysis of Gene Expression (SAGE) experiment with gastrointestinal tissue of healthy and cancer patients.
A semi-parametric approach to the frequency of occurrence under a simple crossover trial.
Lui, Kung-Jong; Chang, Kuang-Chao
2016-02-01
To analyze the frequency of occurrence for an event of interest in a crossover design, we propose a semi-parametric approach. We develop two point estimators and four interval estimators in closed forms for the treatment effect under a random effects multiplicative risk model. Using Monte Carlo simulations, we evaluate these estimators and compare the four interval estimators with the classical interval estimator suggested elsewhere in a variety of situations. We note that the point estimator using the ratio of two arithmetic averages of mean frequencies under a multiplicative risk model can be comparable to the point estimator using the ratio of two geometric averages of mean frequencies. We note that as long as the number of patients per group is large, all the four interval estimators developed here can perform well. We also note that the classical interval estimator derived under the commonly assumed Poisson distribution for the frequency data can be conservative and lose precision if the Poisson distribution assumption is violated. We use a double-blind randomized crossover trial comparing salmeterol with a placebo in exacerbations of asthma to illustrate the practical use of these estimators. © The Author(s) 2012.
Chan, Kwun Chuen Gary; Wang, Mei-Cheng
2017-01-01
Recurrent event processes with marker measurements are mostly and largely studied with forward time models starting from an initial event. Interestingly, the processes could exhibit important terminal behavior during a time period before occurrence of the failure event. A natural and direct way to study recurrent events prior to a failure event is to align the processes using the failure event as the time origin and to examine the terminal behavior by a backward time model. This paper studies regression models for backward recurrent marker processes by counting time backward from the failure event. A three-level semiparametric regression model is proposed for jointly modeling the time to a failure event, the backward recurrent event process, and the marker observed at the time of each backward recurrent event. The first level is a proportional hazards model for the failure time, the second level is a proportional rate model for the recurrent events occurring before the failure event, and the third level is a proportional mean model for the marker given the occurrence of a recurrent event backward in time. By jointly modeling the three components, estimating equations can be constructed for marked counting processes to estimate the target parameters in the three-level regression models. Large sample properties of the proposed estimators are studied and established. The proposed models and methods are illustrated by a community-based AIDS clinical trial to examine the terminal behavior of frequencies and severities of opportunistic infections among HIV infected individuals in the last six months of life.
Kerfdr: a semi-parametric kernel-based approach to local false discovery rate estimation
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Robin Stephane
2009-03-01
Full Text Available Abstract Background The use of current high-throughput genetic, genomic and post-genomic data leads to the simultaneous evaluation of a large number of statistical hypothesis and, at the same time, to the multiple-testing problem. As an alternative to the too conservative Family-Wise Error-Rate (FWER, the False Discovery Rate (FDR has appeared for the last ten years as more appropriate to handle this problem. However one drawback of FDR is related to a given rejection region for the considered statistics, attributing the same value to those that are close to the boundary and those that are not. As a result, the local FDR has been recently proposed to quantify the specific probability for a given null hypothesis to be true. Results In this context we present a semi-parametric approach based on kernel estimators which is applied to different high-throughput biological data such as patterns in DNA sequences, genes expression and genome-wide association studies. Conclusion The proposed method has the practical advantages, over existing approaches, to consider complex heterogeneities in the alternative hypothesis, to take into account prior information (from an expert judgment or previous studies by allowing a semi-supervised mode, and to deal with truncated distributions such as those obtained in Monte-Carlo simulations. This method has been implemented and is available through the R package kerfdr via the CRAN or at http://stat.genopole.cnrs.fr/software/kerfdr.
Hwang, Beom Seuk; Pennell, Michael L
2014-03-30
Many dose-response studies collect data on correlated outcomes. For example, in developmental toxicity studies, uterine weight and presence of malformed pups are measured on the same dam. Joint modeling can result in more efficient inferences than independent models for each outcome. Most methods for joint modeling assume standard parametric response distributions. However, in toxicity studies, it is possible that response distributions vary in location and shape with dose, which may not be easily captured by standard models. To address this issue, we propose a semiparametric Bayesian joint model for a binary and continuous response. In our model, a kernel stick-breaking process prior is assigned to the distribution of a random effect shared across outcomes, which allows flexible changes in distribution shape with dose shared across outcomes. The model also includes outcome-specific fixed effects to allow different location effects. In simulation studies, we found that the proposed model provides accurate estimates of toxicological risk when the data do not satisfy assumptions of standard parametric models. We apply our method to data from a developmental toxicity study of ethylene glycol diethyl ether.
Semi-parametric Robust Event Detection for Massive Time-Domain Databases
Blocker, Alexander W
2013-01-01
The detection and analysis of events within massive collections of time-series has become an extremely important task for time-domain astronomy. In particular, many scientific investigations (e.g. the analysis of microlensing and other transients) begin with the detection of isolated events in irregularly-sampled series with both non-linear trends and non-Gaussian noise. We outline a semi-parametric, robust, parallel method for identifying variability and isolated events at multiple scales in the presence of the above complications. This approach harnesses the power of Bayesian modeling while maintaining much of the speed and scalability of more ad-hoc machine learning approaches. We also contrast this work with event detection methods from other fields, highlighting the unique challenges posed by astronomical surveys. Finally, we present results from the application of this method to 87.2 million EROS-2 sources, where we have obtained a greater than 100-fold reduction in candidates for certain types of pheno...
Wei, Jiawei; Carroll, Raymond J; Maity, Arnab
2011-07-01
We consider the problem of testing for a constant nonparametric effect in a general semi-parametric regression model when there is the potential for interaction between the parametrically and nonparametrically modeled variables. The work was originally motivated by a unique testing problem in genetic epidemiology (Chatterjee, et al., 2006) that involved a typical generalized linear model but with an additional term reminiscent of the Tukey one-degree-of-freedom formulation, and their interest was in testing for main effects of the genetic variables, while gaining statistical power by allowing for a possible interaction between genes and the environment. Later work (Maity, et al., 2009) involved the possibility of modeling the environmental variable nonparametrically, but they focused on whether there was a parametric main effect for the genetic variables. In this paper, we consider the complementary problem, where the interest is in testing for the main effect of the nonparametrically modeled environmental variable. We derive a generalized likelihood ratio test for this hypothesis, show how to implement it, and provide evidence that our method can improve statistical power when compared to standard partially linear models with main effects only. We use the method for the primary purpose of analyzing data from a case-control study of colorectal adenoma.
Kuppens, Toon; Yzerbyt, Vincent Y.
2014-01-01
In the literature on emotions in intergroup relations, it is not always clear how exactly emotions are group-related. Here, we distinguish between emotions that involve appraisals of immediate group concerns (i.e., group-based emotions) and emotions that do not. Recently, general group emotions, mea
Cleaners' experiences with group-based workplace physical training
DEFF Research Database (Denmark)
Kirkelund, Lasse; Mortensen, Ole Steen; Holtermann, Andreas
2012-01-01
This study investigates how work-site health promotion intervention, by involving group-based physical coordination training, may increase participants’ social awareness of new ways to use the body. Purpose: We investigated cleaners’ experiences with a one-year health promotion intervention...... involving group-based physical coordination training (PCT) during working hours. Design: We conducted a qualitative evaluation using method triangulation; continuous unfocused participant observation during the whole intervention, semi-structured focus group interview, and individual written evaluations one...... for implementation seem to be important for sustained effects of health-promotion interventions in the workplace. Originality: The social character of the physical training facilitated a community of practice, which potentially supported the learning of new competencies, and how to improve the organization...
Personality traits and group-based information behaviour
DEFF Research Database (Denmark)
Hyldegård, Jette
2009-01-01
Introduction. The relationship between hypothesised behaviour resulting from a personality test and actual information behaviour resulting from a group-based assignment process is addressed in this paper. Methods. Three voluntary groups of ten librarianship and information science students were...... but there were also deviations, which were found that seemed to be related to the group-work context. The importance of studying personality traits in context has further been confirmed....
An Event Grouping Based Algorithm for University Course Timetabling Problem
Kralev, Velin; Kraleva, Radoslava; Yurukov, Borislav
2016-01-01
This paper presents the study of an event grouping based algorithm for a university course timetabling problem. Several publications which discuss the problem and some approaches for its solution are analyzed. The grouping of events in groups with an equal number of events in each group is not applicable to all input data sets. For this reason, a universal approach to all possible groupings of events in commensurate in size groups is proposed here. Also, an implementation of an algorithm base...
Personality traits and group-based information behaviour
DEFF Research Database (Denmark)
Hyldegård, Jette
2009-01-01
Introduction. The relationship between hypothesised behaviour resulting from a personality test and actual information behaviour resulting from a group-based assignment process is addressed in this paper. Methods. Three voluntary groups of ten librarianship and information science students were....... Information behaviour associated with personality traits was identified, but the presence of personality effects tended to vary with the perceived presence of the social context. Conclusions. Some matches were identified between group members' personality traits and their actual information behaviour...
An Event Grouping Based Algorithm for University Course Timetabling Problem
Kralev, Velin; Kraleva, Radoslava; Yurukov, Borislav
2016-01-01
This paper presents the study of an event grouping based algorithm for a university course timetabling problem. Several publications which discuss the problem and some approaches for its solution are analyzed. The grouping of events in groups with an equal number of events in each group is not applicable to all input data sets. For this reason, a universal approach to all possible groupings of events in commensurate in size groups is proposed here. Also, an implementation of an algorithm base...
Kuppens, Toon; Yzerbyt, Vincent Y
2014-12-01
In the literature on emotions in intergroup relations, it is not always clear how exactly emotions are group-related. Here, we distinguish between emotions that involve appraisals of immediate group concerns (i.e., group-based emotions) and emotions that do not. Recently, general group emotions, measured by asking people how they feel "as a group member" but without specifying an object for these emotions, have been conceptualized as reflecting appraisals of group concerns. In contrast, we propose that general group emotions are best seen as emotions about belonging to a group. In two studies, general group emotions were closely related to emotions that are explicitly measured as belonging emotions. Two further studies showed that general group emotions were not related to appraisals of immediate group concerns, whereas group-based emotions were. We argue for more specificity regarding the group-level aspects of emotion that are tapped by emotion measures.
Analysis of two-phase sampling data with semiparametric additive hazards models.
Sun, Yanqing; Qian, Xiyuan; Shou, Qiong; Gilbert, Peter B
2017-07-01
Under the case-cohort design introduced by Prentice (Biometrica 73:1-11, 1986), the covariate histories are ascertained only for the subjects who experience the event of interest (i.e., the cases) during the follow-up period and for a relatively small random sample from the original cohort (i.e., the subcohort). The case-cohort design has been widely used in clinical and epidemiological studies to assess the effects of covariates on failure times. Most statistical methods developed for the case-cohort design use the proportional hazards model, and few methods allow for time-varying regression coefficients. In addition, most methods disregard data from subjects outside of the subcohort, which can result in inefficient inference. Addressing these issues, this paper proposes an estimation procedure for the semiparametric additive hazards model with case-cohort/two-phase sampling data, allowing the covariates of interest to be missing for cases as well as for non-cases. A more flexible form of the additive model is considered that allows the effects of some covariates to be time varying while specifying the effects of others to be constant. An augmented inverse probability weighted estimation procedure is proposed. The proposed method allows utilizing the auxiliary information that correlates with the phase-two covariates to improve efficiency. The asymptotic properties of the proposed estimators are established. An extensive simulation study shows that the augmented inverse probability weighted estimation is more efficient than the widely adopted inverse probability weighted complete-case estimation method. The method is applied to analyze data from a preventive HIV vaccine efficacy trial.
A Semi-parametric Multivariate Gap-filling Model for Eddy Covariance Latent Heat Flux
Li, M.; Chen, Y.
2010-12-01
Quantitative descriptions of latent heat fluxes are important to study the water and energy exchanges between terrestrial ecosystems and the atmosphere. The eddy covariance approaches have been recognized as the most reliable technique for measuring surface fluxes over time scales ranging from hours to years. However, unfavorable micrometeorological conditions, instrument failures, and applicable measurement limitations may cause inevitable flux gaps in time series data. Development and application of suitable gap-filling techniques are crucial to estimate long term fluxes. In this study, a semi-parametric multivariate gap-filling model was developed to fill latent heat flux gaps for eddy covariance measurements. Our approach combines the advantages of a multivariate statistical analysis (principal component analysis, PCA) and a nonlinear interpolation technique (K-nearest-neighbors, KNN). The PCA method was first used to resolve the multicollinearity relationships among various hydrometeorological factors, such as radiation, soil moisture deficit, LAI, and wind speed. The KNN method was then applied as a nonlinear interpolation tool to estimate the flux gaps as the weighted sum latent heat fluxes with the K-nearest distances in the PCs’ domain. Two years, 2008 and 2009, of eddy covariance and hydrometeorological data from a subtropical mixed evergreen forest (the Lien-Hua-Chih Site) were collected to calibrate and validate the proposed approach with artificial gaps after standard QC/QA procedures. The optimal K values and weighting factors were determined by the maximum likelihood test. The results of gap-filled latent heat fluxes conclude that developed model successful preserving energy balances of daily, monthly, and yearly time scales. Annual amounts of evapotranspiration from this study forest were 747 mm and 708 mm for 2008 and 2009, respectively. Nocturnal evapotranspiration was estimated with filled gaps and results are comparable with other studies
Li, Zhigang; Frost, H R; Tosteson, Tor D; Zhao, Lihui; Liu, Lei; Lyons, Kathleen; Chen, Huaihou; Cole, Bernard; Currow, David; Bakitas, Marie
2017-08-17
Palliative medicine is an interdisciplinary specialty focusing on improving quality of life (QOL) for patients with serious illness and their families. Palliative care programs are available or under development at over 80% of large US hospitals (300+ beds). Palliative care clinical trials present unique analytic challenges relative to evaluating the palliative care treatment efficacy which is to improve patients' diminishing QOL as disease progresses towards end of life (EOL). A unique feature of palliative care clinical trials is that patients will experience decreasing QOL during the trial despite potentially beneficial treatment. Often longitudinal QOL and survival data are highly correlated which, in the face of censoring, makes it challenging to properly analyze and interpret terminal QOL trend. To address these issues, we propose a novel semiparametric statistical approach to jointly model the terminal trend of QOL and survival data. There are two sub-models in our approach: a semiparametric mixed effects model for longitudinal QOL and a Cox model for survival. We use regression splines method to estimate the nonparametric curves and AIC to select knots. We assess the model performance through simulation to establish a novel modeling approach that could be used in future palliative care research trials. Application of our approach in a recently completed palliative care clinical trial is also presented. Copyright © 2017 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
Moliere Nguile-Makao
2015-12-01
Full Text Available The analysis of interaction effects involving genetic variants and environmental exposures on the risk of adverse obstetric and early-life outcomes is generally performed using standard logistic regression in the case-mother and control-mother design. However such an analysis is inefficient because it does not take into account the natural family-based constraints present in the parent-child relationship. Recently, a new approach based on semi-parametric maximum likelihood estimation was proposed. The advantage of this approach is that it takes into account the parental relationship between the mother and her child in estimation. But a package implementing this method has not been widely available. In this paper, we present SPmlficmcm, an R package implementing this new method and we propose an extension of the method to handle missing offspring genotype data by maximum likelihood estimation. Our choice to treat missing data of the offspring genotype was motivated by the fact that in genetic association studies where the genetic data of mother and child are available, there are usually more missing data on the genotype of the offspring than that of the mother. The package builds a non-linear system from the data and solves and computes the estimates from the gradient and the Hessian matrix of the log profile semi-parametric likelihood function. Finally, we analyze a simulated dataset to show the usefulness of the package.
Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad
2015-11-01
One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.
Finding human promoter groups based on DNA physical properties
Zeng, Jia; Cao, Xiao-Qin; Zhao, Hongya; Yan, Hong
2009-10-01
DNA rigidity is an important physical property originating from the DNA three-dimensional structure. Although the general DNA rigidity patterns in human promoters have been investigated, their distinct roles in transcription are largely unknown. In this paper, we discover four highly distinct human promoter groups based on similarity of their rigidity profiles. First, we find that all promoter groups conserve relatively rigid DNAs at the canonical TATA box [a consensus TATA(A/T)A(A/T) sequence] position, which are important physical signals in binding transcription factors. Second, we find that the genes activated by each group of promoters share significant biological functions based on their gene ontology annotations. Finally, we find that these human promoter groups correlate with the tissue-specific gene expression.
Finding human promoter groups based on DNA physical properties.
Zeng, Jia; Cao, Xiao-Qin; Zhao, Hongya; Yan, Hong
2009-10-01
DNA rigidity is an important physical property originating from the DNA three-dimensional structure. Although the general DNA rigidity patterns in human promoters have been investigated, their distinct roles in transcription are largely unknown. In this paper, we discover four highly distinct human promoter groups based on similarity of their rigidity profiles. First, we find that all promoter groups conserve relatively rigid DNAs at the canonical TATA box [a consensus TATA(A/T)A(A/T) sequence] position, which are important physical signals in binding transcription factors. Second, we find that the genes activated by each group of promoters share significant biological functions based on their gene ontology annotations. Finally, we find that these human promoter groups correlate with the tissue-specific gene expression.
Group-based sparse representation for image restoration.
Zhang, Jian; Zhao, Debin; Gao, Wen
2014-08-01
Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high computational complexity in dictionary learning. Second, each patch is considered independently in dictionary learning and sparse coding, which ignores the relationship among patches, resulting in inaccurate sparse coding coefficients. In this paper, instead of using patch as the basic unit of sparse representation, we exploit the concept of group as the basic unit of sparse representation, which is composed of nonlocal patches with similar structures, and establish a novel sparse representation modeling of natural images, called group-based sparse representation (GSR). The proposed GSR is able to sparsely represent natural images in the domain of group, which enforces the intrinsic local sparsity and nonlocal self-similarity of images simultaneously in a unified framework. In addition, an effective self-adaptive dictionary learning method for each group with low complexity is designed, rather than dictionary learning from natural images. To make GSR tractable and robust, a split Bregman-based technique is developed to solve the proposed GSR-driven ℓ0 minimization problem for image restoration efficiently. Extensive experiments on image inpainting, image deblurring and image compressive sensing recovery manifest that the proposed GSR modeling outperforms many current state-of-the-art schemes in both peak signal-to-noise ratio and visual perception.
Hardware Accelerators Targeting a Novel Group Based Packet Classification Algorithm
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O. Ahmed
2013-01-01
Full Text Available Packet classification is a ubiquitous and key building block for many critical network devices. However, it remains as one of the main bottlenecks faced when designing fast network devices. In this paper, we propose a novel Group Based Search packet classification Algorithm (GBSA that is scalable, fast, and efficient. GBSA consumes an average of 0.4 megabytes of memory for a 10 k rule set. The worst-case classification time per packet is 2 microseconds, and the preprocessing speed is 3 M rules/second based on an Xeon processor operating at 3.4 GHz. When compared with other state-of-the-art classification techniques, the results showed that GBSA outperforms the competition with respect to speed, memory usage, and processing time. Moreover, GBSA is amenable to implementation in hardware. Three different hardware implementations are also presented in this paper including an Application Specific Instruction Set Processor (ASIP implementation and two pure Register-Transfer Level (RTL implementations based on Impulse-C and Handel-C flows, respectively. Speedups achieved with these hardware accelerators ranged from 9x to 18x compared with a pure software implementation running on an Xeon processor.
Mixture Density Mercer Kernels
National Aeronautics and Space Administration — We present a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture...
Scharfstein, Daniel; McDermott, Aidan; Díaz, Iván; Carone, Marco; Lunardon, Nicola; Turkoz, Ibrahim
2017-05-23
In practice, both testable and untestable assumptions are generally required to draw inference about the mean outcome measured at the final scheduled visit in a repeated measures study with drop-out. Scharfstein et al. (2014) proposed a sensitivity analysis methodology to determine the robustness of conclusions within a class of untestable assumptions. In their approach, the untestable and testable assumptions were guaranteed to be compatible; their testable assumptions were based on a fully parametric model for the distribution of the observable data. While convenient, these parametric assumptions have proven especially restrictive in empirical research. Here, we relax their distributional assumptions and provide a more flexible, semi-parametric approach. We illustrate our proposal in the context of a randomized trial for evaluating a treatment of schizoaffective disorder. © 2017, The International Biometric Society.
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Zeb Aurangzeb
2014-09-01
Full Text Available This paper examines the relationship between Foreign Direct Investment (FDI and economic growth. We extend the dualistic growth framework by Feder (1982, whereby we divide the economy into an exports and a non-exports sector and assume that the FDI is mainly entering the former. In order to empirically estimate the effects of FDI on economic growth, we employ a smooth coefficient semi-parametric approach. Our results show that countries with higher levels of FDI inflows experience higher productivity in the exports sector as compared with those with low level of FDI inflows. In general, we provide some evidence that FDI inflows play an important role during the development process: Initially, as an important determinant of growth, later on, by helping improve factor productivity in the exports sector and finally, through spillover effects due to fostering the linkages between the Multinational Corporations (MNC and their host economy partners.
Pérez, Hector E; Kettner, Keith
2013-10-01
Time-to-event analysis represents a collection of relatively new, flexible, and robust statistical techniques for investigating the incidence and timing of transitions from one discrete condition to another. Plant biology is replete with examples of such transitions occurring from the cellular to population levels. However, application of these statistical methods has been rare in botanical research. Here, we demonstrate the use of non- and semi-parametric time-to-event and categorical data analyses to address questions regarding seed to seedling transitions of Ipomopsis rubra propagules exposed to various doses of constant or simulated seasonal diel temperatures. Seeds were capable of germinating rapidly to >90 % at 15-25 or 22/11-29/19 °C. Optimum temperatures for germination occurred at 25 or 29/19 °C. Germination was inhibited and seed viability decreased at temperatures ≥30 or 33/24 °C. Kaplan-Meier estimates of survivor functions indicated highly significant differences in temporal germination patterns for seeds exposed to fluctuating or constant temperatures. Extended Cox regression models specified an inverse relationship between temperature and the hazard of germination. Moreover, temperature and the temperature × day interaction had significant effects on germination response. Comparisons to reference temperatures and linear contrasts suggest that summer temperatures (33/24 °C) play a significant role in differential germination responses. Similarly, simple and complex comparisons revealed that the effects of elevated temperatures predominate in terms of components of seed viability. In summary, the application of non- and semi-parametric analyses provides appropriate, powerful data analysis procedures to address various topics in seed biology and more widespread use is encouraged.
Statistical Diagnosis and Gross Error Test for Semiparametric Linear Model%半参数模型统计诊断与粗差检验
Institute of Scientific and Technical Information of China (English)
丁士俊; 张松林; 姜卫平; 王守春
2009-01-01
This paper systematically studies the statistical diagnosis and hypothesis testing for the semiparametric linear re-gression model according to the theories and methods of the statistical diagnosis and hypothesis testing for parametric re-gression model.Several diagnostic measures and the methods for gross error testing are derived.Especially,the global and local influence analysis of the gross error on the parameter X and the nonparameter s are discussed in detail; at the same time,the paper proves that the data point deletion model is equivalent to the mean shift model for the semiparametric re-gression model.Finally,with one simulative computing example,some helpful conclusions are drawn.
Sinha, B K; Pal, Manisha; Das, P
2014-01-01
The book dwells mainly on the optimality aspects of mixture designs. As mixture models are a special case of regression models, a general discussion on regression designs has been presented, which includes topics like continuous designs, de la Garza phenomenon, Loewner order domination, Equivalence theorems for different optimality criteria and standard optimality results for single variable polynomial regression and multivariate linear and quadratic regression models. This is followed by a review of the available literature on estimation of parameters in mixture models. Based on recent research findings, the volume also introduces optimal mixture designs for estimation of optimum mixing proportions in different mixture models, which include Scheffé’s quadratic model, Darroch-Waller model, log- contrast model, mixture-amount models, random coefficient models and multi-response model. Robust mixture designs and mixture designs in blocks have been also reviewed. Moreover, some applications of mixture desig...
Low temperature asphalt mixtures
Modrijan, Damjan
2006-01-01
This thesis presents the problem of manufacturing and building in the asphalt mixtures produced by the classical hot procedure and the possibility of manufacturing low temperature asphalt mixtures.We will see the main advantages of low temperature asphalt mixtures prepared with bitumen with organic addition Sasobit and compare it to the classical asphalt mixtures. The advantages and disadvantages of that are valued in the practical example in the conclusion.
Shimaponda-Mataa, Nzooma M; Tembo-Mwase, Enala; Gebreslasie, Michael; Achia, Thomas N O; Mukaratirwa, Samson
2017-02-01
Although malaria morbidity and mortality are greatly reduced globally owing to great control efforts, the disease remains the main contributor. In Zambia, all provinces are malaria endemic. However, the transmission intensities vary mainly depending on environmental factors as they interact with the vectors. Generally in Africa, possibly due to the varying perspectives and methods used, there is variation on the relative importance of malaria risk determinants. In Zambia, the role climatic factors play on malaria case rates has not been determined in combination of space and time using robust methods in modelling. This is critical considering the reversal in malaria reduction after the year 2010 and the variation by transmission zones. Using a geoadditive or structured additive semiparametric Poisson regression model, we determined the influence of climatic factors on malaria incidence in four endemic provinces of Zambia. We demonstrate a strong positive association between malaria incidence and precipitation as well as minimum temperature. The risk of malaria was 95% lower in Lusaka (ARR=0.05, 95% CI=0.04-0.06) and 68% lower in the Western Province (ARR=0.31, 95% CI=0.25-0.41) compared to Luapula Province. North-western Province did not vary from Luapula Province. The effects of geographical region are clearly demonstrated by the unique behaviour and effects of minimum and maximum temperatures in the four provinces. Environmental factors such as landscape in urbanised places may also be playing a role.
Carroll, Raymond
2009-04-23
We consider the efficient estimation of a regression parameter in a partially linear additive nonparametric regression model from repeated measures data when the covariates are multivariate. To date, while there is some literature in the scalar covariate case, the problem has not been addressed in the multivariate additive model case. Ours represents a first contribution in this direction. As part of this work, we first describe the behavior of nonparametric estimators for additive models with repeated measures when the underlying model is not additive. These results are critical when one considers variants of the basic additive model. We apply them to the partially linear additive repeated-measures model, deriving an explicit consistent estimator of the parametric component; if the errors are in addition Gaussian, the estimator is semiparametric efficient. We also apply our basic methods to a unique testing problem that arises in genetic epidemiology; in combination with a projection argument we develop an efficient and easily computed testing scheme. Simulations and an empirical example from nutritional epidemiology illustrate our methods.
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Mutiah Salamah
2012-01-01
Full Text Available Dengue is one of the most dangerous diseases in the worlds. In particularly in East Java province Indonesia, dengue has been identified as one of the major causes of death. Hence, it is important to investigate the factors that induce the number of dengue incidences in this region. This study examines climate and socio-economic conditions, which are assumed to influence the number of dengue in the examined region. The semiparametric panel regression approach has been applied and the results are compared with the standard panel regression. In this case, the socio-economic condition is treated parametrically while climate effect is modeled nonparametrically. The analysis showed that the number of dengue incidences is significantly influenced by the income per-capita and the number of inhabitant below 15 years. Furthermore, the dengue incidence is optimum under rainfall of 1500 to 3670 mm, temperature of 22 to 27 degree and humidity of 82 to 87%. The elasticity allows us to identify the most responsive and most irresponsive district towards the changes of climate variable. The study shows that Surabaya is the most responsive district with respect to the change of climate variables.
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Resmi Gupta
2017-01-01
Full Text Available Aim. To examine the gestational glycemic profile and identify specific times during pregnancy that variability in glucose levels, measured by change in velocity and acceleration/deceleration of blood glucose fluctuations, is associated with delivery of a large-for-gestational-age (LGA baby, in women with type 1 diabetes. Methods. Retrospective analysis of capillary blood glucose levels measured multiple times daily throughout gestation in women with type 1 diabetes was performed using semiparametric mixed models. Results. Velocity and acceleration/deceleration in glucose levels varied across gestation regardless of delivery outcome. Compared to women delivering LGA babies, those delivering babies appropriate for gestational age exhibited significantly smaller rates of change and less variation in glucose levels between 180 days of gestation and birth. Conclusions. Use of innovative statistical methods enabled detection of gestational intervals in which blood glucose fluctuation parameters might influence the likelihood of delivering LGA baby in mothers with type 1 diabetes. Understanding dynamics and being able to visualize gestational changes in blood glucose are a potentially useful tool to assist care providers in determining the optimal timing to initiate continuous glucose monitoring.
Institute of Scientific and Technical Information of China (English)
Jinhong YOU; CHEN Min; Gemai CHEN
2004-01-01
Consider a semiparametric regression model with linear time series errors Yκ = x′κβ + g(tκ) + εκ,1 ≤ k ≤ n, where Yκ's are responses, xκ= (xκ1,xκ2,…,xκp)′and tκ ∈ T( ) R are fixed design points, β = (β1,β2,…… ,βp)′ is an unknown parameter vector, g(.) is an unknown bounded real-valued function defined on a compact subset T of the real line R, and εκ is a linear process given by εκ = ∑∞j=0 ψjeκ-j, ψ0 = 1, where ∑∞j=0 |ψj| ＜∞, and ej, j = 0,±1,±2,…, are I.I.d, random variables. In this paper we establish the asymptotic normality of the least squares estimator ofβ, a smooth estimator of g(·), and estimators of the autocovariance and autocorrelation functions of the linear process εκ.
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N.W. Surya Wardhani
2014-10-01
Full Text Available Modeling of food security based on the characteristics of the area will be affected by the geographical location which means that geographical location will affect the region’s potential. Therefore, we need a method of statistical modeling that takes into account the geographical location or the location factor observations. In this case, the research variables could be global means that the location affects the response variables significantly; when some of the predictor variables are global and the other variables are local, then Geographically Weighted Ordinal Logistic Regression Semiparametric (GWOLRS could be used to analyze the data. The data used is the resilience and food insecurity data in 2011 in East Java Province. The result showed that three predictor variables that influenced by the location are the percentage of poor (%, rice production per district (tons and life expectancy (%. Those three predictor variables are local because they have significant influence in some districts/cities but had no significant effect in other districts/cities, while other two variables that are clean water and good quality road length (km are assumed global because it is not a significant factor for the whole districts/towns in East Java .
Hubbard, Rebecca A; Miglioretti, Diana L
2013-03-01
False-positive test results are among the most common harms of screening tests and may lead to more invasive and expensive diagnostic testing procedures. Estimating the cumulative risk of a false-positive screening test result after repeat screening rounds is, therefore, important for evaluating potential screening regimens. Existing estimators of the cumulative false-positive risk are limited by strong assumptions about censoring mechanisms and parametric assumptions about variation in risk across screening rounds. To address these limitations, we propose a semiparametric censoring bias model for cumulative false-positive risk that allows for dependent censoring without specifying a fixed functional form for variation in risk across screening rounds. Simulation studies demonstrated that the censoring bias model performs similarly to existing models under independent censoring and can largely eliminate bias under dependent censoring. We used the existing and newly proposed models to estimate the cumulative false-positive risk and variation in risk as a function of baseline age and family history of breast cancer after 10 years of annual screening mammography using data from the Breast Cancer Surveillance Consortium. Ignoring potential dependent censoring in this context leads to underestimation of the cumulative risk of false-positive results. Models that provide accurate estimates under dependent censoring are critical for providing appropriate information for evaluating screening tests.
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Damgaard Lars
2006-04-01
Full Text Available Abstract Data on doe longevity in a rabbit population were analysed using a semiparametric log-Normal animal frailty model. Longevity was defined as the time from the first positive pregnancy test to death or culling due to pathological problems. Does culled for other reasons had right censored records of longevity. The model included time dependent covariates associated with year by season, the interaction between physiological state and the number of young born alive, and between order of positive pregnancy test and physiological state. The model also included an additive genetic effect and a residual in log frailty. Properties of marginal posterior distributions of specific parameters were inferred from a full Bayesian analysis using Gibbs sampling. All of the fully conditional posterior distributions defining a Gibbs sampler were easy to sample from, either directly or using adaptive rejection sampling. The marginal posterior mean estimates of the additive genetic variance and of the residual variance in log frailty were 0.247 and 0.690.
Sánchez, Juan Pablo; Korsgaard, Inge Riis; Damgaard, Lars Holm; Baselga, Manuel
2006-01-01
Data on doe longevity in a rabbit population were analysed using a semiparametric log-Normal animal frailty model. Longevity was defined as the time from the first positive pregnancy test to death or culling due to pathological problems. Does culled for other reasons had right censored records of longevity. The model included time dependent covariates associated with year by season, the interaction between physiological state and the number of young born alive, and between order of positive pregnancy test and physiological state. The model also included an additive genetic effect and a residual in log frailty. Properties of marginal posterior distributions of specific parameters were inferred from a full Bayesian analysis using Gibbs sampling. All of the fully conditional posterior distributions defining a Gibbs sampler were easy to sample from, either directly or using adaptive rejection sampling. The marginal posterior mean estimates of the additive genetic variance and of the residual variance in log frailty were 0.247 and 0.690.
Octavianty, Toharudin, Toni; Jaya, I. G. N. Mindra
2017-03-01
Tuberculosis (TB) is a disease caused by a bacterium, called Mycobacterium tuberculosis, which typically attacks the lungs but can also affect the kidney, spine, and brain (Centers for Disease Control and Prevention). Indonesia had the largest number of TB cases after India (Global Tuberculosis Report 2015 by WHO). The distribution of Mycobacterium tuberculosis genotypes in Indonesia showed the high genetic diversity and tended to vary by geographic regions. For instance, in Bandung city, the prevalence rate of TB morbidity is quite high. A number of TB patients belong to the counted data. To determine the factors that significantly influence the number of tuberculosis patients in each location of the observations can be used statistical analysis tool that is Geographically Weighted Poisson Regression Semiparametric (GWPRS). GWPRS is an extension of the Poisson regression and GWPR that is influenced by geographical factors, and there is also variables that influence globally and locally. Using the TB Data in Bandung city (in 2015), the results show that the global and local variables that influence the number of tuberculosis patients in every sub-district.
Rowlinson, J S; Baldwin, J E; Buckingham, A D; Danishefsky, S
2013-01-01
Liquids and Liquid Mixtures, Third Edition explores the equilibrium properties of liquids and liquid mixtures and relates them to the properties of the constituent molecules using the methods of statistical thermodynamics. Topics covered include the critical state, fluid mixtures at high pressures, and the statistical thermodynamics of fluids and mixtures. This book consists of eight chapters and begins with an overview of the liquid state and the thermodynamic properties of liquids and liquid mixtures, including vapor pressure and heat capacities. The discussion then turns to the thermodynami
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Hannah H Leslie
Full Text Available OBJECTIVE: To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. BACKGROUND: Human immunodeficiency virus (HIV-positive women are at increased risk for cervical cancer and its treatable precursors. Determining whether potential risk factors such as hormonal contraception are true causes is critical for informing public health strategies as longevity increases among HIV-positive women in developing countries. METHODS: We developed a causal model of the factors related to combined oral contraceptive (COC use and cervical intraepithelial neoplasia 2 or greater (CIN2+ and modified the model to fit the observed data, drawn from women in a cervical cancer screening program at HIV clinics in Kenya. Assumptions required for substantiation of a causal relationship were assessed. We estimated the population-level association using semi-parametric methods: g-computation, inverse probability of treatment weighting, and targeted maximum likelihood estimation. RESULTS: We identified 2 plausible causal paths from COC use to CIN2+: via HPV infection and via increased disease progression. Study data enabled estimation of the latter only with strong assumptions of no unmeasured confounding. Of 2,519 women under 50 screened per protocol, 219 (8.7% were diagnosed with CIN2+. Marginal modeling suggested a 2.9% (95% confidence interval 0.1%, 6.9% increase in prevalence of CIN2+ if all women under 50 were exposed to COC; the significance of this association was sensitive to method of estimation and exposure misclassification. CONCLUSION: Use of causal modeling enabled clear representation of the causal relationship of interest and the assumptions required to estimate that relationship from the observed data. Semi-parametric estimation methods provided flexibility and reduced reliance on correct model form. Although selected results suggest an
DEFF Research Database (Denmark)
Koushede, Vibeke; Brixval, Carina Sjöberg; Axelsen, Solveig Forberg
2013-01-01
To examine the efficacy and cost-effectiveness of group based antenatal education for improving childbirth and parenting resources compared to auditorium based education.......To examine the efficacy and cost-effectiveness of group based antenatal education for improving childbirth and parenting resources compared to auditorium based education....
Figueiredo, A.; Doosje, B.; Pires Valentim, J.
2015-01-01
Group-based emotions can be experienced by group members for the past misdeeds of their ingroup towards an outgroup.. The present study examines distinct antecedents and consequences of group-based compunction and anger in two countries with a history of colonization (Portugal, N = 280 and the Nethe
Cruz-Marcelo, Alejandro; Ensor, Katherine B.; Rosner, Gary L.
2011-01-01
The term structure of interest rates is used to price defaultable bonds and credit derivatives, as well as to infer the quality of bonds for risk management purposes. We introduce a model that jointly estimates term structures by means of a Bayesian hierarchical model with a prior probability model based on Dirichlet process mixtures. The modeling methodology borrows strength across term structures for purposes of estimation. The main advantage of our framework is its ability to produce reliable estimators at the company level even when there are only a few bonds per company. After describing the proposed model, we discuss an empirical application in which the term structure of 197 individual companies is estimated. The sample of 197 consists of 143 companies with only one or two bonds. In-sample and out-of-sample tests are used to quantify the improvement in accuracy that results from approximating the term structure of corporate bonds with estimators by company rather than by credit rating, the latter being a popular choice in the financial literature. A complete description of a Markov chain Monte Carlo (MCMC) scheme for the proposed model is available as Supplementary Material. PMID:21765566
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Ana Figueiredo
2016-04-01
Full Text Available Group-based emotions can be experienced by group members for the past misdeeds of their ingroup towards an outgroup.. The present study examines distinct antecedents and consequences of group-based compunction and anger in two countries with a history of colonization (Portugal, N = 280 and the Netherlands, N = 184. While previous research has focused mainly on ingroup-focused antecedents of group-based emotions, such as ingroup identification and perceptions of responsibility, our research also analyzed outgroup-focused variables, such as outgroup identification and meta-perceptions. Multiple group structural equation modeling showed that group-based compunction and group-based anger have similar antecedents (exonerating cognitions, collectivism, outgroup identification and meta-perceptions. Furthermore, the results showed that the two emotions have distinct but related consequences for the improvement of intergroup relations (compensation, subjective importance of discussing the past and forgiveness assignment.
Together we cry: Social motives and preferences for group-based sadness.
Porat, Roni; Halperin, Eran; Mannheim, Ittay; Tamir, Maya
2016-01-01
Group-based emotions play an important role in helping people feel that they belong to their group. People are motivated to belong, but does this mean that they actively try to experience group-based emotions to increase their sense of belonging? In this investigation, we propose that people may be motivated to experience even group-based emotions that are typically considered unpleasant to satisfy their need to belong. To test this hypothesis, we examined people's preferences for group-based sadness in the context of the Israeli National Memorial Day. In two correlational (Studies 1a and 1b) and two experimental (Studies 2 and 3) studies, we demonstrate that people with a stronger need to belong have a stronger preference to experience group-based sadness. This effect was mediated by the expectation that experiencing sadness would be socially beneficial (Studies 1 and 2). We discuss the implications of our findings for understanding motivated emotion regulation and intergroup relations.
Perception of trigeminal mixtures.
Filiou, Renée-Pier; Lepore, Franco; Bryant, Bruce; Lundström, Johan N; Frasnelli, Johannes
2015-01-01
The trigeminal system is a chemical sense allowing for the perception of chemosensory information in our environment. However, contrary to smell and taste, we lack a thorough understanding of the trigeminal processing of mixtures. We, therefore, investigated trigeminal perception using mixtures of 3 relatively receptor-specific agonists together with one control odor in different proportions to determine basic perceptual dimensions of trigeminal perception. We found that 4 main dimensions were linked to trigeminal perception: sensations of intensity, warmth, coldness, and pain. We subsequently investigated perception of binary mixtures of trigeminal stimuli by means of these 4 perceptual dimensions using different concentrations of a cooling stimulus (eucalyptol) mixed with a stimulus that evokes warmth perception (cinnamaldehyde). To determine if sensory interactions are mainly of central or peripheral origin, we presented stimuli in a physical "mixture" or as a "combination" presented separately to individual nostrils. Results showed that mixtures generally yielded higher ratings than combinations on the trigeminal dimensions "intensity," "warm," and "painful," whereas combinations yielded higher ratings than mixtures on the trigeminal dimension "cold." These results suggest dimension-specific interactions in the perception of trigeminal mixtures, which may be explained by particular interactions that may take place on peripheral or central levels.
Energy Technology Data Exchange (ETDEWEB)
Khayrullin, S.R.; Firsov, I.A.; Ongoyev, V.M.; Shekhtman, E.N.; Taskarin, B.T.
1983-01-01
A plugging mixture is proposed which contains triethanolamine, caustic soda, water and an additive. It is distinguished by the fact that in order to reduce the cost of the mixture while preserving its operational qualities, it additionally contains clay powder and as the additive, ground limestone with the following component ratio in percent by mass: ground limestone, 50 to 60; triethanolamine, 0.1 to 0.15; caustic soda, 2 to 3; clay powder, 8 to 10 and water the remainder. The mixture is distinguished by the fact that the ground limestone has a specific surface of 2,000 to 3,000 square centimeters per gram.
Kirschner, Femke; Paas, Fred; Kirschner, Paul A.
2009-01-01
Kirschner, F., Paas, F., & Kirschner, P. (2009). Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency. Computers in Human Behavior, 25, 306-314.
Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation ...
U.S. Environmental Protection Agency — Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression...
Dziak, John J.; Li, Runze; Tan, Xianming; Shiffman, Saul; Shiyko, Mariya P.
2015-01-01
Behavioral scientists increasingly collect intensive longitudinal data (ILD), in which phenomena are measured at high frequency and in real time. In many such studies, it is of interest to describe the pattern of change over time in important variables as well as the changing nature of the relationship between variables. Individuals' trajectories on variables of interest may be far from linear, and the predictive relationship between variables of interest and related covariates may also change over time in a nonlinear way. Time-varying effect models (TVEMs; see Tan, Shiyko, Li, Li, & Dierker, 2012) address these needs by allowing regression coefficients to be smooth, nonlinear functions of time rather than constants. However, it is possible that not only observed covariates but also unknown, latent variables may be related to the outcome. That is, regression coefficients may change over time and also vary for different kinds of individuals. Therefore, we describe a finite mixture version of TVEM for situations in which the population is heterogeneous and in which a single trajectory would conceal important, inter-individual differences. This extended approach, MixTVEM, combines finite mixture modeling with non- or semi-parametric regression modeling, in order to describe a complex pattern of change over time for distinct latent classes of individuals. The usefulness of the method is demonstrated in an empirical example from a smoking cessation study. We provide a versatile SAS macro and R function for fitting MixTVEMs. PMID:26390169
Cure fraction estimation from the mixture cure models for grouped survival data.
Yu, Binbing; Tiwari, Ram C; Cronin, Kathleen A; Feuer, Eric J
2004-06-15
Mixture cure models are usually used to model failure time data with long-term survivors. These models have been applied to grouped survival data. The models provide simultaneous estimates of the proportion of the patients cured from disease and the distribution of the survival times for uncured patients (latency distribution). However, a crucial issue with mixture cure models is the identifiability of the cure fraction and parameters of kernel distribution. Cure fraction estimates can be quite sensitive to the choice of latency distributions and length of follow-up time. In this paper, sensitivity of parameter estimates under semi-parametric model and several most commonly used parametric models, namely lognormal, loglogistic, Weibull and generalized Gamma distributions, is explored. The cure fraction estimates from the model with generalized Gamma distribution is found to be quite robust. A simulation study was carried out to examine the effect of follow-up time and latency distribution specification on cure fraction estimation. The cure models with generalized Gamma latency distribution are applied to the population-based survival data for several cancer sites from the Surveillance, Epidemiology and End Results (SEER) Program. Several cautions on the general use of cure model are advised.
Multilevel Mixture Kalman Filter
Directory of Open Access Journals (Sweden)
Xiaodong Wang
2004-11-01
Full Text Available The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS and integrates out the linear and Gaussian state variables conditioned on these indicators. Due to the marginalization process, the complexity of the mixture Kalman filter is quite high if the dimension of the indicator sampling space is high. In this paper, we address this difficulty by developing a new Monte Carlo sampling scheme, namely, the multilevel mixture Kalman filter. The basic idea is to make use of the multilevel or hierarchical structure of the space from which the indicator variables take values. That is, we draw samples in a multilevel fashion, beginning with sampling from the highest-level sampling space and then draw samples from the associate subspace of the newly drawn samples in a lower-level sampling space, until reaching the desired sampling space. Such a multilevel sampling scheme can be used in conjunction with the delayed estimation method, such as the delayed-sample method, resulting in delayed multilevel mixture Kalman filter. Examples in wireless communication, specifically the coherent and noncoherent 16-QAM over flat-fading channels, are provided to demonstrate the performance of the proposed multilevel mixture Kalman filter.
A tensorial approach to the inversion of group-based phylogenetic models.
Sumner, Jeremy G; Jarvis, Peter D; Holland, Barbara R
2014-12-04
Hadamard conjugation is part of the standard mathematical armoury in the analysis of molecular phylogenetic methods. For group-based models, the approach provides a one-to-one correspondence between the so-called "edge length" and "sequence" spectrum on a phylogenetic tree. The Hadamard conjugation has been used in diverse phylogenetic applications not only for inference but also as an important conceptual tool for thinking about molecular data leading to generalizations beyond strictly tree-like evolutionary modelling. For general group-based models of phylogenetic branching processes, we reformulate the problem of constructing a one-one correspondence between pattern probabilities and edge parameters. This takes a classic result previously shown through use of Fourier analysis and presents it in the language of tensors and group representation theory. This derivation makes it clear why the inversion is possible, because, under their usual definition, group-based models are defined for abelian groups only. We provide an inversion of group-based phylogenetic models that can implemented using matrix multiplication between rectangular matrices indexed by ordered-partitions of varying sizes. Our approach provides additional context for the construction of phylogenetic probability distributions on network structures, and highlights the potential limitations of restricting to group-based models in this setting.
Evaluating user reputation in online rating systems via an iterative group-based ranking method
Gao, Jian
2015-01-01
Reputation is a valuable asset in online social lives and it has drawn increased attention. How to evaluate user reputation in online rating systems is especially significant due to the existence of spamming attacks. To address this issue, so far, a variety of methods have been proposed, including network-based methods, quality-based methods and group-based ranking method. In this paper, we propose an iterative group-based ranking (IGR) method by introducing an iterative reputation-allocation process into the original group-based ranking (GR) method. More specifically, users with higher reputation have higher weights in dominating the corresponding group sizes. The reputation of users and the corresponding group sizes are iteratively updated until they become stable. Results on two real data sets suggest that the proposed IGR method has better performance and its robustness is considerably improved comparing with the original GR method. Our work highlights the positive role of users' grouping behavior towards...
Mixtures Estimation and Applications
Mengersen, Kerrie; Titterington, Mike
2011-01-01
This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject
Groten, J.P.
2000-01-01
Drinking water can be considered as a complex mixture that consists of tens, hundreds or thousands of chemicals of which the composition is qualitatively and quantitatively not fully known. From a public health point of view it is most relevant to answer the question of whether chemicals in drinking
Information Activities and Appropriation in Teacher Trainees' Digital, Group-Based Learning
Hanell, Fredrik
2016-01-01
Introduction: This paper reports results from an ethnographic study of teacher trainees' information activities in digital, group-based learning and their relation to the interplay between use and appropriation of digital tools and the learning environment. Method: The participants in the present study are 249 pre-school teacher trainees in…
Student Perceptions of Group-Based Competitive Exercises in the Chemistry Classroom
Cannon, Kevin C.; Mody, Tina; Breen, Maureen P.
2008-01-01
A non-traditional teaching method that can operate as a vehicle for engaging students is group-based competitive exercises. These exercises combine cooperative learning with a competitive environment and may be employed to promote subject- and problem-based learning. Survey responses of college-level organic chemistry and biochemistry students…
Web Environments for Group-Based Project Work in Higher Education
Diepen, van Nico; Collis, Betty; Andernach, Toine
1997-01-01
We discuss problems confronting the use of group-based project work as an instructional strategy in higher education and describe two courses in which course-specific World Wide Web (Web) environments have evolved over a series of course sequences and are used both as tool environments for group-pro
Personality Traits and Group-Based Information Behaviour: An Exploratory Study
Hyldegard, Jette
2009-01-01
Introduction: The relationship between hypothesised behaviour resulting from a personality test and actual information behaviour resulting from a group-based assignment process is addressed in this paper. Methods: Three voluntary groups of ten librarianship and information science students were followed during a project assignment. The long…
Effectiveness of a Group-Based Program for Parents of Children with Dyslexia
Multhauf, Bettina; Buschmann, Anke; Soellner, Renate
2016-01-01
Parents of children with dyslexia experience more parenting stress and depressive symptoms than other parents. The purpose of this study was to evaluate the effects of a cognitive-behavioral group-based program for parents of dyslexic children on parenting stress levels, parent-child homework interactions and parental competencies. 39 children…
Goldenberg, Amit; Halperin, Eran; van Zomeren, Martijn; Gross, James J.
2016-01-01
Scholars interested in emotion regulation have documented the different goals and strategies individuals have for regulating their emotions. However, little attention has been paid to the regulation of group-based emotions, which are based on individuals' self-categorization as a group member and oc
Arnold, I.J.M.; Walker, R.
2004-01-01
This paper explores the contribution of virtual tools to student learning within full-time management programmes. More specifically, the paper focuses on asynchronous communication tools, considering the scope they offer for group-based collaborative learning outside the classroom. We report on the
Evaluation of a group-based social skills training for children with problem behavior
van Vugt, E.S.; Deković, M.; Prinzie, P.; Stams, G.J.J.M.; Asscher, J.J.
2012-01-01
This study evaluated a group-based training program in social skills targeting reduction of problem behaviors in N = 161 children between 7 and 13 years of age. The effects of the intervention were tested in a quasi-experimental study, with a follow-up assessment 12 months after an optional
Goldenberg, Amit; Halperin, Eran; van Zomeren, Martijn; Gross, James J.
2016-01-01
Scholars interested in emotion regulation have documented the different goals and strategies individuals have for regulating their emotions. However, little attention has been paid to the regulation of group-based emotions, which are based on individuals' self-categorization as a group member and oc
Arnold, I.J.M.; Walker, R.
2004-01-01
This paper explores the contribution of virtual tools to student learning within full-time management programmes. More specifically, the paper focuses on asynchronous communication tools, considering the scope they offer for group-based collaborative learning outside the classroom. We report on the
When talking makes you feel like a group: The emergence of group-based emotions.
Yzerbyt, Vincent; Kuppens, Toon; Mathieu, Bernard
2016-01-01
Group-based emotions are emotional reactions to group concerns and have been shown to emerge when people appraise events while endorsing a specific social identity. Here we investigate whether discussing a group-relevant event with other group members affects emotional reactions in a similar way. In two experiments, we confronted participants with an unfair group-relevant event, while manipulating their social identity and whether they discussed the event or an unrelated topic. Our major finding is that having group members discuss the unfair group-relevant event led to emotions that were more negative than in the irrelevant discussion and comparable to those observed when social identity had been made salient explicitly beforehand. Moreover, it also generated group-based appraisals of injustice (Experiment 1) and group-based identity (Experiment 2). This research sheds new light not only on the consequences of within-group sharing of emotions for the unfolding of intergroup relations but also on the nature of group-based emotions.
Effectiveness of a Group-Based Program for Parents of Children with Dyslexia
Multhauf, Bettina; Buschmann, Anke; Soellner, Renate
2016-01-01
Parents of children with dyslexia experience more parenting stress and depressive symptoms than other parents. The purpose of this study was to evaluate the effects of a cognitive-behavioral group-based program for parents of dyslexic children on parenting stress levels, parent-child homework interactions and parental competencies. 39 children…
Goldenberg, Amit; Halperin, Eran; van Zomeren, Martijn; Gross, James J
2016-05-01
Scholars interested in emotion regulation have documented the different goals and strategies individuals have for regulating their emotions. However, little attention has been paid to the regulation of group-based emotions, which are based on individuals' self-categorization as a group member and occur in response to situations perceived as relevant for that group. We propose a model for examining group-based emotion regulation that integrates intergroup emotions theory and the process model of emotion regulation. This synergy expands intergroup emotion theory by facilitating further investigation of different goals (i.e., hedonic or instrumental) and strategies (e.g., situation selection and modification strategies) used to regulate group-based emotions. It also expands emotion regulation research by emphasizing the role of self-categorization (e.g., as an individual or a group member) in the emotional process. Finally, we discuss the promise of this theoretical synergy and suggest several directions for future research on group-based emotion regulation. © 2015 by the Society for Personality and Social Psychology, Inc.
Karataş, Zeynep; Gökçakan, Dan Zafer
2009-01-01
This study aimed to examine the effect of group-based psychodrama therapy on the level aggression in adolescents. The study included 23 students from Nezihe Yalvac Anatolian Vocational High School of Hotel Management and Tourism that had high aggression scores. Eleven of the participants (6 female, 5 male) constituted the experimental group and 12 (6 male, 6 female) were in the control group. The 34-item Aggression Scale was used to measure level of aggression. We utilized mixed pattern design including experiment-control, pre-test and post test and follow up. The experimental group participated in group-based psychodrama therapy once a week for 90 minutes, for 14 weeks in total. The Aggression Scale was administered to the experimental and control groups before and after treatment; it was additionally administered to the experimental group 16 weeks after treatment. Data were analyzed using ANCOVA and dependent samples t tests. Our analysis shows that group-based psychodrama had an effect on the experimental group in terms of total aggression, anger, hostility, and indirect aggression scores (F=65.109, F=20.175, F=18.593, F=40.987, respectively, P<.001). There was no effect of the group-based treatment on verbal or physical aggression scores. Follow-up indicated that the effect of the therapy was still measureable 16 weeks after the cessation of the therapy. Results of the present study indicate that group-based psychodrama therapy decreased the level of aggression in the experimental group. Current findings are discussed with reference to the literature. Recommendations for further research and for psychiatric counselors are provided.
Pointer Sentinel Mixture Models
Merity, Stephen; Xiong, Caiming; Bradbury, James; Socher, Richard
2016-01-01
Recent neural network sequence models with softmax classifiers have achieved their best language modeling performance only with very large hidden states and large vocabularies. Even then they struggle to predict rare or unseen words even if the context makes the prediction unambiguous. We introduce the pointer sentinel mixture architecture for neural sequence models which has the ability to either reproduce a word from the recent context or produce a word from a standard softmax classifier. O...
Uncertainty dimensions of information behaviour in a group based problem solving context
DEFF Research Database (Denmark)
Hyldegård, Jette
2009-01-01
This paper presents a study of uncertainty dimensions of information behaviour in a group based problem solving context. After a presentation of the cognitive uncertainty dimension underlying Kuhlthau's ISP-model, uncertainty factors associated with personality, the work task situation and social......-dimensional phenomenon, which should not be studied out of context. On the other hand, this complexity of the uncertainty concept also represents a methodological and practical challenge to the researcher as well as the practioner....
A Multistage Control Mechanism for Group-Based Machine-Type Communications in an LTE System
Directory of Open Access Journals (Sweden)
Wen-Chien Hung
2013-01-01
Full Text Available When machine-type communication (MTC devices perform the long-term evolution (LTE attach procedure without bit rate limitations, they may produce congestion in the core network. To prevent this congestion, the LTE standard suggests using group-based policing to regulate the maximum bit rate of all traffic generated by a group of MTC devices. However, previous studies on the access point name-aggregate maximum bit rate based on group-based policing are relatively limited. This study proposes a multistage control (MSC mechanism to process the operations of maximum bit rate allocation based on resource-use information. For performance evaluation, this study uses a Markov chain with to analyze MTC application in a 3GPP network. Traffic flow simulations in an LTE system indicate that the MSC mechanism is an effective bandwidth allocation method in an LTE system with MTC devices. Experimental results show that the MSC mechanism achieves a throughput 22.5% higher than that of the LTE standard model using the group-based policing, and it achieves a lower delay time and greater long-term fairness as well.
IMPACTS OF GROUP-BASED SIGNAL CONTROL POLICY ON DRIVER BEHAVIOR AND INTERSECTION SAFETY
Directory of Open Access Journals (Sweden)
Keshuang TANG
2008-01-01
Full Text Available Unlike the typical stage-based policy commonly applied in Japan, the group-based control (often called movement-based in the traffic control industry in Japan refers to such a control pattern that the controller is capable of separately allocating time to each signal group instead of stage based on traffic demand. In order to investigate its applicability at signalized intersections in Japan, an intersection located in Yokkaichi City of Mie Prefecture was selected as an experimental application site by the Japan Universal Traffic Management Society (UTMS. Based on the data collected at the intersection before and after implementing the group-based control policy respectively, this study evaluated the impacts of such a policy on driver behavior and intersection safety. To specify those impacts, a few models utilizing cycle-based data were first developed to interpret the occurrence probability and rate of red-light-running (RLR. Furthermore, analyses were performed on the yellow-entry time (Ye of the last cleared vehicle and post encroachment time (PET during the phase switching. Conclusions supported that the group-based control policy, along with certain other factors, directly or indirectly influenced the RLR behavior of through and right-turn traffics. Meanwhile, it has potential safety benefits as well, indicated by the declined Ye and increased PET values.
Essays on Finite Mixture Models
A. van Dijk (Bram)
2009-01-01
textabstractFinite mixture distributions are a weighted average of a ¯nite number of distributions. The latter are usually called the mixture components. The weights are usually described by a multinomial distribution and are sometimes called mixing proportions. The mixture components may be the
Essays on Finite Mixture Models
A. van Dijk (Bram)
2009-01-01
textabstractFinite mixture distributions are a weighted average of a ¯nite number of distributions. The latter are usually called the mixture components. The weights are usually described by a multinomial distribution and are sometimes called mixing proportions. The mixture components may be the sam
Mixtures of truncated basis functions
DEFF Research Database (Denmark)
Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2012-01-01
In this paper we propose a framework, called mixtures of truncated basis functions (MoTBFs), for representing general hybrid Bayesian networks. The proposed framework generalizes both the mixture of truncated exponentials (MTEs) framework and the mixture of polynomials (MoPs) framework. Similar...
Separating Underdetermined Convolutive Speech Mixtures
DEFF Research Database (Denmark)
Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan
2006-01-01
a method for underdetermined blind source separation of convolutive mixtures. The proposed framework is applicable for separation of instantaneous as well as convolutive speech mixtures. It is possible to iteratively extract each speech signal from the mixture by combining blind source separation...
Toxicological evaluation of chemical mixtures
Feron, V.J.; Groten, J.P.
2002-01-01
This paper addresses major developments in the safety evaluation of chemical mixtures during the past 15 years, reviews today's state of the art of mixture toxicology, and discusses challenges ahead. Well-thought-out tailor-made mechanistic and empirical designs for studying the toxicity of mixtures
Semi-parametric forecasting model for USD/CNY exchange rate%人民币汇率的半参数预测模型
Institute of Scientific and Technical Information of China (English)
蔡宗武; 陈琳娜; 方颖
2012-01-01
利用从2006年1月4日到2008年7月18日人民币对美元汇率中间价的日均数据,同时运用非参数函数系数模型和GARCH模型来分析人民币对美元汇率收益率与波动率的非线性时间序列特征.实证结果表明,半参数组合模型具有较好的拟合以及预测效果,而且汇率管制政策变动的虚拟变量的估计系数显著不为0.跨度为50天的样本外预测显示:96％的收益率真实值都落在2.5％以及97.5％的非参数分位数回归预测线区间之内；参数GARCH(1,1)模型拟合的波动率所显示出的汇率震荡与实际情况一致.%Using the daily USD/CNY exchange rate time series data from January 4th, 2006 to July 18th, 2008, this paper proposes a semi-parametric approach to model the conditional mean and conditional volatility simultaneously. A nonparametric functional-coefficient model is employed to estimate the conditional mean, and a GARCH-type model with a policy change dummy is adopted to describe the dynamics of the conditional volatility. Moreover, the corresponding policies play a significant role on both mean and volatility. Finally, a nonparametric quantile regression estimation is applied to compute prediction intervals. The empirical results demonstrate that the proposed semi-parametric model has good performance in terms of in-sample goodness of fit and out-of-sample forecasts.
Mixture Based Outlier Filtration
Directory of Open Access Journals (Sweden)
P. Pecherková
2006-01-01
Full Text Available Success/failure of adaptive control algorithms – especially those designed using the Linear Quadratic Gaussian criterion – depends on the quality of the process data used for model identification. One of the most harmful types of process data corruptions are outliers, i.e. ‘wrong data’ lying far away from the range of real data. The presence of outliers in the data negatively affects an estimation of the dynamics of the system. This effect is magnified when the outliers are grouped into blocks. In this paper, we propose an algorithm for outlier detection and removal. It is based on modelling the corrupted data by a two-component probabilistic mixture. The first component of the mixture models uncorrupted process data, while the second models outliers. When the outlier component is detected to be active, a prediction from the uncorrupted data component is computed and used as a reconstruction of the observed data. The resulting reconstruction filter is compared to standard methods on simulated and real data. The filter exhibits excellent properties, especially in the case of blocks of outliers.
Lopes, S; Costa, S; Mesquita, C; Duarte, J
2016-01-01
Ankylosing Spondylitis (AS) is a chronic inflammatory rheumatic disease characterized by inflammation of the joints of the spine and sacroiliac and to a lesser percentage of the peripheral joints. It is a debilitating condition which reduces quality of life in patients with AS. The practice of physical therapy is recommended as non-pharmacological treatment as well as the treatment and prevention of associated deformities. To collect and summarize the available evidence in scientific databases to realize the effectiveness of home based and group based programs in patients with AS. Systematic review, where articles for the study were collected from scientific database PubMed. We have found 65 articles with publication date between January 1, 2004 and January 31, 2014. Inclusion and exclusion criteria were established to make the selection of articles to include in the study. All investigators provided their agreement in presencial meeting for a final selection, and at a later stage, the articles were read in full by the three investigators. The present systematic review includes eight randomized controlled trials. All articles show functional benefits in patients with AS subject to exercise programs in group based and / or home based. From the eight articles, 4 addressed programs conducted in home based context and 4 addressed in group based context programs. There appears to be evidence that the programs carried out based on group are more effective than those home based conducted in patients with AS. It was concluded also be advantageous to carry out home based exercise programs than the absence of any exercise program..
Directory of Open Access Journals (Sweden)
Sofia Lopes
2016-04-01
Full Text Available Introduction: Ankylosing Spondylitis (AS is a chronic inflammatory rheumatic disease characterized by inflammation of the joints of the spine and sacroiliac and to a lesser percentage of the peripheral joints. It is a debilitating condition which reduces quality of life in patients with AS. The practice of physical therapy is recommended as non-pharmacological treatment as well as the treatment and prevention of associated deformities. Objective: To collect and summarize the available evidence in scientific databases to realize the effectiveness of home based and group based programs in patients with AS. Methods: Systematic review, where articles for the study were collected from scientific database PubMed. We have found 65 articles with publication date between January 1, 2004 and January 31, 2014. Inclusion and exclusion criteria were established to make the selection of articles to include in the study. All investigators provided their agreement in presencial meeting for a final selection, and at a later stage, the articles were read in full by the three investigators. Results: The present systematic review includes eight randomized controlled trials. All articles show functional benefits in patients with AS subject to exercise programs in group based and / or home based. From the eight articles, 4 addressed programs conducted in home based context and 4 addressed in group based context programs. Conclusion: There appears to be evidence that the programs carried out based on group are more effective than those home based conducted in patients with AS. It was concluded also be advantageous to carry out home based exercise programs than the absence of any exercise program.
Designing for interaction: Six steps to designing computer-supported group-based learning
2004-01-01
At present, the design of computer-supported group-based learning (CS)GBL) is often based on subjective decisions regarding tasks, pedagogy and technology, or concepts such as cooperative learning and collaborative learning. Critical review reveals these concepts as insufficiently substantial to serve as a basis for (CS)GBL design. Furthermore, the relationship between outcome and group interaction is rarely specified a priori. Thus, there is a need for a more systematic approach to desig...
DEFF Research Database (Denmark)
Buus, Niels; Angel, Sanne; Traynor, Michael
2010-01-01
Group-based clinical supervision is commonly offered as a stress-reducing intervention in psychiatric settings, but nurses often feel ambivalent about participating. This study aimed at exploring psychiatric nurses' experiences of participating in groupbased supervision and identifying psychosocial...... reasons for their ambivalence. Semi-structured interviews were conducted with 22 psychiatric nurses at a Danish university hospital. The results indicated that participation in clinical supervision was difficult for the nurses because of an uncomfortable exposure to the professional community. The sense...... of exposure was caused by the particular interactional organisation during the sessions, which brought to light pre-existing but covert conflicts among the nurses....
Kombrink, Karola; Munk, Axel; Friede, Tim
2013-08-15
The clinical trial design including a test treatment, an active control and a placebo is called the gold standard design. In this paper, we develop a statistical method for planning and evaluating non-inferiority trials with gold standard design for right-censored time-to-event data. We consider both lost to follow-up and administrative censoring. We present a semiparametric approach that only assumes the proportionality of the hazard functions. In particular, we develop an algorithm for calculating the minimal total sample size and its optimal allocation to treatment groups such that a desired power can be attained for a specific parameter constellation under the alternative. For the purpose of sample size calculation, we assume the endpoints to be Weibull distributed. By means of simulations, we investigate the actual type I error rate, power and the accuracy of the calculated sample sizes. Finally, we compare our procedure with a previously proposed procedure assuming exponentially distributed event times. To illustrate our method, we consider a double-blinded, randomized, active and placebo controlled trial in major depression. Copyright © 2013 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
Julie Vercelloni
Full Text Available Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making.
Vercelloni, Julie; Caley, M Julian; Kayal, Mohsen; Low-Choy, Samantha; Mengersen, Kerrie
2014-01-01
Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making.
Institute of Scientific and Technical Information of China (English)
冯三营; 薛留根
2012-01-01
考虑非参数协变量带有测量误差(EV)的非线性半参数模型,在测量误差分布为普通光滑分布时,利用经验似然方法,给出了回归系数,光滑函数以及误差方差的最大经验似然估计.在一定条件下证明了所得估计量的渐近正态性和相合性.最后通过数值模拟研究了所提估计方法在有限样本下的实际表现.%In this paper, we consider the nonlinear semiparametric models with measurement error in the nonparametric part. When the error is ordinarily smooth, we obtain the maximum empirical likelihood estimators of regression coefficient, smooth function and error variance by using the empirical likelihood method. The asymptotic normality and consistency of the proposed estimators are proved under some appropriate conditions. Finite sample performance of the proposed method is illustrated in a simulation study.
Concomitant variables in finite mixture models
Wedel, M
The standard mixture model, the concomitant variable mixture model, the mixture regression model and the concomitant variable mixture regression model all enable simultaneous identification and description of groups of observations. This study reviews the different ways in which dependencies among
Multiclass Boosting with Adaptive Group-Based kNN and Its Application in Text Categorization
Directory of Open Access Journals (Sweden)
Lei La
2012-01-01
Full Text Available AdaBoost is an excellent committee-based tool for classification. However, its effectiveness and efficiency in multiclass categorization face the challenges from methods based on support vector machine (SVM, neural networks (NN, naïve Bayes, and k-nearest neighbor (kNN. This paper uses a novel multi-class AdaBoost algorithm to avoid reducing the multi-class classification problem to multiple two-class classification problems. This novel method is more effective. In addition, it keeps the accuracy advantage of existing AdaBoost. An adaptive group-based kNN method is proposed in this paper to build more accurate weak classifiers and in this way control the number of basis classifiers in an acceptable range. To further enhance the performance, weak classifiers are combined into a strong classifier through a double iterative weighted way and construct an adaptive group-based kNN boosting algorithm (AGkNN-AdaBoost. We implement AGkNN-AdaBoost in a Chinese text categorization system. Experimental results showed that the classification algorithm proposed in this paper has better performance both in precision and recall than many other text categorization methods including traditional AdaBoost. In addition, the processing speed is significantly enhanced than original AdaBoost and many other classic categorization algorithms.
Testing the effectiveness of group-based memory rehabilitation in chronic stroke patients.
Miller, Laurie A; Radford, Kylie
2014-01-01
Memory complaints are common after stroke, yet there have been very few studies of the outcome of memory rehabilitation in these patients. The present study evaluated the effectiveness of a new manualised, group-based memory training programme. Forty outpatients with a single-stroke history and ongoing memory complaints were enrolled. The six-week course involved education and strategy training and was evaluated using a wait-list crossover design, with three assessments conducted 12 weeks apart. Outcome measures included: tests of anterograde memory (Rey Auditory Verbal Learning Test: RAVLT; Complex Figure Test) and prospective memory (Royal Prince Alfred Prospective Memory Test); the Comprehensive Assessment of Prospective Memory (CAPM) questionnaire and self-report of number of strategies used. Significant training-related gains were found on RAVLT learning and delayed recall and on CAPM informant report. Lower baseline scores predicted greater gains for several outcome measures. Patients with higher IQ or level of education showed more gains in number of strategies used. Shorter time since onset was related to gains in prospective memory, but no other stroke-related variables influenced outcome. Our study provides evidence that a relatively brief, group-based training intervention can improve memory functioning in chronic stroke patients and clarified some of the baseline factors that influence outcome.
Decentralized architecture for resource management of group-based distributed systems
Institute of Scientific and Technical Information of China (English)
Rong ZHANG; Koji ZETTSU; Yutaka KIDAWARA; Yasushi KIYOKI
2008-01-01
As the development of hardware and software,large scale,flexible,distributed,secure and coordinated resource sharing has attracted much attention.One of the major challenges is to support distributed group-based resource management,e.g.interest-based organization,with resources/services classifiable.Although there have been some proposals to-address this challenge,they share the same weakness of using either severs or super peers to keep global knowledge,and win good search efficiency at the expenses of the system scalability.As a result,such designs can not keep both the search efficiency and system scalability.To that end,this paper proposes a group-based distributed architecture.It organizes the nodes inside the groups by Chord protocol,a classical Peer-to-Peer (P2P) technology and it defines new communication protocol for nodes among different groups but removes servers/super peers for group management.Such a design keeps the resource classifiable property together with good system performance.The main characteristics of this architecture are highlighted by its convenience for group activity analysis,promising scalability,high search efficiency,as well as robustness.The experimental performance results presented in the paper demonstrate the efficiency of the design.
A Human-Centric Approach To Group-Based Context-Awareness
Directory of Open Access Journals (Sweden)
Nasser Ghadiri
2011-01-01
Full Text Available The emerging need for qualitative approaches in context-aware information processing calls for proper modelling of context information and efficient handling of its inherent uncertainty resulted from human interpretation and usage. Many of the current approaches to context-awareness either lack a solid theoretical basis for modelling or ignore important requirements such as modularity, high-order uncertainty management and group-based context-awareness. Therefore, their real-world application and extendibility remains limited. In this paper, we present f-Context as a service-based contextawareness framework, based on language-action perspective (LAP theory for modelling. Then we identify some of the complex, informational parts of context which contain high-order uncertainties due to differences between members of the group in defining them. An agent-based perceptual computer architecture is proposed for implementing f-Context that uses computing with words (CWW for handling uncertainty. The feasibility of f-Context is analyzed using a realistic scenario involving a group of mobile users. We believe that the proposed approach can open the door to future research on context-awareness by offering a theoretical foundation based on human communication, and a service-based layered architecture which exploits CWW for context-aware, group-based and platform-independent access to information systems.
Protein mixtures: interactions and gelation
Ersch, C.
2015-01-01
Gelation is a ubiquitous process in the preparation of foods. As most foods are multi constituent mixtures, understanding gelation in mixtures is an important goal in food science. Here we presented a systematic investigation on the influence of molecular interactions on the gelation in protein mixtures. Gelatin gels with added globular protein and globular protein gels with added gelatin were analyzed for their gel microstructure and rheological properties. Mixed gels with altered microstruc...
de Vos, Bart; van Zomeren, Martijn; Gordijn, Ernestine H.; Postmes, Tom
2013-01-01
The communication of group-based anger in intergroup conflict is often associated with destructive conflict behavior. However, we show that communicating group-based anger toward the out-group can evoke empathy and thus reduce intergroup conflict. This is because it stresses the value of maintaining
de Vos, Bart; van Zomeren, Martijn; Gordijn, Ernestine H.; Postmes, Tom
2013-01-01
The communication of group-based anger in intergroup conflict is often associated with destructive conflict behavior. However, we show that communicating group-based anger toward the out-group can evoke empathy and thus reduce intergroup conflict. This is because it stresses the value of maintaining
Neurotoxicity of Metal Mixtures.
Andrade, V M; Aschner, M; Marreilha Dos Santos, A P
2017-01-01
Metals are the oldest toxins known to humans. Metals differ from other toxic substances in that they are neither created nor destroyed by humans (Casarett and Doull's, Toxicology: the basic science of poisons, 8th edn. McGraw-Hill, London, 2013). Metals are of great importance in our daily life and their frequent use makes their omnipresence and a constant source of human exposure. Metals such as arsenic [As], lead [Pb], mercury [Hg], aluminum [Al] and cadmium [Cd] do not have any specific role in an organism and can be toxic even at low levels. The Substance Priority List of Agency for Toxic Substances and Disease Registry (ATSDR) ranked substances based on a combination of their frequency, toxicity, and potential for human exposure. In this list, As, Pb, Hg, and Cd occupy the first, second, third, and seventh positions, respectively (ATSDR, Priority list of hazardous substances. U.S. Department of Health and Human Services, Public Health Service, Atlanta, 2016). Besides existing individually, these metals are also (or mainly) found as mixtures in various parts of the ecosystem (Cobbina SJ, Chen Y, Zhou Z, Wub X, Feng W, Wang W, Mao G, Xu H, Zhang Z, Wua X, Yang L, Chemosphere 132:79-86, 2015). Interactions among components of a mixture may change toxicokinetics and toxicodynamics (Spurgeon DJ, Jones OAH, Dorne J-L, Svendsen C, Swain S, Stürzenbaum SR, Sci Total Environ 408:3725-3734, 2010) and may result in greater (synergistic) toxicity (Lister LJ, Svendsen C, Wright J, Hooper HL, Spurgeon DJ, Environ Int 37:663-670, 2011). This is particularly worrisome when the components of the mixture individually attack the same organs. On the other hand, metals such as manganese [Mn], iron [Fe], copper [Cu], and zinc [Zn] are essential metals, and their presence in the body below or above homeostatic levels can also lead to disease states (Annangi B, Bonassi S, Marcos R, Hernández A, Mutat Res 770(Pt A):140-161, 2016). Pb, As, Cd, and Hg can induce Fe, Cu, and Zn
Aspects of Nonabelian Group Based Cryptography: A Survey and Open Problems
Fine, Benjamin; Kahrobaei, Delaram; Rosenberger, Gerhard
2011-01-01
Most common public key cryptosystems and public key exchange protocols presently in use, such as the RSA algorithm, Diffie-Hellman, and elliptic curve methods are number theory based and hence depend on the structure of abelian groups. The strength of computing machinery has made these techniques theoretically susceptible to attack and hence recently there has been an active line of research to develop cryptosystems and key exchange protocols using noncommutative cryptographic platforms. This line of investigation has been given the broad title of noncommutative algebraic cryptography. This was initiated by two public key protocols that used the braid groups, one by Ko, Lee et.al.and one by Anshel, Anshel and Goldfeld. The study of these protocols and the group theory surrounding them has had a large effect on research in infinite group theory. In this paper we survey these noncommutative group based methods and discuss several ideas in abstract infinite group theory that have arisen from them. We then presen...
Directory of Open Access Journals (Sweden)
Tinka M Veldhuis
Full Text Available Rejection can convey that one is seen as inferior and not worth bothering with. Is it possible for people to feel vicariously rejected in this sense and have reactions that are similar to those following personal rejection, such as feeling humiliated, powerless, and angry? A study on personal rejection was followed by two main studies on vicarious group-based rejection. It was found that merely observing rejection of ingroup members can trigger feelings of humiliation that are equally intense as those experienced in response to personal rejection. Moreover, given that the rejection is explicit, vicariously experienced feelings of humiliation can be accompanied by powerlessness and anger. Potentially, this combination of emotions could be an important source of offensive action against rejecters.
Uncertainty dimensions of information behaviour in a group based problem solving context
DEFF Research Database (Denmark)
Hyldegård, Jette
2009-01-01
This paper presents a study of uncertainty dimensions of information behaviour in a group based problem solving context. After a presentation of the cognitive uncertainty dimension underlying Kuhlthau's ISP-model, uncertainty factors associated with personality, the work task situation and social...... members' experiences of uncertainty differ from the individual information seeker in Kuhlthau's ISP-model, and how this experience may be related to personal, work task and social factors. A number of methods have been employed to collect data on each group member during the assignment process......: a demographic survey, a personality test, 3 process surveys, 3 diaries and 3 interviews. It was found that group members' experiences of uncertainty did not correspond with the ISP-model in that other factors beyond the mere information searching process seemed to intermingle with the complex process...
GBP-WAHSN: A Group-Based Protocol for Large Wireless Ad Hoc and Sensor Networks
Institute of Scientific and Technical Information of China (English)
Jaime Lloret; Miguel Garcia; Jesus Tomás; Fernando Boronat
2008-01-01
Grouping nodes gives better performance to the whole network by diminishing the average network delay and avoiding unnecessary message for warding and additional overhead. Many routing protocols for ad-hoc and sensor network shave been designed but none of them are based on groups. In this paper, we will start defining group-based topologies,and then we will show how some wireless ad hoc sensor networks (WAHSN) routing protocols perform when the nodes are arranged in groups. In our proposal connections between groups are established as a function of the proximity of the nodes and the neighbor's available capacity (based on the node's energy). We describe the architecture proposal, the messages that are needed for the proper operation and its mathematical description. We have also simulated how much time is needed to propagate information between groups. Finally, we will show a comparison with other architectures.
A Human-Centric Approach to Group-Based Context-Awareness
Ghadiri, Nasser; Ghasem-Aghaee, Nasser; Nematbakhsh, Mohammad A; 10.5121/ijnsa.2011.3104
2011-01-01
The emerging need for qualitative approaches in context-aware information processing calls for proper modeling of context information and efficient handling of its inherent uncertainty resulted from human interpretation and usage. Many of the current approaches to context-awareness either lack a solid theoretical basis for modeling or ignore important requirements such as modularity, high-order uncertainty management and group-based context-awareness. Therefore, their real-world application and extendability remains limited. In this paper, we present f-Context as a service-based context-awareness framework, based on language-action perspective (LAP) theory for modeling. Then we identify some of the complex, informational parts of context which contain high-order uncertainties due to differences between members of the group in defining them. An agent-based perceptual computer architecture is proposed for implementing f-Context that uses computing with words (CWW) for handling uncertainty. The feasibility of f-...
Group-based microfinance for collective empowerment: a systematic review of health impacts.
Orton, Lois; Pennington, Andy; Nayak, Shilpa; Sowden, Amanda; White, Martin; Whitehead, Margaret
2016-09-01
To assess the impact on health-related outcomes, of group microfinance schemes based on collective empowerment. We searched the databases Social Sciences Citation Index, Embase, MEDLINE, MEDLINE In-Process, PsycINFO, Social Policy & Practice and Conference Proceedings Citation Index for articles published between 1 January 1980 and 29 February 2016. Articles reporting on health impacts associated with group-based microfinance were included in a narrative synthesis. We identified one cluster-randomized control trial and 22 quasi-experimental studies. All of the included interventions targeted poor women living in low- or middle-income countries. Some included a health-promotion component. The results of the higher quality studies indicated an association between membership of a microfinance scheme and improvements in the health of women and their children. The observed improvements included reduced maternal and infant mortality, better sexual health and, in some cases, lower levels of interpersonal violence. According to the results of the few studies in which changes in empowerment were measured, membership of the relatively large and well-established microfinance schemes generally led to increased empowerment but this did not necessarily translate into improved health outcomes. Qualitative evidence suggested that increased empowerment may have contributed to observed improvements in contraceptive use and mental well-being and reductions in the risk of violence from an intimate partner. Membership of the larger, well-established group-based microfinance schemes is associated with improvements in some health outcomes. Future studies need to be designed to cope better with bias and to assess negative as well as positive social and health impacts.
Masicampo, E J; Barth, Maria; Ambady, Nalini
2014-12-01
Knowledge of individuals' group membership can alter moral judgments of their behavior. We found that such moral judgments were amplified when judgers learned that a person belonged to a group shown to elicit disgust in others. When a person was labeled as obese, a hippie, or "trailer trash," people judged that person's behavior differently than when such descriptors were omitted: Virtuous behaviors were more highly praised, and moral violations were more severely criticized. Such group-based discrimination in moral judgment was specific to the domain of moral purity. Members of disgust-eliciting groups but not members of other minorities were the target of harsh judgments for purity violations (e.g., lewd behavior) but not for other violations (e.g., refusing to help others). The same pattern held true for virtuous behaviors, so that members of disgust-eliciting groups were more highly praised than others but only in the purity domain. Furthermore, group-based discrimination was mediated by feelings of disgust toward the target group but not by other emotions. Last, analysis of New York Police Department officers' encounters with suspected criminals revealed a similar pattern to that found in laboratory experiments. Police officers were increasingly likely to make an arrest or issue a summons as body mass index increased (i.e., as obesity rose) among people suspected of purity crimes (e.g., prostitution) but not of other crimes (e.g., burglary). Thus, moral judgments in the lab and in the real world exhibit patterns of discrimination that are both group and behavior specific.
A Group-Based Yoga Therapy Intervention for Urinary Incontinence in Women: A Pilot Randomized Trial
Huang, Alison J.; Jenny, Hillary E.; Chesney, Margaret A.; Schembri, Michael; Subak, Leslee L.
2015-01-01
Objective To examine the feasibility, efficacy, and safety of a group-based yoga therapy intervention for middle-aged and older women with urinary incontinence. Methods We conducted a pilot randomized trial of ambulatory women aged 40 years and older with stress, urgency, or mixed-type incontinence. Women were randomized to a 6-week yoga therapy program (N=10) consisting of twice weekly group classes and once weekly home practice or a waitlist control group (N=9). All participants also received written pamphlets about standard behavioral self-management strategies for incontinence. Changes in incontinence were assessed by 7-day voiding diaries. Results Mean (±SD) age was 61.4 (±8.2) years, and mean baseline frequency of incontinence was 2.5 (±1.3) episodes/day. After 6 weeks, total incontinence frequency decreased by 66% (1.8 [±0.9] fewer episodes/day) in the yoga therapy versus 13% (0.3 [±1.7] fewer episodes/day) in the control group (P=0.049). Participants in the yoga therapy group also reported an average 85% decrease in stress incontinence frequency (0.7 [±0.8] fewer episodes/day) compared to a 25% increase in controls (0.2 [± 1.1] more episodes/day) (P=0.039). No significant differences in reduction in urgency incontinence were detected between the yoga therapy versus control groups (1.0 [±1.0] versus 0.5 [±0.5] fewer episodes/day, P=0.20). All women starting the yoga therapy program completed at least 90% of group classes and practice sessions. Two participants in each group reported adverse events unrelated to the intervention. Conclusions Findings provide preliminary evidence to support the feasibility, efficacy, and safety of a group-based yoga therapy intervention to improve urinary incontinence in women. PMID:24763156
Thermophysical Properties of Hydrocarbon Mixtures
SRD 4 NIST Thermophysical Properties of Hydrocarbon Mixtures (PC database for purchase) Interactive computer program for predicting thermodynamic and transport properties of pure fluids and fluid mixtures containing up to 20 components. The components are selected from a database of 196 components, mostly hydrocarbons.
Evaporating Drops of Alkane Mixtures
Guéna, Geoffroy; Poulard, Christophe; Cazabat, Anne-Marie
2005-01-01
22 pages 9 figures; Alkane mixtures are model systems where the influence of surface tension gradients during the spreading and the evaporation of wetting drops can be easily studied. The surface tension gradients are mainly induced by concentration gradients, mass diffusion being a stabilising process. Depending on the relative concentration of the mixture, a rich pattern of behaviours is obtained.
Protein mixtures: interactions and gelation
Ersch, C.
2015-01-01
Gelation is a ubiquitous process in the preparation of foods. As most foods are multi constituent mixtures, understanding gelation in mixtures is an important goal in food science. Here we presented a systematic investigation on the influence of molecular interactions on the gelation in protein mixt
Evaporating Drops of Alkane Mixtures
Gu'ena, G; Poulard, C; Cazabat, Anne-Marie; Gu\\'{e}na, Geoffroy; Poulard, Christophe
2005-01-01
Alkane mixtures are model systems where the influence of surface tension gradients during the spreading and the evaporation of wetting drops can be easily studied. The surface tension gradients are mainly induced by concentration gradients, mass diffusion being a stabilising process. Depending on the relative concentration of the mixture, a rich pattern of behaviours is obtained.
Protein mixtures: interactions and gelation
Ersch, C.
2015-01-01
Gelation is a ubiquitous process in the preparation of foods. As most foods are multi constituent mixtures, understanding gelation in mixtures is an important goal in food science. Here we presented a systematic investigation on the influence of molecular interactions on the gelation in protein mixt
Easy and flexible mixture distributions
DEFF Research Database (Denmark)
Fosgerau, Mogens; Mabit, Stefan L.
2013-01-01
We propose a method to generate flexible mixture distributions that are useful for estimating models such as the mixed logit model using simulation. The method is easy to implement, yet it can approximate essentially any mixture distribution. We test it with good results in a simulation study...
半参数平滑转换回归模型及其级数估计%A Semiparametric Smooth Transition Regression Model and Its Series Estimator
Institute of Scientific and Technical Information of China (English)
王成勇
2012-01-01
将STR类模型的转换函数设定为决定于某未知光滑有界函数的复合Logistic函数,提出半参数平滑转换回归模型.在独立同分布数据假设下,对其中的未知光滑有界函数采用级数估计,基于非线性最小二乘估计理论证明了参数估计量的相合性和渐近正态性,并简要讨论了置信区间的构造以及模型检验等问题.通过随机模拟与传统的STR模型进行比较,结果表明,该文的新模型及估计方法具有广泛的适用性和灵活性.%An unknown smooth function is substituted into the traditional smooth transition regression model and a semiparametric smooth transition regression model has been proposed in this paper. Based on the i.i.d. data assumption, we estimate the unknown smooth transition function by series estimator, the consistency and asymptotic normality properties of parameters are proved applying Nonlinear Least Square regression theory. The bootstrapping consistent confidence interval and hypothesis testing problem are also discussed briefly. The simulation results shows that, compared to traditional STR type model, our new model and estimating method are more flexible and have comprehensive applicability.
Directory of Open Access Journals (Sweden)
Gita Ramjee
2013-11-01
Full Text Available Objective: To describe and quantify the differences in risk behaviours, HIV prevalence and incidence rates by birth cohorts among a group of women in Durban, South Africa. Methods: Cross-sectional and prospective cohort analyses were conducted for women who consented to be screened and enrolled in an HIV prevention trial. Demographic and sexual behaviours were described by five-year birth cohorts. Semiparametric regression models were used to investigate the bivariate associations between these factors and the birth cohorts. HIV seroconversion rates were also estimated by birth cohorts. Results: The prevalence of HIV-1 infection at the screening visit was lowest (20.0% among the oldest (born before 1960 cohorts, while the highest prevalence was observed among those born between 1975 and 79. Level of education increased across the birth cohorts while the median age at first sexual experience declined among those born after 1975 compared to those born before 1975. Only 33.03% of the oldest group reported ever using a condom while engaging in vaginal sex compared to 73.68% in the youngest group; however, HIV and other sexually transmitted infection (STI incidence rates were significantly higher among younger women compared to older women. Conclusions: These findings clearly suggest that demographic and sexual risk behaviours are differentially related to the birth cohorts. Significantly high HIV and STI incidence rates were observed among the younger group. Although the level of education increased, early age at sexual debut was more common among the younger group. The continuing increase in HIV and STI incidence rates among the later cohorts suggests that the future trajectory of the epidemic will be dependent on the infection patterns in younger birth cohorts.
Gilbert, Peter B; Yu, Xuesong; Rotnitzky, Andrea
2014-03-15
To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semiparametric efficient estimator is applied. This approach is made efficient by specifying the phase two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. We perform simulations to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. We provide proofs and R code. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean 'importance-weighted' breadth (Y) of the T-cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24 % in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y | W] is important for realizing the efficiency gain, which is aided by an ample phase two sample and by using a robust fitting method. Copyright © 2013 John Wiley & Sons, Ltd.
Gilbert, Peter B.; Yu, Xuesong; Rotnitzky, Andrea
2014-01-01
To address the objective in a clinical trial to estimate the mean or mean difference of an expensive endpoint Y, one approach employs a two-phase sampling design, wherein inexpensive auxiliary variables W predictive of Y are measured in everyone, Y is measured in a random sample, and the semi-parametric efficient estimator is applied. This approach is made efficient by specifying the phase-two selection probabilities as optimal functions of the auxiliary variables and measurement costs. While this approach is familiar to survey samplers, it apparently has seldom been used in clinical trials, and several novel results practicable for clinical trials are developed. Simulations are performed to identify settings where the optimal approach significantly improves efficiency compared to approaches in current practice. Proofs and R code are provided. The optimality results are developed to design an HIV vaccine trial, with objective to compare the mean “importance-weighted” breadth (Y) of the T cell response between randomized vaccine groups. The trial collects an auxiliary response (W) highly predictive of Y, and measures Y in the optimal subset. We show that the optimal design-estimation approach can confer anywhere between absent and large efficiency gain (up to 24% in the examples) compared to the approach with the same efficient estimator but simple random sampling, where greater variability in the cost-standardized conditional variance of Y given W yields greater efficiency gains. Accurate estimation of E[Y∣W] is important for realizing the efficiency gain, which is aided by an ample phase-two sample and by using a robust fitting method. PMID:24123289
Weissman-Miller, Deborah
2013-11-02
Point estimation is particularly important in predicting weight loss in individuals or small groups. In this analysis, a new health response function is based on a model of human response over time to estimate long-term health outcomes from a change point in short-term linear regression. This important estimation capability is addressed for small groups and single-subject designs in pilot studies for clinical trials, medical and therapeutic clinical practice. These estimations are based on a change point given by parameters derived from short-term participant data in ordinary least squares (OLS) regression. The development of the change point in initial OLS data and the point estimations are given in a new semiparametric ratio estimator (SPRE) model. The new response function is taken as a ratio of two-parameter Weibull distributions times a prior outcome value that steps estimated outcomes forward in time, where the shape and scale parameters are estimated at the change point. The Weibull distributions used in this ratio are derived from a Kelvin model in mechanics taken here to represent human beings. A distinct feature of the SPRE model in this article is that initial treatment response for a small group or a single subject is reflected in long-term response to treatment. This model is applied to weight loss in obesity in a secondary analysis of data from a classic weight loss study, which has been selected due to the dramatic increase in obesity in the United States over the past 20 years. A very small relative error of estimated to test data is shown for obesity treatment with the weight loss medication phentermine or placebo for the test dataset. An application of SPRE in clinical medicine or occupational therapy is to estimate long-term weight loss for a single subject or a small group near the beginning of treatment.
Bayesian hierarchical grouping: Perceptual grouping as mixture estimation.
Froyen, Vicky; Feldman, Jacob; Singh, Manish
2015-10-01
We propose a novel framework for perceptual grouping based on the idea of mixture models, called Bayesian hierarchical grouping (BHG). In BHG, we assume that the configuration of image elements is generated by a mixture of distinct objects, each of which generates image elements according to some generative assumptions. Grouping, in this framework, means estimating the number and the parameters of the mixture components that generated the image, including estimating which image elements are "owned" by which objects. We present a tractable implementation of the framework, based on the hierarchical clustering approach of Heller and Ghahramani (2005). We illustrate it with examples drawn from a number of classical perceptual grouping problems, including dot clustering, contour integration, and part decomposition. Our approach yields an intuitive hierarchical representation of image elements, giving an explicit decomposition of the image into mixture components, along with estimates of the probability of various candidate decompositions. We show that BHG accounts well for a diverse range of empirical data drawn from the literature. Because BHG provides a principled quantification of the plausibility of grouping interpretations over a wide range of grouping problems, we argue that it provides an appealing unifying account of the elusive Gestalt notion of Prägnanz.
Batterman, Stuart; Su, Feng-Chiao; Li, Shi; Mukherjee, Bhramar; Jia, Chunrong
2015-01-01
semi-parametric Dirichlet process mixture (DPM) of normal distributions for three individual VOC
Atoning for Colonial Injustices: Group-Based Shame and Guilt Motivate Support for Reparation
Directory of Open Access Journals (Sweden)
Winnifred R. Louis
2010-05-01
Full Text Available An investigation of the role of group-based shame and guilt in motivating citizens of ex-colonial countries to support restitution to former colonized groups which were the target of violence and oppression. Study 1 (N = 125 was conducted in Australia during the lead-up to the first official government apology to Aboriginal Australians. Among white Australians, guilt and shame were associated with attitudinal support for intergroup apology and victim compensation. However, only shame was associated with actual political behaviour (signing a petition in support of the apology. Study 2 (N = 181, conducted in Britain, focussed on Britain's violent mistreatment of the Kenyan population during decolonization. It tested a hypothesis that there are two forms of shame-essence shame and image shame-and demonstrated that image shame was associated with support for apology, whereas essence shame was associated with support for more substantial material and financial compensation. The findings are discussed in light of promoting restitution and reconciliation within nations with histories of colonial violence.
The Visual Matrix Method: Imagery and Affect in a Group-Based Research Setting
Directory of Open Access Journals (Sweden)
Lynn Froggett
2015-07-01
Full Text Available The visual matrix is a method for researching shared experience, stimulated by sensory material relevant to a research question. It is led by imagery, visualization and affect, which in the matrix take precedence over discourse. The method enables the symbolization of imaginative and emotional material, which might not otherwise be articulated and allows "unthought" dimensions of experience to emerge into consciousness in a participatory setting. We describe the process of the matrix with reference to the study "Public Art and Civic Engagement" (FROGGETT, MANLEY, ROY, PRIOR & DOHERTY, 2014 in which it was developed and tested. Subsequently, examples of its use in other contexts are provided. Both the matrix and post-matrix discussions are described, as is the interpretive process that follows. Theoretical sources are highlighted: its origins in social dreaming; the atemporal, associative nature of the thinking during and after the matrix which we describe through the Deleuzian idea of the rhizome; and the hermeneutic analysis which draws from object relations theory and the Lorenzerian tradition of scenic understanding. The matrix has been conceptualized as a "scenic rhizome" to account for its distinctive quality and hybrid origins in research practice. The scenic rhizome operates as a "third" between participants and the "objects" of contemplation. We suggest that some of the drawbacks of other group-based methods are avoided in the visual matrix—namely the tendency for inter-personal dynamics to dominate the event. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs150369
Towards Open-World Person Re-Identification by One-Shot Group-Based Verification.
Zheng, Wei-Shi; Gong, Shaogang; Xiang, Tao
2016-03-01
Solving the problem of matching people across non-overlapping multi-camera views, known as person re-identification (re-id), has received increasing interests in computer vision. In a real-world application scenario, a watch-list (gallery set) of a handful of known target people are provided with very few (in many cases only a single) image(s) (shots) per target. Existing re-id methods are largely unsuitable to address this open-world re-id challenge because they are designed for (1) a closed-world scenario where the gallery and probe sets are assumed to contain exactly the same people, (2) person-wise identification whereby the model attempts to verify exhaustively against each individual in the gallery set, and (3) learning a matching model using multi-shots. In this paper, a novel transfer local relative distance comparison (t-LRDC) model is formulated to address the open-world person re-identification problem by one-shot group-based verification. The model is designed to mine and transfer useful information from a labelled open-world non-target dataset. Extensive experiments demonstrate that the proposed approach outperforms both non-transfer learning and existing transfer learning based re-id methods.
Functional group based Ligand binding affinity scoring function at atomic environmental level
Varadwaj, Pritish Kumar; Lahiri, Tapobrata
2009-01-01
Use of knowledge based scoring function (KBSF) for virtual screening and molecular docking has become an established method for drug discovery. Lack of a precise and reliable free energy function that describes several interactions including water-mediated atomic interaction between amino-acid residues and ligand makes distance based statistical measure as the only alternative. Till now all the distance based scoring functions in KBSF arena use atom singularity concept, which neglects the environmental effect of the atom under consideration. We have developed a novel knowledge-based statistical energy function for protein-ligand complexes which takes atomic environment in to account hence functional group as a singular entity. The proposed knowledge based scoring function is fast, simple to construct, easy to use and moreover it tackle the existing problem of handling molecular orientation in active site pocket. We have designed and used Functional group based Ligand retrieval (FBLR) system which can identify and detect the orientation of functional groups in ligand. This decoy searching was used to build the above KBSF to quantify the activity and affinity of high resolution protein-ligand complexes. We have proposed the probable use of these decoys in molecular build-up as a de-novo drug designing approach. We have also discussed the possible use of the said KSBF in pharmacophore fragment detection and pseudo center based fragment alignment procedure. PMID:19255647
Group-based strategy diffusion in multiplex networks with weighted values
Yu, Jianyong; Jiang, J. C.; Xiang, Leijun
2017-03-01
The information diffusion of multiplex social networks has received increasing interests in recent years. Actually, the multiplex networks are made of many communities, and it should be gotten more attention for the influences of community level diffusion, besides of individual level interactions. In view of this, this work explores strategy interactions and diffusion processes in multiplex networks with weighted values from a new perspective. Two different groups consisting of some agents with different influential strength are firstly built in each layer network, the authority and non-authority groups. The strategy interactions between different groups in intralayer and interlayer networks are performed to explore community level diffusion, by playing two classical strategy games, Prisoner's Dilemma and Snowdrift Game. The impact forces from the different groups and the reactive forces from individual agents are simultaneously taken into account in intralayer and interlayer interactions. This paper reveals and explains the evolutions of cooperation diffusion and the influences of interlayer interaction tight degrees in multiplex networks with weighted values. Some thresholds of critical parameters of interaction degrees and games parameters settings are also discussed in group-based strategy diffusion.
Sensitivity of Some Explosive/Brine Mixtures
1980-08-01
concentration in brine mixtures. 3 Friction test results of brine mixtures. 10 4 Thermal test results of brine mixtures. 11 Li 71 - INTRODUCTION A...also carried out on these impact insensitive mixtures. Of the seven mixtures only the 15% M28-Comp. B sample passed the thermal test , since smoking
DEFF Research Database (Denmark)
Madsen, Majbritt; Larsen, Kristian; Madsen, Inger Kirkegård;
2013-01-01
This study aimed to test whether group-based rehabilitation focusing on strength training, education and self-management is more effective than individual, supervised home-training after fast-track total knee arthroplasty (TKA).......This study aimed to test whether group-based rehabilitation focusing on strength training, education and self-management is more effective than individual, supervised home-training after fast-track total knee arthroplasty (TKA)....
de Vos, Bart; van Zomeren, Martijn; Gordijn, Ernestine H; Postmes, Tom
2013-08-01
The communication of group-based anger in intergroup conflict is often associated with destructive conflict behavior. However, we show that communicating group-based anger toward the out-group can evoke empathy and thus reduce intergroup conflict. This is because it stresses the value of maintaining a positive long-term intergroup relationship, thereby increasing understanding for the situation (in contrast to the communication of the closely related emotion of contempt). Three experiments demonstrate that the communication of group-based anger indeed reduces destructive conflict intentions compared with (a) a control condition (Experiments 1-2), (b) the communication of group-based contempt (Experiment 2), and (c) the communication of a combination of group-based anger and contempt (Experiments 2-3). Moreover, results from all three experiments reveal that empathy mediated the positive effect of communicating "pure" group-based anger. We discuss the implications of these findings for the theory and practice of communicating emotions in intergroup conflicts.
Geometry method of estimating functions in nonlinear semiparametric models%非线性半参数统计模型估计函数的几何方法
Institute of Scientific and Technical Information of China (English)
周路平; 冯予
2016-01-01
The probability density function family of nonlinear semi-parametric statistical model are considered as a statistical manifold.Using the methods of differential geometry to construct Hilbert space corresponding to nonlinear semiparametric model, and then study some questions of estimation function. Using the subspace spanned by two kinds of score function to decompose the Hilbert space orthogonally,and then discuss the set of the estimated function is located, and how to select the best estimate of function problems. Finally, through the analysis of examples to verify the effectiveness of this method.%将非线性半参数统计模型的概率密度函数族视为统计流形，利用微分几何方法，建立非线性半参数统计模型相对应的Hilbert 空间，进而研究非线性半参数统计模型的估计函数问题。利用两类得分函数张成的子空间对 Hilbert 空间进行正交分解，进而讨论估计函数所在的集合，以及如何选取最优估计函数的问题。最后，通过实例分析来验证此方法的有效性。
Institute of Scientific and Technical Information of China (English)
裴晓换; 郭鹏江
2012-01-01
Aim To obtain the property of consistency for the estimates of β and g(·) in semiparametric regression model with missing data under fixed design. Methods Using the lemma, some inequality and the given conditions. Results The property of strong consistency for the estimates of β and g(·) is proved. Conclusion In the semiparametric regression model with missing data, the estimates of β and g(·)have the property of strong consistency.%目的 在随机缺失情况下证明固定设计半参数回归模型的强相合性.方法 利用引理,一些不等式及已给条件进行证明.结果 证明了参数β的最小二乘估计和未知函数g(·)的非参数核估计是强相合的.结论随机缺失下半参数回归模型中β的参数估计和非参数函数g(·)的估计量是强相合的.
Institute of Scientific and Technical Information of China (English)
王晖; 左国新
2013-01-01
基于高阶差分方法给出半参数回归模型中参数β的minimax线性估计条件,并指出差分方法下得到的最小二乘估计(β)diff为β的minimax线性估计.另外对差分项存在多重共线性的情况,指出参数β的岭估计(β)diff(k)存在minimax估计优良性的条件.%The paper introduces conditions of difference-based minimax estimates of the regression parameters β in a semiparametric model. The ordinary least squares estimator βdiff based on higher order differences of the observations, and the minimax linear estimator of β are considered at the same time. Furthermore, the difference-based ridge regression estimator βdiff(k) that used in the presence of multicollinearity in a semiparametric model, and the conditions of βdiff(k) as a minimax linear estimator are also considered.
Optimal Parameters Multicomponent Mixtures Extruding
Directory of Open Access Journals (Sweden)
Ramil F. Sagitov
2013-01-01
Full Text Available Experimental research of multicomponent mixtures extruding from production wastes are carried out, unit for production of composites from different types of waste is presented. Having analyzed dependence of multicomponent mixtures extruding energy requirements on die length and components content at three values of angular rate of screw rotation, we received the values of energy requirements at optimal length of the die, angular speed and percent of binding additives.
Gaussian-mixture umbrella sampling
Maragakis, Paul; van der Vaart, Arjan; Karplus, Martin
2009-01-01
We introduce the Gaussian-mixture umbrella sampling method (GAMUS), a biased molecular dynamics technique based on adaptive umbrella sampling that efficiently escapes free energy minima in multi-dimensional problems. The prior simulation data are reweighted with a maximum likelihood formulation, and the new approximate probability density is fit to a Gaussian-mixture model, augmented by information about the unsampled areas. The method can be used to identify free energy minima in multi-dimen...
Analysis of asphalt mixtures on town roads
Glavica, Primož
2006-01-01
Asphalt mixtures are most commonly used composite for construction of top layers of different drive ways. By definition asphalt mixtures are composed of crushed rock, fill, bitumen and additives. Percentage of individual components wary according to the purpose asphalt mixture is to be used for. Asphalt mixtures must be capable of enduring different types of load. According to the type of load asphalt mixtures are divided into asphalt mixtures used for supporting layers and asp...
Eriksson, Tina; Siersma, Volkert Dirk; Løgstrup, Louise; Buch, Martin Sandberg; Elwyn, Glyn; Edwards, Adrian
2010-10-01
The Maturity Matrix (MM) comprises a formative evaluation instrument for primary care practices to self-assess their degree of organisational development in a group setting, guided by an external facilitator. The practice teams discuss organisational development, score their own performance and set improvement goals for the following year. The objective of this project was to introduce a translated and culturally adapted version of the MM in Denmark, to test its feasibility, to promote and document organisational change in general practices and to analyse associations between the recorded change(s) and structural factors in practices and the factors associated with the MM process. MM was used by general practices in three counties in Denmark, in two assessment sessions 1 year apart. First rounds of MM visits were carried out in 2006-2007 in 60 practice teams (320 participants (163 GPs, 157 staff)) and the second round in 2007-2008. A total of 48 practice teams (228 participants (117 GPs; 111 staff) participated in both sessions. The MM sessions were the primary intervention. Moreover, in about half of the practices, the facilitator reminded practice teams of their goals by sending them the written report of the initial session and contacted the practices regularly by telephone reminding them of the goals they had set. Those practice teams had password-protected access to their own and benchmark data. Where the minimum possible is 0 and maximum possible is 8, the mean overall MM score increased from 4.4 to 5.3 (difference=0.9, 95%, CI 0.76 to 1.06) from first to second sessions, indicating that development had taken place as measured by this group-based self-evaluation method. There was some evidence that lower-scoring dimensions were prioritised and more limited evidence that the prioritisation and interventions between meetings were helpful to achieve changes. This study provides evidence that MM worked well in general practices in Denmark. Practice teams appeared
Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis
Directory of Open Access Journals (Sweden)
Li Y
2014-04-01
Full Text Available Yunfeng Li,1 Huanxue Zhou,2 Beilei Cai,1 Kristijan H Kahler,1 Haijun Tian,1 Susan Gabriel,1 Steve Arcona11Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 2KMK Consulting Inc., Florham Park, NJ, USABackground: Proportion of days covered (PDC, a commonly used adherence metric, does not provide information about the longitudinal course of adherence to treatment over time. Group-based trajectory model (GBTM is an alternative method that overcomes this limitation.Methods: The statistical principles of GBTM and PDC were applied to assess adherence during a 12-month follow-up in psoriasis patients starting treatment with a biologic. The optimal GBTM model was determined on the basis of the balance between each model's Bayesian information criterion and the percentage of patients in the smallest group in each model. Variables potentially predictive of adherence were evaluated.Results: In all, 3,249 patients were included in the analysis. Four GBTM adherence groups were suggested by the optimal model, and patients were categorized as demonstrating continuously high adherence, high-then-low adherence, moderate-then-low adherence, or consistently moderate adherence during follow-up. For comparison, four PDC groups were constructed: PDC Group 4 (PDC ≥75%, PDC Group 3 (25%≤ PDC <50%, PDC Group 2 (PDC <25%, and PDC Group 1 (50%≤ PDC <75%. Our findings suggest that the majority of patients (97.9% from PDC Group 2 demonstrated moderate-then-low adherence, whereas 96.4% of patients from PDC Group 4 showed continuously high adherence. The remaining PDC-based categorizations did not capture patients with uniform adherence behavior based on GBTM. In PDC Group 3, 25.3%, 17.2%, and 57.5% of patients exhibited GBTM-defined consistently moderate adherence, moderate-then-low adherence, or high-then-low adherence, respectively. In PDC Group 1, 70.8%, 23.6%, and 5.7% of patients had consistently moderate adherence, high-then-low adherence, and
Osborne, Danny; Huo, Yuen J; Smith, Heather J
2015-03-01
Although group-based relative deprivation predicts people's willingness to protest unfair outcomes, perceiving that one's subgroup is respected increases employees' support for organizations. An integration of these perspectives suggests that subgroup respect will dampen the impact of group-based relative deprivation on workers' responses to unfair organizational outcomes. We examined this hypothesis among university faculty (N = 804) who underwent a system-wide pay cut. As expected, group-based relative deprivation predicted protest intentions. This relationship was, however, muted among those who believed university administrators treated their area of expertise (i.e., their subgroup) with a high (vs. low) level of respect. Moderated mediation analyses confirmed that group-based relative deprivation had a conditional indirect effect on protest intentions via participants' (dis)identification with their university at low to moderate, but not high, levels of subgroup respect. Our finding that satisfying relational needs can attenuate responses to group-based relative deprivation demonstrates the benefits of integrating insights from distinct research traditions. © 2014 The British Psychological Society.
Marangoni Convection in Binary Mixtures
Zhang, J; Oron, A; Behringer, Robert P.; Oron, Alexander; Zhang, Jie
2006-01-01
Marangoni instabilities in binary mixtures are different from those in pure liquids. In contrast to a large amount of experimental work on Marangoni convection in pure liquids, such experiments in binary mixtures are not available in the literature, to our knowledge. Using binary mixtures of sodium chloride/water, we have systematically investigated the pattern formation for a set of substrate temperatures and solute concentrations in an open system. The flow patterns evolve with time, driven by surface-tension fluctuations due to evaporation and the Soret effect, while the air-liquid interface does not deform. A shadowgraph method is used to follow the pattern formation in time. The patterns are mainly composed of polygons and rolls. The mean pattern size first decreases slightly, and then gradually increases during the evolution. Evaporation affects the pattern formation mainly at the early stage and the local evaporation rate tends to become spatially uniform at the film surface. The Soret effect becomes i...
Mixtures of skewed Kalman filters
Kim, Hyoungmoon
2014-01-01
Normal state-space models are prevalent, but to increase the applicability of the Kalman filter, we propose mixtures of skewed, and extended skewed, Kalman filters. To do so, the closed skew-normal distribution is extended to a scale mixture class of closed skew-normal distributions. Some basic properties are derived and a class of closed skew. t distributions is obtained. Our suggested family of distributions is skewed and has heavy tails too, so it is appropriate for robust analysis. Our proposed special sequential Monte Carlo methods use a random mixture of the closed skew-normal distributions to approximate a target distribution. Hence it is possible to handle skewed and heavy tailed data simultaneously. These methods are illustrated with numerical experiments. © 2013 Elsevier Inc.
Teaching high-school Geoscience through a group-based activity: the Geotrivia experiment
Bakopoulou, Athanasia
2015-04-01
Geotrivia is an educational game which aims at the enhancement of geoscience teaching in secondary education, through an interactive group-based activity. As behavioural teaching methods no longer excite students in a multitask society, new approaches should be implemented to keep up with novel learning methodologies and team-based techniques. Thus, the main aim of the experiment was to come up with an alternative learning process on geology and geography in order to upgrade and attract more students to Geosciences. Geotrivia is based on the techniques of motivation (competition to be the winner) and enjoyable educational time (it is funny to play a game) in terms of team-based student collaboration. Pedagogical aims of Geotrivia consist of team-based work, independency, autonomy and initiative, active participation, student self-evaluation and metacognition. Geotrivia is a card game, consisting of about 150 playing cards, a whistle and an hourglass. Each playing card contains a geology- or geography-related question and the answer to the question is given in the lower part of the card. Class students are divided in about 4 groups of about 5 students each. The aim of each group is to collect as many cards as possible. The hourglass is flipped and a member of the team takes the pack of cards and uses it to ask questions to his team; the other members have to answer as many questions. The team wins a card when they give a correct answer. The game is played at the end of each curriculum unit; a comprehensive version of the game is held at end of the school year. Most -but not all- questions are based on the course syllabus, which deals with the geology and geography of Europe at junior high school level (e.g. what is the cause of high seismicity in Greece?). Accordingly, Geotrivia questions can be adjusted to each country school book of geology - geography at any grade. To evaluate the results of Geotrivia, we used the methodology of pretest and posttest, an
Institute of Scientific and Technical Information of China (English)
许昌; 岳东杰; 董育烦; 邓成发
2011-01-01
主成分分析在一定程度上可以解决大坝变形监测回归模型因子间的复共线性,然而当提取的主成分信息不充分时,主成分回归用于大坝安全预测可能失效.提出以主成分分析提取的主成分作为半参数回归的参数分量,剩余成分和模型误差作为未知的非参数分量对主成分回归进行补偿,建立一种基于主成分和半参数的大坝变形监测混合回归模型.利用某大坝实测资料进行建模分析,结果表明该混合模型能克服回归因子间的复共线性,避免半参数回归补偿最小二乘估计中法矩阵的病态性,比传统的主成分回归和逐步回归模型具有更好的拟合和预报精度.%Principal component analysis (PCA) is a solution to the multicollinearity problem of dam regression models. However, uninformative principal components (PCs) may lead to the failure prediction of dam deformation. Thus a hybrid regression model using semi-parametric regression and PCA is proposed, where the PCs with the highest variance are treated as the semi-parametric component; the remaining PCs and model errors are treated as the non-parametric component to be estimated. The hybrid model is tested using the field observations of a dam in China. The result shows the hybrid model can circumvent the multicollinearity of dam causative effects and the ill-conditioned problem in semi-parametric penalized least squares regression. A comparative study with traditional PC regression and stepwise regression demonstrate the superior performance for dam deformation prediction.
Taylor dispersion analysis of mixtures.
Cottet, Hervé; Biron, Jean-Philippe; Martin, Michel
2007-12-01
Taylor dispersion analysis (TDA) is a fast and simple method for determining hydrodynamic radii. In the case of sample mixtures, TDA, as the other nonseparative methods, leads to an average diffusion coefficient on the different molecules constituting the mixture. We set in this work the equations giving, on a consistent basis, the average values obtained by TDA with detectors with linear response functions. These equations confronted TDA experiments of sample mixtures containing different proportions of a small molecule and a polymer standard. Very good agreement between theory and experiment was obtained. In a second part of this work, on the basis of monomodal or bimodal molar mass distributions of polymers, the different average diffusion coefficients corresponding to TDA were compared to the z-average diffusion coefficient (D(z)) obtained from dynamic light scattering (DLS) experiments and to the weight average diffusion coefficient (D(w)). This latter value is sometimes considered as the most representative of the sample mixture. From these results, it appears that, for monomodal distribution and relatively low polydispersity (I = 1.15), the average diffusion coefficient generally derived from TDA is very close to Dw. However, for highly polydisperse samples (e.g., bimodal polydisperse distributions), important differences could be obtained (up to 35% between TDA and D(w)). In all the cases, the average diffusion coefficient obtained by TDA for a mass concentration detector was closer to the Dw value than the z-average obtained by DLS.
Bayerl, P.S.; Lauche, K.; Axtell, C.
2016-01-01
In this study, we set out to better understand the dynamics behind group-based technology adoption by nvestigating the underlying mechanisms of changes in collective adoption decisions over time. Using a longitudinal multi-case study of production teams in the British oil and gas industry, we outli
Barnes, Jacqueline; Melhuish, Edward C.
2017-01-01
This study investigated whether the amount and timing of group-based childcare between birth and 51 months were predictive of cognitive development at 51 months, taking into account other non-parental childcare, demographic characteristics, cognitive development at 18 months, sensitive parenting and a stimulating home environment. Children's…
A shared past and a common future: the Portuguese colonial war and the dynamics of group-based guilt
Figueiredo, A.; Valentim, J.; Doosje, B.
2011-01-01
In the present study we examine feelings of group-based guilt among Portuguese people in relation to the Portuguese colonial war, and their consequences for social behaviour. Specifically, we focus on the way Portuguese university students identify with their national group and the outgroup and thei
The Web as Process Tool and Product Environment for Group-Based Project Work in Higher Education.
Collis, Betty; Andernach, Toine; van Diepen, Nico
This paper discusses problems confronting the use of group-based project work as an instructional strategy in higher education, and describes two technical courses (i.e., courses in online learning and applications of business information technology) at the University of Twente (Netherlands) in which course-specific World Wide Web environments are…
How Perspective-Taking Helps and Hinders Group-Based Guilt as a Function of Group Identification
Zebel, Sven; Doosje, Bertjan; Spears, Russell
2009-01-01
In two studies we hypothesized that outgroup perspective-taking promotes group-based guilt among weakly identified perpetrator group members, but hinders it among higher identifiers. In Study 1, native Dutch participants (N = 153) confronted their group's past mistreatment of outgroups, while perspe
Weigel, Corina; Kokocinski, Kathrin; Lederer, Peter; Dotsch, Jorg; Rascher, Wolfgang; Knerr, Ina
2008-01-01
Objective: The authors performed a group-based program for obese children and adolescents in Bavaria, Germany to enable them to establish a health-oriented lifestyle and to reduce overweight. The authors compared this program with a control approach based on the patients' own initiative. Design: This is a controlled clinical trial. Setting: A…
The web as process tool and product environment for group-based project work in higher education
Collis, Betty; Andernach, Toine; Diepen, van Nico; Maurer, Hermann
1996-01-01
This paper discusses problems confronting the use of group-based project work as an instructional strategy in higher education, and describes two technical courses (i.e., courses in online learning and applications of business information technology) at the University of Twente (Netherlands) in whic
Rees, G.; Saw, C.; Larizza, M.; Lamoureux, E.; Keeffe, J.
2007-01-01
This qualitative study investigates the views of clients with low vision and vision rehabilitation professionals on the involvement of family and friends in group-based rehabilitation programs. Both groups outlined advantages and disadvantages to involving significant others, and it is essential that clients are given the choice. Future work is…
A shared past and a common future: the Portuguese colonial war and the dynamics of group-based guilt
Figueiredo, A.; Valentim, J.; Doosje, B.
2011-01-01
In the present study we examine feelings of group-based guilt among Portuguese people in relation to the Portuguese colonial war, and their consequences for social behaviour. Specifically, we focus on the way Portuguese university students identify with their national group and the outgroup and thei
Johnston, Keith; Conneely, Claire; Murchan, Damian; Tangney, Brendan
2015-01-01
Bridge21 is an innovative approach to learning for secondary education that was originally conceptualised as part of a social outreach intervention in the authors' third-level institution whereby participants attended workshops at a dedicated learning space on campus focusing on a particular model of technology-mediated group-based learning. This…
Bayerl, P.S.; Lauche, K.; Axtell, C.
2016-01-01
In this study, we set out to better understand the dynamics behind group-based technology adoption by nvestigating the underlying mechanisms of changes in collective adoption decisions over time. Using a longitudinal multi-case study of production teams in the British oil and gas industry, we
P.S. Bayerl (Saskia); K. Lauche (Kristina); Axtell, C. (Carolyn)
2016-01-01
textabstractIn this study, we set out to better understand the dynamics behind group-based technology adoption by investigating the underlying mechanisms of changes in collective adoption decisions over time. Using a longitudinal multi-case study of production teams in the British oil and gas
Fernald, Lia C. H.; Kagawa, Rose M. C.; Knauer, Heather A.; Schnaas, Lourdes; Guerra, Armando Garcia; Neufeld, Lynnette M.
2017-01-01
We examined effects on child development of a group-based parenting support program ("Educación Inicial" - EI) when combined with Mexico's conditional cash transfer (CCT) program ("Prospera," originally 'Oportunidades" and "Progresa"). This cluster-randomized trial included 204 communities (n = 1,113 children in…
Fernald, Lia C. H.; Kagawa, Rose M. C.; Knauer, Heather A.; Schnaas, Lourdes; Guerra, Armando Garcia; Neufeld, Lynnette M.
2017-01-01
We examined effects on child development of a group-based parenting support program ("Educación Inicial" - EI) when combined with Mexico's conditional cash transfer (CCT) program ("Prospera," originally 'Oportunidades" and "Progresa"). This cluster-randomized trial included 204 communities (n = 1,113 children in…
Baumgartner, S.E.; Leydesdorff, L.
2014-01-01
Group-based trajectory modeling (GBTM) is applied to the citation curves of articles in six journals and to all citable items in a single field of science (virology, 24 journals) to distinguish among the developmental trajectories in subpopulations. Can citation patterns of highly-cited papers be
ROBUST PENALIZED LEAST SQUARES ESTIMATION FOR A SEMIPARAMETRIC REGRESSION MODEL%半参数回归模型的稳健补偿最小二乘估计
Institute of Scientific and Technical Information of China (English)
胡宏昌
2008-01-01
In this paper, we consider a semiparametric regression model. By the robust penalized least squares estimate method, the robust penalized least squares estimators are given, and their influence functions and asymptotic variance-covariance matrixes are investigated. A simulated example shows that the method is excels the penalized least squares method, and has robustness.%本文研究了一类半参数回归模型,利用稳健补偿最小二乘估计法,得到了稳健补偿最小二乘估计量,以及它们的影响函数及渐近方差-协方差,对结果的分析表明了该法优于补偿最小二乘法,而且具有稳定性.
Institute of Scientific and Technical Information of China (English)
武大勇; 李锋
2015-01-01
The linear semiparametric regression models with missing data were considered.The maximum empirical es-timations of the regression coefficients,and the smoothing function were obtained by the maximum empirical method. The asymptotic normality and consistency of the proposed estimations were proved under some appropriate conditions.%考虑了随机缺失数据下非线性回归模型的估计问题，利用最大经验似然估计的方法给出了回归系数、光滑函数的最大经验似然估计，并在一定条件下证明了所得估计量的渐近正态性和强相合性。
Semiparametric inference of grouped zero-inflated poisson models%分组零膨胀泊松模型的半参数统计推断
Institute of Scientific and Technical Information of China (English)
钟雨珂; 薛宏旗; 张三国
2009-01-01
The incidence of zero counts is often greater than expected for the Poisson distribution and zero counts frequently have special status. And sometimes the count data may be grouped, which means that for some observation the count is not known exactly but is known to fall in a particular range. This paper considers a semiparametric zero-inflated Poisson (ZIP) model to fit such grouped data with excess zeros, where the partial linear link function is used in the mean of the Poisson distribution and the linear link function is used in modeling the probability of zero. A Sieve maximum likelihood estimator(MLE) is proposed to estimate both the regression parameters and the nonparametric function, and a score test is provided for the presence of excess zeros. Asymptotic properties of the proposed Sieve MLEs are discussed. Under some mild conditions, the estimators are shown to be strong consistent. Moreover, the estimators of the unknown parameters are asymptotic efficient and normally distributed. The estimator of the nonparametric function has optimal convergence rate. Simulation studies are carried out to investigate the performance of the proposed method. For illustration purpose, the method is applied to a data set from a public health survey.%泊松回归模型常常用于计数数据的研究中,然而在实际数据中零值的比例可能远远大于泊松分布中取零值的概率,而且这些零值通常都有其特殊含义.此外计数数据可能是分组数据,即观测到的数据不是确切值而只是已知其落在某一个区间范围之内;或者某些特定的数据,例如工资,要先对它进行人为的分组然后再进行分析.考虑一种零膨胀泊松半参数回归模型来处理上述分组计数数据.该模型中泊松分布的期望与协变量之间采用部分线性连接函数,而零值的概率与协变量之间采用线性连接函数.利用Sieve极大似然估计方法来估计该回归模型中参数和非参数函数,
Local fluctuations in solution mixtures
Ploetz, Elizabeth A.; Smith, Paul E.
2011-01-01
An extension of the traditional Kirkwood-Buff (KB) theory of solutions is outlined which provides additional fluctuating quantities that can be used to characterize and probe the behavior of solution mixtures. Particle-energy and energy-energy fluctuations for local regions of any multicomponent solution are expressed in terms of experimentally obtainable quantities, thereby supplementing the usual particle-particle fluctuations provided by the established KB inversion approach. The expressions are then used to analyze experimental data for pure water over a range of temperatures and pressures, a variety of pure liquids, and three binary solution mixtures – methanol and water, benzene and methanol, and aqueous sodium chloride. In addition to providing information on local properties of solutions it is argued that the particle-energy and energy-energy fluctuations can also be used to test and refine solute and solvent force fields for use in computer simulation studies. PMID:21806137
Binary mixtures of chiral gases
Presilla, Carlo
2015-01-01
A possible solution of the well known paradox of chiral molecules is based on the idea of spontaneous symmetry breaking. At low pressure the molecules are delocalized between the two minima of a given molecular potential while at higher pressure they become localized in one minimum due to the intermolecular dipole-dipole interactions. Evidence for such a phase transition is provided by measurements of the inversion spectrum of ammonia and deuterated ammonia at different pressures. In particular, at pressure greater than a critical value no inversion line is observed. These data are well accounted for by a model previously developed and recently extended to mixtures. In the present paper, we discuss the variation of the critical pressure in binary mixtures as a function of the fractions of the constituents.
Atomistic Simulations of Bicelle Mixtures
Jiang, Yong; Wang, Hao; Kindt, James T.
2010-01-01
Mixtures of long- and short-tail phosphatidylcholine lipids are known to self-assemble into a variety of aggregates combining flat bilayerlike and curved micellelike features, commonly called bicelles. Atomistic simulations of bilayer ribbons and perforated bilayers containing dimyristoylphosphatidylcholine (DMPC, di-C14 tails) and dihexanoylphosphatidylcholine (DHPC, di-C6 tails) have been carried out to investigate the partitioning of these components between flat and curved microenvironmen...
Atomistic Simulations of Bicelle Mixtures
Jiang, Yong; WANG, HAO; Kindt, James T.
2010-01-01
Mixtures of long- and short-tail phosphatidylcholine lipids are known to self-assemble into a variety of aggregates combining flat bilayerlike and curved micellelike features, commonly called bicelles. Atomistic simulations of bilayer ribbons and perforated bilayers containing dimyristoylphosphatidylcholine (DMPC, di-C14 tails) and dihexanoylphosphatidylcholine (DHPC, di-C6 tails) have been carried out to investigate the partitioning of these components between flat and curved microenvironmen...
FRACTIONAL TRANSPORT OF SEDIMENT MIXTURES
Institute of Scientific and Technical Information of China (English)
Baosheng WU; Albert MOLINAS; Anping SHU
2003-01-01
A new method based on the Transport Capacity Fraction (TCF) concept is proposed to compute the fractional transport rates for nonuniform sediment mixtures in sand-bed channels. The TCF concept is derived from the understanding that the measurements and predictions of bed-material load are more accurate and reliable than the measurements and predictions of fractional loads. First the bed-material load is computed using an appropriate equation, then the fractional transport rates are determined by distributing the bed-material load into size groups through a transport capacity distribution function. For the computation of bed-material loads, the Aekers and White, Engelund and Hansen, and Yang equations are used in this study. Two new transport capacity distribution functions are developed for flows in sand-bed channels. The new expressions presented in this paper account for the sheltering and exposure effects that exist in mixtures. Comparisons with measured data show that the proposed method can significantly improve the predictions of fractional transport rates for nonuniform sediment mixtures.
Donohue, Shane
2014-01-01
The use of audience response systems (ARSs) or 'clickers' in higher education has increased over the recent years, predominantly owing to their ability to actively engage students, for promoting individual and group learning, and for providing instantaneous feedback to students and teachers. This paper describes how group-based ARS quizzes have been integrated into an undergraduate civil engineering course on foundation design. Overall, the ARS summary quizzes were very well received by the students. Feedback obtained from the students indicates that the majority believed the group-based quizzes were useful activities, which helped to improve their understanding of course materials, encouraged self-assessment, and assisted preparation for their summative examination. Providing students with clickers does not, however, necessarily guarantee the class will be engaged with the activity. If an ARS activity is to be successful, careful planning and design must be carried out and modifications adopted where necessary, which should be informed by the literature and relevant student feedback.
Directory of Open Access Journals (Sweden)
Sumit Mehra
2016-11-01
Full Text Available Ageing is associated with a decline in daily functioning and mobility. A physically active life and physical exercise can minimize the decline of daily functioning and improve the physical-, psychological- and social functioning of older adults. Despite several advantages of group-based exercise programs, older adults participating in such interventions often do not meet the frequency, intensity or duration of exercises needed to gain health benefits. An exercise program that combines the advantages of group-based exercises led by an instructor with tailored home-based exercises can increase the effectiveness. Technology can assist in delivering a personalized program. The aim of the study was to determine the susceptibility of older adults currently participating in a nationwide group-based exercise program to such a blended exercise program. Eight focus-groups were held with adults of 55 years of age or older. Two researchers coded independently the remarks of the 30 participants that were included in the analysis according to the three key concepts of the Self Determination Theory: autonomy, competence and relatedness. The results show that maintaining self-reliance and keeping in touch with others were the main motives to participate in the weekly group-based exercises. Participants recognized benefits of doing additional home-based exercises, but had concerns regarding guidance, safety and motivation. Furthermore, some participants strongly rejected the idea to use technology to support them in doing exercises at home, but the majority was open to it. Insights are discussed how these findings can help design novel interventions that can increase the wellbeing of older adults and preserve an independent living.
Pressick, Elizabeth L; Gray, Marion A; Cole, Rachel L; Burkett, Brendan J
2016-09-01
To evaluate research into the effectiveness of group-based sport and exercise programs targeting Indigenous adults on anthropometric, physiological and quality of life outcomes. A systematic review with quality assessment of study design. A computer-based literature search of EBSCO, SPORTDiscus, CINAHL, Informit, Scopus, Web of Science, Medline, PubMed, Global Health, ProQuest and Discover databases was conducted. Methodological quality of individual articles was assessed using McMasters University Guidelines and Appraisal Forms for Critical Review for Quantitative Research. Results of the effectiveness of programs are then summarised. Six articles were identified with critical appraisal scores ranging from 6 to 12 (from a possible 15 points), with a mean score of 9.6. Five articles were of moderate to good quality. Significant improvements were observed in anthropometric, physiological and quality of life outcomes across all studies. Elements of successful group-based exercise and sport programs corresponded to global recommendations on physical activity for health for 18 to 64 year olds, and were implemented over a period of time ranging from 12 to 24 weeks to exhibit results, plus community consultation in developing programs and nutrition education. Group-based programs that include nutrition, exercise and/or sport components are effective in producing short to intermediate term health outcomes among Indigenous adults. Further high quality research, specifically on group-based modified sport programs for Indigenous adults that are culturally appropriate and aim to improve quality of life are needed. Copyright © 2015 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Beltrán Carrillo, Vicente J.; Tortosa Martínez, Juan; Jennings, George; Sánchez, Elena S.
2013-01-01
Numerous quantitative studies have illustrated the potential usefulness of exercise programs for women with fibromyalgia. However, a deeper understanding of the physical and especially psychosocial benefits of exercise therapy from the subjective perspective of this population is still needed. This study was conducted with 25 women who had fibromyalgia and were participating in a nine-month, group-based exercise program. The aim was to provide an in-depth description and analysis of the perce...
Mutwarasibo, Faustin
2013-01-01
The overarching aim of the present thesis is to gain knowledge about how Rwandan university students understand and practice group-based learning. Specifically, this research takes a social constructivist perspective when examining how second year students within the area of Modern Languages reflect on collaborative writing and peer assessment as means to promote academic writing and active learning. Four studies make up this research. Thus, Study I examines how students carry out self-direct...
Mac Neil, Brad A; Leung, Pauline; Nadkarni, Pallavi; Stubbs, Laura; Singh, Manya
2016-10-01
Eating disorder clinics across Canada place heavy reliance on group-based programming. However, little work has examined whether this modality of treatment is well-received by patients and results in clinical improvements. The purpose of this pilot study was to evaluate patient satisfaction and outcomes for group-based programming offered through an adult eating disorders clinic. Participants were 81 adults who met DSM-5 criteria for an eating disorder and participated in the study as part of the clinic's program evaluation. Participants received medical monitoring, psychiatric follow-up, adjunct nutrition and pre-psychological treatment, and participated in the clinic's core cognitive behavioural therapy (CBT) group. Demographic information and weight were collected at intake. Participants also completed pre- and post-group programming measures of life satisfaction, depressive and anxiety symptoms, psychological symptoms of the eating disorder, and satisfaction with the programming. Participants' experienced a significant increase in satisfaction with life, and decreases in depressive symptoms and psychological symptoms of the eating disorder post-group. Adults endorsed feeling fairly satisfied with the group-based services provided. Results draw attention to the importance of program evaluation as an integral component of an adult outpatient eating disorder clinic by providing a voice for patients' views of the services received and program outcomes.
Espejo, Emmanuel P; Gorlick, Amanda; Castriotta, Natalie
2017-03-01
Group-based Transdiagnostic Cognitive Behavioral Therapy (TCBT) for anxiety disorders aims to target common factors to produce beneficial effects on multiple anxiety disorders at once. While there is growing evidence that various anxiety disorders can be effectively treated by this approach, the common factors contributing to these treatment effects are not well delineated. In a sample of 48 Veterans who completed Group-based TCBT, the current study examined change in threat perception and change in experiential avoidance pre to post-treatment and as potential mediators of changes in negative affect and personalized fear ratings. Results indicated that both threat perception and experiential avoidance were significantly reduced during treatment. Additionally, reductions in both threat perception and experiential avoidance significantly predicted reductions in negative affect and fear ratings. When change in threat perception and change in experiential avoidance were examined simultaneously, both remained significant predictors of changes in negative affect though only experiential avoidance predicted changes in fear ratings. Thus, both reductions in threat perception and experiential avoidance may mediate the broad treatment effects observed in group-based TCBT. Directions for future research are discussed. Published by Elsevier Ltd.
21 CFR 82.6 - Certifiable mixtures.
2010-04-01
... mixture is harmless and suitable for use therein; and (3) No diluent (except resins, natural gum, pectin... mixture is for external application to shell eggs, or for use in coloring a food specified in the...
Psychophysical studies of mixtures of tastants
Graaf, de C.
1988-01-01
The human perception of mixtures of tastante was studied with reference to three central issues, i.e., 1) the paradigma of equiratio taste substance mixtures. as an instrument to manipulate the physical composition of tastant mixtures. This paradiama also enables the construction of psychophysical
Supercritical Water Mixture (SCWM) Experiment
Hicks, Michael C.; Hegde, Uday G.
2012-01-01
The subject presentation, entitled, Supercritical Water Mixture (SCWM) Experiment, was presented at the International Space Station (ISS) Increment 33/34 Science Symposium. This presentation provides an overview of an international collaboration between NASA and CNES to study the behavior of a dilute aqueous solution of Na2SO4 (5% w) at near-critical conditions. The Supercritical Water Mixture (SCWM) investigation, serves as important precursor work for subsequent Supercritical Water Oxidation (SCWO) experiments. The SCWM investigation will be performed in DECLICs High Temperature Insert (HTI) for the purpose of studying critical fluid phenomena at high temperatures and pressures. The HTI includes a completely sealed and integrated test cell (i.e., Sample Cell Unit SCU) that will contain approximately 0.3 ml of the aqueous test solution. During the sequence of tests, scheduled to be performed in FY13, temperatures and pressures will be elevated to critical conditions (i.e., Tc = 374C and Pc = 22 MPa) in order to observe salt precipitation, precipitate agglomeration and precipitate transport in the presence of a temperature gradient without the influences of gravitational forces. This presentation provides an overview of the motivation for this work, a description of the DECLIC HTI hardware, the proposed test sequences, and a brief discussion of the scientific research objectives.
Atomistic simulations of bicelle mixtures.
Jiang, Yong; Wang, Hao; Kindt, James T
2010-06-16
Mixtures of long- and short-tail phosphatidylcholine lipids are known to self-assemble into a variety of aggregates combining flat bilayerlike and curved micellelike features, commonly called bicelles. Atomistic simulations of bilayer ribbons and perforated bilayers containing dimyristoylphosphatidylcholine (DMPC, di-C(14) tails) and dihexanoylphosphatidylcholine (DHPC, di-C(6) tails) have been carried out to investigate the partitioning of these components between flat and curved microenvironments and the stabilization of the bilayer edge by DHPC. To approach equilibrium partitioning of lipids on an achievable simulation timescale, configuration-bias Monte Carlo mutation moves were used to allow individual lipids to change tail length within a semigrand-canonical ensemble. Since acceptance probabilities for direct transitions between DMPC and DHPC were negligible, a third component with intermediate tail length (didecanoylphosphatidylcholine, di-C(10) tails) was included at a low concentration to serve as an intermediate for transitions between DMPC and DHPC. Strong enrichment of DHPC is seen at ribbon and pore edges, with an excess linear density of approximately 3 nm(-1). The simulation model yields estimates for the onset of edge stability with increasing bilayer DHPC content between 5% and 15% DHPC at 300 K and between 7% and 17% DHPC at 323 K, higher than experimental estimates. Local structure and composition at points of close contact between pores suggest a possible mechanism for effective attractions between pores, providing a rationalization for the tendency of bicelle mixtures to aggregate into perforated vesicles and perforated sheets.
The Kinetics of Enzyme Mixtures
Directory of Open Access Journals (Sweden)
Simon Brown
2014-03-01
Full Text Available Even purified enzyme preparations are often heterogeneous. For example, preparations of aspartate aminotransferase or cytochrome oxidase can consist of several different forms of the enzyme. For this reason we consider how different the kinetics of the reactions catalysed by a mixture of forms of an enzyme must be to provide some indication of the characteristics of the species present. Based on the standard Michaelis-Menten model, we show that if the Michaelis constants (Km of two isoforms differ by a factor of at least 20 the steady-state kinetics can be used to characterise the mixture. However, even if heterogeneity is reflected in the kinetic data, the proportions of the different forms of the enzyme cannot be estimated from the kinetic data alone. Consequently, the heterogeneity of enzyme preparations is rarely reflected in measurements of their steady-state kinetics unless the species present have significantly different kinetic properties. This has two implications: (1 it is difficult, but not impossible, to detect molecular heterogeneity using kinetic data and (2 even when it is possible, a considerable quantity of high quality data is required.
Werth, Arman Karl
Cooperative learning has been one of the most widely used instructional practices around the world since the early 1980's. Small learning groups have been in existence since the beginning of the human race. These groups have grown in their variance and complexity overtime. Classrooms are getting more diverse every year and instructors need a way to take advantage of this diversity to improve learning. The purpose of this study was to see if heterogeneous cooperative learning groups based on student achievement can be used as a differentiated instructional strategy to increase students' ability to demonstrate knowledge of science concepts and ability to do engineering design. This study includes two different groups made up of two different middle school science classrooms of 25-30 students. These students were given an engineering design problem to solve within cooperative learning groups. One class was put into heterogeneous cooperative learning groups based on student's pre-test scores. The other class was grouped based on random assignment. The study measured the difference between each class's pre-post gains, student's responses to a group interaction form and interview questions addressing their perceptions of the makeup of their groups. The findings of the study were that there was no significant difference between learning gains for the treatment and comparison groups. There was a significant difference between the treatment and comparison groups in student perceptions of their group's ability to stay on task and manage their time efficiently. Both the comparison and treatment groups had a positive perception of the composition of their cooperative learning groups.
Effect of Mixture Pressure and Equivalence Ratio on Detonation Cell Size for Hydrogen-Air Mixtures
2015-06-01
EFFECT OF MIXTURE PRESSURE AND EQUIVALENCE RATIO ON DETONATION CELL SIZE FOR HYDROGEN -AIR MIXTURES...protection in the United States. AFIT-ENY-MS-15-J-045 EFFECT OF MIXTURE PRESSURE AND EQUIVALENCE RATIO ON DETONATION CELL SIZE FOR HYDROGEN -AIR...DISTRIBUTION UNLIMITED. AFIT-ENY-MS-15-J-045 EFFECT OF MIXTURE PRESSURE AND EQUIVALENCE RATIO ON DETONATION CELL SIZE FOR HYDROGEN -AIR MIXTURES
Directory of Open Access Journals (Sweden)
Nabila El-Bassel
Full Text Available IMPORTANCE: This study is designed to address the need for evidence-based HIV/STI prevention approaches for drug-involved women under criminal justice community supervision. OBJECTIVE: We tested the efficacy of a group-based traditional and multimedia HIV/STI prevention intervention (Project WORTH: Women on the Road to Health among drug-involved women under community supervision. DESIGN, SETTING, PARTICIPANTS, AND INTERVENTION: We randomized 306 women recruited from community supervision settings to receive either: (1 a four-session traditional group-based HIV/STI prevention intervention (traditional WORTH; (2 a four-session multimedia group-based HIV/STI prevention intervention that covered the same content as traditional WORTH but was delivered in a computerized format; or (3 a four-session group-based Wellness Promotion intervention that served as an attention control condition. The study examined whether the traditional or multimedia WORTH intervention was more efficacious in reducing risks when compared to Wellness Promotion; and whether multimedia WORTH was more efficacious in reducing risks when compared to traditional WORTH. MAIN OUTCOMES AND MEASURES: Primary outcomes were assessed over the 12-month post-intervention period and included the number of unprotected sex acts, the proportion of protected sex acts, and consistent condom use. At baseline, 77% of participants reported unprotected vaginal or anal sex (n = 237 and 63% (n = 194 had multiple sex partners. RESULTS: Women assigned to traditional or multimedia WORTH were significantly more likely than women assigned to the control condition to report an increase in the proportion of protected sex acts (β = 0.10; 95% CI = 0.02-0.18 and a decrease in the number of unprotected sex acts (IRR = 0.72; 95% CI = 0.57-0.90. CONCLUSION AND RELEVANCE: The promising effects of traditional and multimedia WORTH on increasing condom use and high participation rates suggest
El-Bassel, Nabila; Gilbert, Louisa; Goddard-Eckrich, Dawn; Chang, Mingway; Wu, Elwin; Hunt, Tim; Epperson, Matt; Shaw, Stacey A; Rowe, Jessica; Almonte, Maria; Witte, Susan
2014-01-01
This study is designed to address the need for evidence-based HIV/STI prevention approaches for drug-involved women under criminal justice community supervision. We tested the efficacy of a group-based traditional and multimedia HIV/STI prevention intervention (Project WORTH: Women on the Road to Health) among drug-involved women under community supervision. We randomized 306 women recruited from community supervision settings to receive either: (1) a four-session traditional group-based HIV/STI prevention intervention (traditional WORTH); (2) a four-session multimedia group-based HIV/STI prevention intervention that covered the same content as traditional WORTH but was delivered in a computerized format; or (3) a four-session group-based Wellness Promotion intervention that served as an attention control condition. The study examined whether the traditional or multimedia WORTH intervention was more efficacious in reducing risks when compared to Wellness Promotion; and whether multimedia WORTH was more efficacious in reducing risks when compared to traditional WORTH. Primary outcomes were assessed over the 12-month post-intervention period and included the number of unprotected sex acts, the proportion of protected sex acts, and consistent condom use. At baseline, 77% of participants reported unprotected vaginal or anal sex (n = 237) and 63% (n = 194) had multiple sex partners. Women assigned to traditional or multimedia WORTH were significantly more likely than women assigned to the control condition to report an increase in the proportion of protected sex acts (β = 0.10; 95% CI = 0.02-0.18) and a decrease in the number of unprotected sex acts (IRR = 0.72; 95% CI = 0.57-0.90). The promising effects of traditional and multimedia WORTH on increasing condom use and high participation rates suggest that WORTH may be scaled up to redress the concentrated epidemics of HIV/STIs among drug-involved women in the criminal justice system. Clinical
de Lacy-Vawdon, Cassandra J; Schwarzman, Joanna; Nolan, Genevieve; de Silva, Renee; Menzies, David; Smith, Ben J
2017-05-22
This review examines program features that influence attendance and adherence to group-based physical activity (PA) by older adults. Medline, PubMed, CINAHL plus, PsycINFO, and the Cochrane Library were searched for studies published from 1995-2016. Quantitative and qualitative studies investigating factors related to PA group attendance or adherence by persons aged 55 years and over, were included. Searching yielded eight quantitative and 13 qualitative studies, from 2044 titles. Quantitative findings identified social factors, instructor characteristics, PA types, class duration and frequency, and perceived PA outcomes as important for attendance and adherence, whilst qualitative studies identified settings, leadership, PA types, observable benefits and social support factors. Studies were predominantly low- to moderate-quality. This review identified design and delivery considerations for group-based PA programs to inform best-practice frameworks and industry capacity-building. Future research should use longitudinal and mixed-methods designs to strengthen evidence about facilitators of program reach and engagement.
Franklin, Jessica M; Shrank, William H; Pakes, Juliana; Sanfélix-Gimeno, Gabriel; Matlin, Olga S; Brennan, Troyen A; Choudhry, Niteesh K
2013-09-01
Classifying medication adherence is important for efficiently targeting adherence improvement interventions. The purpose of this study was to evaluate the use of a novel method, group-based trajectory models, for classifying patients by their long-term adherence. We identified patients who initiated a statin between June 1, 2006 and May 30, 2007 in prescription claims from CVS Caremark and evaluated adherence over the subsequent 15 months. We compared several adherence summary measures, including proportion of days covered (PDC) and trajectory models with 2-6 groups, with the observed adherence pattern, defined by monthly indicators of full adherence (defined as having ≥24 d covered of 30). We also compared the accuracy of adherence prediction based on patient characteristics when adherence was defined by either a trajectory model or PDC. In 264,789 statin initiators, the 6-group trajectory model summarized long-term adherence best (C=0.938), whereas PDC summarized less well (C=0.881). The accuracy of adherence predictions was similar whether adherence was classified by PDC or by trajectory model. Trajectory models summarized adherence patterns better than traditional approaches and were similarly predicted by covariates. Group-based trajectory models may facilitate targeting of interventions and may be useful to adjust for confounding by health-seeking behavior.
Davies, Christopher E; Glonek, Gary Fv; Giles, Lynne C
2017-08-01
One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Group-based trajectory models generally assume a certain structure in the covariances between measurements, for example conditional independence, homogeneous variance between groups or stationary variance over time. Violations of these assumptions could be expected to result in poor model performance. We used simulation to investigate the effect of covariance misspecification on misclassification of trajectories in commonly used models under a range of scenarios. To do this we defined a measure of performance relative to the ideal Bayesian correct classification rate. We found that the more complex models generally performed better over a range of scenarios. In particular, incorrectly specified covariance matrices could significantly bias the results but using models with a correct but more complicated than necessary covariance matrix incurred little cost.
Directory of Open Access Journals (Sweden)
Probidita Roychoudhury
2017-01-01
Full Text Available In view of the exponential growth in the volume of wireless data communication among heterogeneous devices ranging from smart phones to tiny sensors across a wide range of applications, 3GPP LTE-A has standardized Machine Type Communication (MTC which allows communication between entities without any human intervention. The future 5G cellular networks also envisage massive deployment of MTC Devices (MTCDs which will increase the total number of connected devices hundredfold. This poses a huge challenge to the traditional cellular system processes, especially the traditional Mutual Authentication and Key Agreement (AKA mechanism currently used in LTE systems, as the signaling load caused by the increasingly large number of devices may have an adverse effect on the regular Human to Human (H2H traffic. A solution in the literature has been the use of group based architecture which, while addressing the authentication traffic, has their share of issues. This paper introduces Hierarchical Group based Mutual Authentication and Key Agreement (HGMAKA protocol to address those issues and also enables the small cell heterogeneous architecture in line with 5G networks to support MTC services. The aggregate Message Authentication Code based approach has been shown to be lightweight and significantly efficient in terms of resource usage compared to the existing protocols, while being robust to authentication message failures, and scalable to heterogeneous network architectures.
Directory of Open Access Journals (Sweden)
Arfiza Ridwan
2012-08-01
Full Text Available Background: In most countries worldwide, hypertension is considered as an important problem. Moreover, an increasing trend in the prevalence and incidence has been reported in most countries. This increasing trend requires an innovative approach to improve the lifestyle modification of hypertensive sufferers including their dietary behaviors. Objective: This developmental research aims to develop a program for improving the dietary behaviors of community dwellers with hypertension. Method: The process of this program development includes a literature review related to the self-management programs for hypertension, and dietary behavior outcomes, expert validation, and pilot testing. Result: The setting, strategies, duration, and outcome measurement from the literature review were taken into consideration to develop the new program. The newly developed group-based self-management program consists of: 1 the sharing and reflecting of individual current dietary behavior, 2 group educational session, 3 individual comparison of behavior and reflection of obstacles, 4 individual goal setting, and 5 follow up. In the educational session, the DASH eating plan is used as the reference as it is commonly used in studies about diet for hypertension. Key words: hypertension, self-management, group based program, dietary behaviors.
Afrikaner spirituality: A complex mixture
Directory of Open Access Journals (Sweden)
Erna Olivier
2006-10-01
Full Text Available The article argues that the perception that Afrikaner spirituality is and has always been founded mainly or only upon the Calvinistic tradition is a misconception. Nineteenth century Afrikaner spiritualism consisted of a mixture of theology, philosophy and a way of adapting to extreme living conditions. These factors, although with different contents, are also the determinant issues that made 21st century Afrikaner spirituality such a complex phenomenon. The article postulates that the Afrikaner nation’s current identity crisis can be resolved by closely looking at the different influences on the spirituality of the nation and by carefully guiding the people through the complex set of multiple choices to a fresh relation with Christ in a new found Christian identity to confirm our Christian foundation.
Lee, I-Ching; Pratto, Felicia; Johnson, Blair T.
2011-01-01
A meta-analysis examined the extent to which socio-structural and psycho-cultural characteristics of societies correspond with how much gender and ethnic/racial groups differ on their support of group-based hierarchy. Robustly, women opposed group-based hierarchy more than men did, and members of lower power ethnic/racial groups opposed…
Shepherd, L.; Spears, Russell; Manstead, A.S.R.
2013-01-01
In two studies we examined whether and when anticipated group-based shame leads to less ingroup favoritism on the part of members of high-status groups in stable hierarchies. In Study 1 (n = 195) we measured anticipated group-based shame and found that it only negatively predicted ingroup favoritism
Bayesian mixture models for spectral density estimation
Cadonna, Annalisa
2017-01-01
We introduce a novel Bayesian modeling approach to spectral density estimation for multiple time series. Considering first the case of non-stationary timeseries, the log-periodogram of each series is modeled as a mixture of Gaussiandistributions with frequency-dependent weights and mean functions. The implied model for the log-spectral density is a mixture of linear mean functionswith frequency-dependent weights. The mixture weights are built throughsuccessive differences of a logit-normal di...
Thermodynamic Calculations for Complex Chemical Mixtures
Mcbride, B. J.
1986-01-01
General computer program, CECTRP, developed for calculation of thermodynamic properties of complex mixtures with option to calculate transport properties of these mixtures. Free-energy minimization technique used in equilibrium calculation. Rigorous equations used in transport calculations. Program calculates equilibrium compositions and corresponding thermodynamic and transport properties of mixtures. CECTRP accommodates up to 24 reactants, 20 elements, and 600 products, 400 of which are condensed. Written in FORTRAN IV for any large computer system.
Shear viscosity of liquid mixtures Mass dependence
Kaushal, R
2002-01-01
Expressions for zeroth, second, and fourth sum rules of transverse stress autocorrelation function of two component fluid have been derived. These sum rules and Mori's memory function formalism have been used to study shear viscosity of Ar-Kr and isotopic mixtures. It has been found that theoretical result is in good agreement with the computer simulation result for the Ar-Kr mixture. The mass dependence of shear viscosity for different mole fraction shows that deviation from ideal linear model comes even from mass difference in two species of fluid mixture. At higher mass ratio shear viscosity of mixture is not explained by any of the emperical model.
Empirical profile mixture models for phylogenetic reconstruction
National Research Council Canada - National Science Library
Si Quang, Le; Gascuel, Olivier; Lartillot, Nicolas
2008-01-01
Motivation: Previous studies have shown that accounting for site-specific amino acid replacement patterns using mixtures of stationary probability profiles offers a promising approach for improving...
DEFF Research Database (Denmark)
Stenov, Vibeke; Hempler, Nana Folmann; Reventlow, Susanne
2017-01-01
AIM: To investigate approaches among healthcare providers (HCPs) that support or hinder person-centredness in group-based diabetes education programmes targeting persons with type 2 diabetes. METHODS: Ethnographic fieldwork in a municipal and a hospital setting in Denmark. The two programmes incl......-centred approaches in a group context. CONCLUSION: Teacher-centredness undermined person-centredness because HCPs primarily delivered disease-specific recommendations, leading to biomedical information overload for participants....... on delivering disease-specific information. Communication was dialog based, but HCPs primarily asked closed-ended questions with one correct answer. Additional hindering approaches included ignoring participants with suboptimal health behaviours and a tendency to moralize that resulted in feelings of guilt...
Choudhari, Prafulla; Kumbhar, Santosh; Phalle, Siddharth; Choudhari, Sujata; Desai, Sujit; Khare, Shivratna; Jadhav, Swapnil
2017-01-01
To identify the structural requirement for development of lead structures with PPAR gamma binding activity group based quantitative structure activity relationship (GQSAR) studies on 46 reported structures were carried out. The molecules in the current dataset were fragmented into seven functional groups fragments (R1, R2, R3, R4, R5, R6 and R7). GQSAR models were derived using multiple linear regressions analysis. Four generated GQSAR models were selected based on the statistical significance of the model. It was found that the presence of smaller groups on fragment R7 and presence of lipophilic group at fragment R2 was conducive for PPAR gamma binding. Additionally, the existence of hydrogen bond acceptor at fragments R6 was fruitful PPAR gamma binding. The generated models provide a site-specific insight into the structural requirements PPAR γ binding which can be used to design and develop potent antidiabetic compounds.
Group-based and personalized care in an age of genomic and evidence-based medicine: a reappraisal.
Maglo, Koffi N
2012-01-01
This article addresses the philosophical and moral foundations of group-based and individualized therapy in connection with population care equality. The U.S. Food and Drug Administration (FDA) recently modified its public health policy by seeking to enhance the efficacy and equality of care through the approval of group-specific prescriptions and doses for some drugs. In the age of genomics, when individualization of care increasingly has become a major concern, investigating the relationship between population health, stratified medicine, and personalized therapy can improve our understanding of the ethical and biomedical implications of genomic medicine. I suggest that the need to optimize population health through population substructure-sensitive research and the need to individualize care through genetically targeted therapies are not necessarily incompatible. Accordingly, the article reconceptualizes a unified goal for modern scientific medicine in terms of individualized equal care.
Gulliver, Eric A.
The objective of this thesis to identify and develop techniques providing direct comparison between simulated and real packed particle mixture microstructures containing submicron-sized particles. This entailed devising techniques for simulating powder mixtures, producing real mixtures with known powder characteristics, sectioning real mixtures, interrogating mixture cross-sections, evaluating and quantifying the mixture interrogation process and for comparing interrogation results between mixtures. A drop and roll-type particle-packing model was used to generate simulations of random mixtures. The simulated mixtures were then evaluated to establish that they were not segregated and free from gross defects. A powder processing protocol was established to provide real mixtures for direct comparison and for use in evaluating the simulation. The powder processing protocol was designed to minimize differences between measured particle size distributions and the particle size distributions in the mixture. A sectioning technique was developed that was capable of producing distortion free cross-sections of fine scale particulate mixtures. Tessellation analysis was used to interrogate mixture cross sections and statistical quality control charts were used to evaluate different types of tessellation analysis and to establish the importance of differences between simulated and real mixtures. The particle-packing program generated crescent shaped pores below large particles but realistic looking mixture microstructures otherwise. Focused ion beam milling was the only technique capable of sectioning particle compacts in a manner suitable for stereological analysis. Johnson-Mehl and Voronoi tessellation of the same cross-sections produced tessellation tiles with different the-area populations. Control charts analysis showed Johnson-Mehl tessellation measurements are superior to Voronoi tessellation measurements for detecting variations in mixture microstructure, such as altered
Chao, Maria T; Tippens, Kimberly M; Connelly, Erin
2012-06-01
Acupuncture utilization in the United States has increased in recent years, but is less common among racial/ethnic minorities and those of low socioeconomic status. Group-based, community acupuncture is a delivery model gaining in popularity around the United States, due in part to low-cost treatments provided on a sliding-fee scale. Affordable, community-based acupuncture may increase access to health care at a time when increasing numbers of people are uninsured. To assess the population using local community acupuncture clinics, sociodemographic factors, health status, and utilization patterns compared to national acupuncture users were examined. Data were employed from (1) a cross-sectional survey of 478 clients of two community acupuncture clinics in Portland, Oregon and (2) a nationally representative sample of acupuncture users from the 2007 National Health Interview Survey. Portland community acupuncture clients were more homogeneous racially, had higher educational attainment, lower household income, and were more likely to receive 10 or more treatments in the past 12 months (odds ratio=5.39, 95% confidence interval=3.54, 8.22), compared to a nationally representative sample of U.S. acupuncture users. Self-reported health status and medical reasons for seeking acupuncture treatment were similar in both groups. Back pain (21%), joint pain (17%), and depression (13%) were the most common conditions for seeking treatment at community acupuncture clinics. Study findings suggest that local community acupuncture clinics reach individuals of a broad socioeconomic spectrum and may allow for increased frequency of treatment. Limited racial diversity among community acupuncture clients may reflect local demographics of Portland. In addition, exposure to and knowledge about acupuncture is likely to vary by race and ethnicity. Future studies should examine access, patient satisfaction, frequency of treatment, and clinical outcomes of group-based models of community
Thermodynamics of mixtures containing amines
Energy Technology Data Exchange (ETDEWEB)
Gonzalez, Juan Antonio [G.E.T.E.F. Dpto Termodinamica y Fisica Aplicada, Facultad de Ciencias, Universidad de Valladolid, Valladolid 47071 (Spain)], E-mail: jagl@termo.uva.es; Mozo, Ismael; Garcia de la Fuente, Isaias; Cobos, Jose Carlos [G.E.T.E.F. Dpto Termodinamica y Fisica Aplicada, Facultad de Ciencias, Universidad de Valladolid, Valladolid 47071 (Spain); Riesco, Nicolas [Department of Chemical Engineering, Loughborough University, Loughborough, LE113TU Leicestershire (United Kingdom)
2008-01-30
Mixtures with dimethyl or trimethylpyridines and alkane, aromatic compound or 1-alkanol have been examined using different theories: DISQUAC, Flory, the concentration-concentration structure factor, S{sub CC}(0), or the Kirkwood-Buff formalism. DISQUAC represents fairly well the available experimental data, and improves theoretical calculations from Dortmund UNIFAC. Two important effects have been investigated: (i) the effect of increasing the number of methyl groups attached to the aromatic ring of the amine; (ii) the effect of modifying the position of the methyl groups in this ring. The molar excess enthalpy, H{sup E}, and the molar excess volume, V{sup E}, decrease in systems with alkane or methanol as follows: pyridine > 3-methylpyridine > 3,5-dimethylpyridine and pyridine > 2-methylpyridine > 2,4-dimethylpyridine > 2,4,6-trimethylpyridine, which has been attributed to a weakening of the amine-amine interactions in the same sequences. This is in agreement with the relative variation of the effective dipole moment, {mu}-bar, and of the differences between the boiling temperature of a pyridine base and that of the homomorphic alkane. For heptane solutions, the observed H{sup E} variation, H{sup E} (3,5-dimethylpyridine) > H{sup E} (2,4-dimethylpyridine) > H{sup E} (2,6-dimethylpyridine), is explained similarly. Calculations on the basis of the Flory model confirm that orientational effects become weaker in systems with alkane in the order: pyridine > methylpyridine > dimethylpyridine > trimethylpyridine. S{sub CC}(0) calculations show that steric effects increase with the number of CH{sub 3}- groups in the pyridine base, and that the steric effects exerted by methyl groups in positions 2 and 6 are higher than when they are placed in positions 3 and 5. The hydrogen bond energy in methanol mixtures is independent of the pyridine base, and it is estimated to be -35.2 kJ mol{sup -1}. Heterocoordination in these solutions is due in part to size effects. Their
基于生存数据的半参数变换的删失回归估计%Censored Regression in Semiparametric Transformation Models for Survival Data
Institute of Scientific and Technical Information of China (English)
赵晓兵
2006-01-01
生存数据经过未知的单调变换后等于协变量的线性函数加上随机误差,随机误差的分布函数已知或是带未知参数的已知函数.本文先给出未知单调变换的一个相合估计,再对删失数据做变换,在此基础上给出了协变量系数的最小二乘估计,并讨论它的大样本性质.%We consider a class of semi-parametric transformation models, under which an unknown transformation of the survival time is linear related to the covariates with various error distributions, which are parametrically specified with unknown parameters. Estimators of the coefficients of covariates are obtained from linear least squares procedures and the Class-K method with censored observations. We show that the estimators are consistent and asymptotically normal. This transformation model, coupled with proposed inference procedures, provides many alternatives to the Cox models and survival analysis.
Time-dependence in mixture toxicity prediction.
Dawson, Douglas A; Allen, Erin M G; Allen, Joshua L; Baumann, Hannah J; Bensinger, Heather M; Genco, Nicole; Guinn, Daphne; Hull, Michael W; Il'Giovine, Zachary J; Kaminski, Chelsea M; Peyton, Jennifer R; Schultz, T Wayne; Pöch, Gerald
2014-12-04
The value of time-dependent toxicity (TDT) data in predicting mixture toxicity was examined. Single chemical (A and B) and mixture (A+B) toxicity tests using Microtox(®) were conducted with inhibition of bioluminescence (Vibrio fischeri) being quantified after 15, 30 and 45-min of exposure. Single chemical and mixture tests for 25 sham (A1:A2) and 125 true (A:B) combinations had a minimum of seven duplicated concentrations with a duplicated control treatment for each test. Concentration/response (x/y) data were fitted to sigmoid curves using the five-parameter logistic minus one parameter (5PL-1P) function, from which slope, EC25, EC50, EC75, asymmetry, maximum effect, and r(2) values were obtained for each chemical and mixture at each exposure duration. Toxicity data were used to calculate percentage-based TDT values for each individual chemical and mixture of each combination. Predicted TDT values for each mixture were calculated by averaging the TDT values of the individual components and regressed against the observed TDT values obtained in testing, resulting in strong correlations for both sham (r(2)=0.989, n=25) and true mixtures (r(2)=0.944, n=125). Additionally, regression analyses confirmed that observed mixture TDT values calculated for the 50% effect level were somewhat better correlated with predicted mixture TDT values than at the 25 and 75% effect levels. Single chemical and mixture TDT values were classified into five levels in order to discern trends. The results suggested that the ability to predict mixture TDT by averaging the TDT of the single agents was modestly reduced when one agent of the combination had a positive TDT value and the other had a minimal or negative TDT value. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Batterman, Stuart; Su, Feng-Chiao; Li, Shi; Mukherjee, Bhramar; Jia, Chunrong
2014-06-01
affect VOC exposures, many personal, environmental, and socioeconomic determinants remain to be identified, and the significance and applicability of the determinants reported in the literature are uncertain. To help answer these unresolved questions and overcome limitations of previous analyses, this project used several novel and powerful statistical modeling and analysis techniques and two large data sets. The overall objectives of this project were (1) to identify and characterize exposure distributions (including extreme values), (2) evaluate mixtures (including dependencies), and (3) identify determinants of VOC exposure. METHODS VOC data were drawn from two large data sets: the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study (1999-2001) and the National Health and Nutrition Examination Survey (NHANES; 1999-2000). The RIOPA study used a convenience sample to collect outdoor, indoor, and personal exposure measurements in three cities (Elizabeth, NJ; Houston, TX; Los Angeles, CA). In each city, approximately 100 households with adults and children who did not smoke were sampled twice for 18 VOCs. In addition, information about 500 variables associated with exposure was collected. The NHANES used a nationally representative sample and included personal VOC measurements for 851 participants. NHANES sampled 10 VOCs in common with RIOPA. Both studies used similar sampling methods and study periods. Specific Aim 1. To estimate and model extreme value exposures, extreme value distribution models were fitted to the top 10% and 5% of VOC exposures. Health risks were estimated for individual VOCs and for three VOC mixtures. Simulated extreme value data sets, generated for each VOC and for fitted extreme value and lognormal distributions, were compared with measured concentrations (RIOPA observations) to evaluate each model's goodness of fit. Mixture distributions were fitted with the conventional finite mixture of normal distributions and the semi-parametric
Mixture Modeling: Applications in Educational Psychology
Harring, Jeffrey R.; Hodis, Flaviu A.
2016-01-01
Model-based clustering methods, commonly referred to as finite mixture modeling, have been applied to a wide variety of cross-sectional and longitudinal data to account for heterogeneity in population characteristics. In this article, we elucidate 2 such approaches: growth mixture modeling and latent profile analysis. Both techniques are…
Two-microphone Separation of Speech Mixtures
DEFF Research Database (Denmark)
2006-01-01
Matlab source code for underdetermined separation of instaneous speech mixtures. The algorithm is described in [1] Michael Syskind Pedersen, DeLiang Wang, Jan Larsen and Ulrik Kjems: ''Two-microphone Separation of Speech Mixtures,'' 2006, submitted for journal publoication. See also, [2] Michael...
Fibril assembly in whey protein mixtures
Bolder, S.G.
2007-01-01
The objective of this thesis was to study fibril assembly in mixtures of whey proteins. The effect of the composition of the protein mixture on the structures and the resulting phase behaviour was investigated. The current work has shown that beta-lactoglobulin is responsible for the fibril assembly
Supercritical separation process for complex organic mixtures
Chum, Helena L.; Filardo, Giuseppe
1990-01-01
A process is disclosed for separating low molecular weight components from complex aqueous organic mixtures. The process includes preparing a separation solution of supercritical carbon dioxide with an effective amount of an entrainer to modify the solvation power of the supercritical carbon dioxide and extract preselected low molecular weight components. The separation solution is maintained at a temperature of at least about 70.degree. C. and a pressure of at least about 1,500 psi. The separation solution is then contacted with the organic mixtures while maintaining the temperature and pressure as above until the mixtures and solution reach equilibrium to extract the preselected low molecular weight components from the organic mixtures. Finally, the entrainer/extracted components portion of the equilibrium mixture is isolated from the separation solution.
Directory of Open Access Journals (Sweden)
Marit B Rise
Full Text Available BACKGROUND: Disease management is crucial in type 2 diabetes. Diabetes self-management education aims to provide the knowledge necessary to make and maintain lifestyle changes. However, few studies have investigated the processes after such courses. The aim of this study was to investigate how participants make and maintain lifestyle changes after participating in group-based type 2 diabetes self-management education. METHODS: Data was collected through qualitative semi-structured interviews with 23 patients who attended educational group programs in Central Norway. The participants were asked how they had used the advice given and what they had changed after the course. RESULTS: Knowledge was essential for making lifestyle changes following education. Three factors affected whether lifestyle changes were implemented: obtaining new knowledge, taking responsibility, and receiving confirmation of an already healthy lifestyle. Four factors motivated individuals to maintain changes: support from others, experiencing an effect, fear of complications, and the formation of new habits. CONCLUSION: Knowledge was used to make and maintain changes in diet, medication and physical activity. Knowledge also acted as confirmation of an already adequate lifestyle. Knowledge led to no changes if diabetes appeared "not that scary" or if changes appeared too time consuming. Those involved in diabetes education need to be aware of the challenges in convincing asymptomatic patients about the benefits of adherence to self-management behaviour.
Rise, Marit B; Pellerud, Anneli; Rygg, Lisbeth Ø; Steinsbekk, Aslak
2013-01-01
Disease management is crucial in type 2 diabetes. Diabetes self-management education aims to provide the knowledge necessary to make and maintain lifestyle changes. However, few studies have investigated the processes after such courses. The aim of this study was to investigate how participants make and maintain lifestyle changes after participating in group-based type 2 diabetes self-management education. Data was collected through qualitative semi-structured interviews with 23 patients who attended educational group programs in Central Norway. The participants were asked how they had used the advice given and what they had changed after the course. Knowledge was essential for making lifestyle changes following education. Three factors affected whether lifestyle changes were implemented: obtaining new knowledge, taking responsibility, and receiving confirmation of an already healthy lifestyle. Four factors motivated individuals to maintain changes: support from others, experiencing an effect, fear of complications, and the formation of new habits. Knowledge was used to make and maintain changes in diet, medication and physical activity. Knowledge also acted as confirmation of an already adequate lifestyle. Knowledge led to no changes if diabetes appeared "not that scary" or if changes appeared too time consuming. Those involved in diabetes education need to be aware of the challenges in convincing asymptomatic patients about the benefits of adherence to self-management behaviour.
Engström, Anna; Abildsnes, Eirik; Mildestvedt, Thomas
2016-01-01
The health burden related to obesity is rising among children and adolescents along with the general population worldwide. For the individual as well as the society this trend is alarming. Several factors are driving the trend, and the solution seems to be multifaceted because long-lasting treatment alternatives are lacking. This study aims to explore adolescents' and young adults' motivation for attending group-based obesity treatment and social and environmental factors that can facilitate or hinder lifestyle change. In this study, we arranged three focus groups with 17 participants from different obesity treatment programs in the west and south of Norway. The content in these programs differed, but they all used Motivational Interviewing as a teaching method. We conducted a data-driven analysis using systematic text condensation. Self-determination theory has been used as an explanatory framework. We identified four major themes: 1) motivation, 2) body experience and self-image, 3) relationships and sense of belonging, and 4) the road ahead. Many of the participants expressed external motivation to participate but experienced increasing inner motivation and enjoyment during the treatment. Several participants reported negative experiences related to being obese and appreciated group affiliation and sharing experiences with other participants. Motivation may shift during a lifestyle course. Facilitating factors include achieving and experiencing positive outcomes as well as gaining autonomy support from other course participants and friends. Obstacles to change were a widespread obesogenic environment as well as feelings of guilt, little trust in personal achievements and non-supporting friends.
On the mixture model for multiphase flow
Energy Technology Data Exchange (ETDEWEB)
Manninen, M.; Taivassalo, V. [VTT Energy, Espoo (Finland). Nuclear Energy; Kallio, S. [Aabo Akademi, Turku (Finland)
1996-12-31
Numerical flow simulation utilising a full multiphase model is impractical for a suspension possessing wide distributions in the particle size or density. Various approximations are usually made to simplify the computational task. In the simplest approach, the suspension is represented by a homogeneous single-phase system and the influence of the particles is taken into account in the values of the physical properties. This study concentrates on the derivation and closing of the model equations. The validity of the mixture model is also carefully analysed. Starting from the continuity and momentum equations written for each phase in a multiphase system, the field equations for the mixture are derived. The mixture equations largely resemble those for a single-phase flow but are represented in terms of the mixture density and velocity. The volume fraction for each dispersed phase is solved from a phase continuity equation. Various approaches applied in closing the mixture model equations are reviewed. An algebraic equation is derived for the velocity of a dispersed phase relative to the continuous phase. Simplifications made in calculating the relative velocity restrict the applicability of the mixture model to cases in which the particles reach the terminal velocity in a short time period compared to the characteristic time scale of the flow of the mixture. (75 refs.)
Foaming of mixtures of pure hydrocarbons
Robinson, J. V.; Woods, W. W.
1950-01-01
Mixtures of pure liquid hydrocarbons are capable of foaming. Nine hydrocarbons were mixed in pairs, in all possible combinations, and four proportions of each combination. These mixtures were sealed in glass tubes, and the foaming was tested by shaking. Mixtures of aliphatic with other aliphatic hydrocarbons, or of alkyl benzenes with other alkyl benzenes, did not foam. Mixtures of aliphatic hydrocarbons with alkyl benzenes did foam. The proportions of the mixtures greatly affected the foaming, the maximum foaming of 12 of 20 pairs being at the composition 20 percent aliphatic hydrocarbon, 80 percent alkyl benzene. Six seconds was the maximum foam lifetime of any of these mixtures. Aeroshell 120 lubricating oil was fractionated into 52 fractions and a residue by extraction with acetone in a fractionating extractor. The index of refraction, foam lifetime, color, and viscosity of these fractions were measured. Low viscosity and high index fractions were extracted first. The viscosity of the fractions extracted rose and the index decreased as fractionation proceeded. Foam lifetimes and color were lowest in the middle fractions. Significance is attached to the observation that none of the foam lifetimes of the fractions or residue is as high as the foam lifetime of the original Aeroshell, indicating that the foaming is not due to a particular foaming constituent, but rather to the entire mixture.
Coking technology using packed coal mixtures
Energy Technology Data Exchange (ETDEWEB)
Kuznichenko, V.M.; Shteinberg, Eh.A.; Tolstoi, A.P. (Khar' kovskii Nauchno-Issledovatel' skii Uglekhimicheskii Institut, Kharkov (Ukrainian SSR))
1991-08-01
Discusses coking of packed coal charges in the FRG, USSR, France, India, Poland and Czechoslovakia. The following aspects are evaluated: types of weakly caking coals that are used as components of packed mixtures, energy consumption of packing, effects of coal mixture packing on coke oven design, number of coke ovens in a battery, heating temperature, coking time, coke properties, investment and operating cost. Statistical data that characterize the Saarberg packing process used in the FRG are analyzed. Packing coal mixtures for coking improves coke quality and reduces environmental pollution. 4 refs.
Directory of Open Access Journals (Sweden)
Juliana Fernandes
2016-02-01
Full Text Available The bordeaux mixture is used as a natural agricultural fungicide, and its application in sericulture can benefit the production of silkworm cocoons, Bombyx mori (Lepidoptera: Bombycidae. The aim of this study was to verify whether the bordeaux mixture exerts a protective effect in B. mori against fungal and viral diseases. This experiment was performed during two seasons, autumn and spring, in which 7,500 caterpillars were used at the beginning of the third instar and divided into five groups, with three repetitions of 500 individuals each. In the three groups, the caterpillars were fed leaves of Mulberry (Morus spp. that were enriched with an aqueous bordeaux mixture solution at concentrations of 5, 10 and 20%. One group was fed exclusively mulberry leaves (control, and another was fed leaves that were moistened with water. Fungal contamination was evaluated in the integumentary surface of the insect and the mulberry leaves in the bed of creation by checking the number of colony-forming units (CFU. In the analysis of viral contamination, 20 caterpillars from each group at the beginning of the fifth instar were inoculated with 10 ?l of a suspension of Bombyx mori nucleopolyhedrovirus (BmNPV. Daily, from the second to the ninth day after inoculation (dai, two caterpillars of each group were anesthetized and formalin-fixed 7% for microscopic processing and viral cytopathology analysis. A completely randomized design was used, and the CFU were compared by Tukey test with 5% significance. The results showed a decrease of 55.1% in CFU present on the mulberry leaves in the fall, when the 5% bordeaux mixture solution was used. There was no significant difference between the groups based on the bordeaux mixture in this period. During the same period, reductions of CFU of 28.5, 74.9 and 74.4% were verified in the integument of B. mori when bordeaux mixture solutions of 5, 10 and 20% were used, respectively, compared with the data that were obtained in
Willner, Paul; Rose, John; Jahoda, Andrew; Kroese, Biza Stenfert; Felce, David; Cohen, David; Macmahon, Pamela; Stimpson, Aimee; Rose, Nicola; Gillespie, David; Shead, Jennifer; Lammie, Claire; Woodgate, Christopher; Townson, Julia; Nuttall, Jacqueline; Hood, Kerenza
2013-09-01
Many people with intellectual disabilities find it hard to control their anger and this often leads to aggression which can have serious consequences, such as exclusion from mainstream services and the need for potentially more expensive emergency placements. To evaluate the effectiveness of a cognitive-behavioural therapy (CBT) intervention for anger management in people with intellectual disabilities. A cluster-randomised trial of group-based 12-week CBT, which took place in day services for people with intellectual disabilities and was delivered by care staff using a treatment manual. Participants were 179 service users identified as having problems with anger control randomly assigned to either anger management or treatment as usual. Assessments were conducted before the intervention, and at 16 weeks and 10 months after randomisation (trial registration: ISRCTN37509773). The intervention had only a small, and non-significant, effect on participants' reports of anger on the Provocation Index, the primary outcome measure (mean difference 2.8, 95% CI -1.7 to 7.4 at 10 months). However, keyworker Provocation Index ratings were significantly lower in both follow-up assessments, as were service-user ratings on another self-report anger measure based on personally salient triggers. Both service users and their keyworkers reported greater usage of anger coping skills at both follow-up assessments and keyworkers and home carers reported lower levels of challenging behaviour. The intervention was effective in improving anger control by people with intellectual disabilities. It provides evidence of the effectiveness of a CBT intervention for this client group and demonstrates that the staff who work with them can be trained and supervised to deliver such an intervention with reasonable fidelity.
Baranoff, John A; Hanrahan, Stephanie J; Burke, Anne L J; Connor, Jason P
2016-02-01
Acceptance and commitment therapy has shown to be effective in chronic pain rehabilitation, and acceptance has been shown to be a key process of change. The influence of treatment dose on acceptance is not clear, and in particular, the effectiveness of a non-intensive treatment (acceptance and commitment therapy (ACT) group program for chronic pain. The study sought to compare, at both groups and individual patient levels, changes in acceptance with changes observed in previous ACT studies. Seventy-one individuals with chronic pain commenced a 9-week ACT-based group program at an outpatient chronic pain service. In addition to acceptance, outcomes included the following: pain catastrophizing, depression, anxiety, quality of life, and pain-related anxiety. To compare the current findings with previous research, effect sizes from seven studies were aggregated using the random-effects model to calculate benchmarks. Reliable change indices (RCIs) were applied to assess change on an individual patient-level. The ACT intervention achieved a statistically significant increase in acceptance and medium effect size (d = 0.54) at a group level. Change in acceptance was of a similar magnitude to that found in previous ACT studies that examined interventions with similar treatment hours (acceptance occurred in approximately one-third (37.2, 90% CI) of patients. Approximately three-quarters (74.3, 90% CI) demonstrated reliable change in at least one of the outcome measures. The low-intensity, group-based ACT intervention was effective at a group level and showed a similar magnitude of change in acceptance to previous ACT studies employing low-intensity interventions. Three-quarters of patients reported reliable change on at least one outcome measure.
Buch, Martin Sandberg; Edwards, Adrian; Eriksson, Tina
2009-01-01
The Maturity Matrix is a group-based formative self-evaluation tool aimed at assessing the degree of organisational development in general practice and providing a starting point for local quality improvement. Earlier studies of the Maturity Matrix have shown that participants find the method a useful way of assessing their practice's organisational development. However, little is known about participants' views on the resulting efforts to implement intended changes. To explore users' perspectives on the Maturity Matrix method, the facilitation process, and drivers and barriers for implementation of intended changes. Observation of two facilitated practice meetings, 17 semi-structured interviews with participating general practitioners (GPs) or their staff, and mapping of reasons for continuing or quitting the project. General practices in Denmark Main outcomes: Successful change was associated with: a clearly identified anchor person within the practice, a shared and regular meeting structure, and an external facilitator who provides support and counselling during the implementation process. Failure to implement change was associated with: a high patient-related workload, staff or GP turnover (that seemed to affect small practices more), no clearly identified anchor person or anchor persons who did not do anything, no continuous support from an external facilitator, and no formal commitment to working with agreed changes. Future attempts to improve the impact of the Maturity Matrix, and similar tools for quality improvement, could include: (a) attention to matters of variation caused by practice size, (b) systematic counselling on barriers to implementation and support to structure the change processes, (c) a commitment from participants that goes beyond participation in two-yearly assessments, and (d) an anchor person for each identified goal who takes on the responsibility for improvement in practice.
Xu, Xiaofeng; Elias, Dwayne A.; Graham, David E.; Phelps, Tommy J.; Carroll, Sue L.; Wullschleger, Stan D.; Thornton, Peter E.
2015-07-01
Accurately estimating methane (CH4) flux in terrestrial ecosystems is critically important for investigating and predicting biogeochemistry-climate feedbacks. Improved simulations of CH4 flux require explicit representations of the microbial processes that account for CH4 dynamics. A microbial functional group-based module was developed, building on the decomposition subroutine of the Community Land Model 4.5. This module considers four key mechanisms for CH4 production and consumption: methanogenesis from acetate or from single-carbon compounds and CH4 oxidation using molecular oxygen or other inorganic electron acceptors. Four microbial functional groups perform these processes: acetoclastic methanogens, hydrogenotrophic methanogens, aerobic methanotrophs, and anaerobic methanotrophs. This module was used to simulate dynamics of carbon dioxide (CO2) and CH4 concentrations from an incubation experiment with permafrost soils. The results show that the model captures the dynamics of CO2 and CH4 concentrations in microcosms with top soils, mineral layer soils, and permafrost soils under natural and saturated moisture conditions and three temperature conditions of -2°C, 3°C, and 5°C (R2 > 0.67 P temperature conditions. Sensitivity analysis confirmed the importance of acetic acid's direct contribution as substrate and indirect effects through pH feedback on CO2 and CH4 production and consumption. This study suggests that representing the microbial mechanisms is critical for modeling CH4 production and consumption; it is urgent to incorporate microbial mechanisms into Earth system models for better predicting trace gas dynamics and the behavior of the climate system.
Quantiles for Finite Mixtures of Normal Distributions
Rahman, Mezbahur; Rahman, Rumanur; Pearson, Larry M.
2006-01-01
Quantiles for finite mixtures of normal distributions are computed. The difference between a linear combination of independent normal random variables and a linear combination of independent normal densities is emphasized. (Contains 3 tables and 1 figure.)
A mixture theory for geophysical fluids
Directory of Open Access Journals (Sweden)
A. C. Eringen
2004-01-01
Full Text Available A continuum theory is developed for a geophysical fluid consisting of two species. Balance laws are given for the individual components of the mixture, modeled as micropolar viscous fluids. The continua allow independent rotational degrees of freedom, so that the fluids can exhibit couple stresses and a non-symmetric stress tensor. The second law of thermodynamics is used to develop constitutive equations. Linear constitutive equations are constituted for a heat conducting mixture, each species possessing separate viscosities. Field equations are obtained and boundary and initial conditions are stated. This theory is relevant to an atmospheric mixture consisting of any two species from rain, snow and/or sand. Also, this is a continuum theory for oceanic mixtures, such as water and silt, or water and oil spills, etc.
The disentangling number for phylogenetic mixtures
Sullivant, Seth
2011-01-01
We provide a logarithmic upper bound for the disentangling number on unordered lists of leaf labeled trees. This results is useful for analyzing phylogenetic mixture models. The proof depends on interpreting multisets of trees as high dimensional contingency tables.
Mapping the jamming transition of bidisperse mixtures
Koeze, D. J.; Vågberg, D.; Tjoa, B. B. T.; Tighe, B. P.
2016-03-01
We systematically map out the jamming transition of all 2D bidisperse mixtures of frictionless disks in the hard-particle limit. The critical volume fraction, mean coordination number, number of rattlers, structural order parameters, and bulk modulus each show a rich variation with mixture composition and particle size ratio, and can therefore be tuned by choosing certain mixtures. We identify two local minima in the critical volume fraction, both of which have low structural order; one minimum is close to the widely studied 50 : 50 mixture of particles with a ratio of radii of 1 : 1.4. We also identify a region at low size ratios characterized by increased structural order and high rattler fractions, with a corresponding enhancement in the stiffness.
Ultrafiltration of a polymer-electrolyte mixture
Vonk, P; Noordman, T.R; Schippers, D; Tilstra, B; Wesselingh, J.A
1997-01-01
We present a mathematical model to describe the ultrafiltration behaviour of polymer-electrolyte mixtures. The model combines the proper thermodynamic forces (pressure, chemical potential and electrical potential differences) with multicomponent diffusion theory. The model is verified with experimen
Model structure selection in convolutive mixtures
DEFF Research Database (Denmark)
Dyrholm, Mads; Makeig, Scott; Hansen, Lars Kai
2006-01-01
The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimoneous represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimoneous...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: 'Are we actually dealing with a convolutive mixture?'. We try to answer this question for EEG data....
Model structure selection in convolutive mixtures
DEFF Research Database (Denmark)
Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai
2006-01-01
The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data....
Laboratory performance of asphalt rubber mixtures
Fontes, Liseane; Trichês, Glicério; Pais, Jorge; Pereira, Paulo; Minhoto, Manuel
2009-01-01
Asphalt rubber mixtures are one of the most promising techniques to extend the service life of asphalt pavement overlays. Asphalt rubber binder is composed of crumb rubber from reclaimed tires and conventional asphalt. The asphalt rubber binder can be obtained through wet process in two different systems: tire rubber modified asphalt binder (produced at industrial plants) and continuous blending (produced in asphalt plants). This study presents a laboratory evaluation of asphalt rubber mixtur...
Assessing sanitary mixtures in East African cities
Letema, S.C.
2012-01-01
The urbanisation of poverty and informality in East African cities poses a threat to environmental health, perpetuates social exclusion and inequalities, and creates service gaps (UN-Habitat, 2008). This makes conventional sanitation provision untenable citywide, giving rise to the emergence of sanitation mixtures. Sanitation mixtures have different scales, institutional arrangements, user groups, and rationalities for their establishment, location, and management. For assessing the performan...
Fitting mixture distributions to phenylthiocarbamide (PTC) sensitivity.
Jones, P N; G.J. McLachlan
1991-01-01
A technique for fitting mixture distributions to phenylthiocarbamide (PTC) sensitivity is described. Under the assumptions of Hardy-Weinberg equilibrium, a mixture of three normal components is postulated for the observed distribution, with the mixing parameters corresponding to the proportions of the three genotypes associated with two alleles A and a acting at a single locus. The corresponding genotypes AA, Aa, and aa are then considered to have separate means and variances. This paper is c...
Institute of Scientific and Technical Information of China (English)
侯文; 宋立新; 黄玉洁
2012-01-01
考察了响应变量在随机删失情形下的非线性半参数回归模型,构造了未知参数的经验对数似然比统计量和调整经验对数似然比统计量,证明在一定条件下,所构造的经验似然比统计量渐近于x2分布,并由此构造出未知参数的置信域.此外,又构造了未知参数的最小二乘估计量,证明了它的渐近性质.通过模拟研究表明,经验似然方法在置信域的覆盖概率以及精度方面要优于最小二乘法.%In this paper, a censored nonlinear semiparametric regression model is investigated. Empirical log-likelihood ratio statistics and adjust empirical log-likelihood ratio statistics for the unknown parameters in the model are suggested. It is shown that the proposed statistics have asymptotically chi-squared distribution under some mild conditions, and hence it can be used to construct the confidence region of the unknown parameter. In addition the least squares estimator of unknown parameter is constructed, and its asymptotic behavior is proved. A simulation study is carried out to show the empirical likelihood methods appears to be better than the least-squares method in terms of the confidence regions and its coverage probabilities.
Durmaz, Murat; Karslioglu, Mahmut Onur
2015-04-01
There are various global and regional methods that have been proposed for the modeling of ionospheric vertical total electron content (VTEC). Global distribution of VTEC is usually modeled by spherical harmonic expansions, while tensor products of compactly supported univariate B-splines can be used for regional modeling. In these empirical parametric models, the coefficients of the basis functions as well as differential code biases (DCBs) of satellites and receivers can be treated as unknown parameters which can be estimated from geometry-free linear combinations of global positioning system observables. In this work we propose a new semi-parametric multivariate adaptive regression B-splines (SP-BMARS) method for the regional modeling of VTEC together with satellite and receiver DCBs, where the parametric part of the model is related to the DCBs as fixed parameters and the non-parametric part adaptively models the spatio-temporal distribution of VTEC. The latter is based on multivariate adaptive regression B-splines which is a non-parametric modeling technique making use of compactly supported B-spline basis functions that are generated from the observations automatically. This algorithm takes advantage of an adaptive scale-by-scale model building strategy that searches for best-fitting B-splines to the data at each scale. The VTEC maps generated from the proposed method are compared numerically and visually with the global ionosphere maps (GIMs) which are provided by the Center for Orbit Determination in Europe (CODE). The VTEC values from SP-BMARS and CODE GIMs are also compared with VTEC values obtained through calibration using local ionospheric model. The estimated satellite and receiver DCBs from the SP-BMARS model are compared with the CODE distributed DCBs. The results show that the SP-BMARS algorithm can be used to estimate satellite and receiver DCBs while adaptively and flexibly modeling the daily regional VTEC.
Using Big Data Analytics to Address Mixtures Exposure
The assessment of chemical mixtures is a complex issue for regulators and health scientists. We propose that assessing chemical co-occurrence patterns and prevalence rates is a relatively simple yet powerful approach in characterizing environmental mixtures and mixtures exposure...
Catalyst mixture for aromatic hydrocarbon synthesis
Energy Technology Data Exchange (ETDEWEB)
Minderhoud, J.K.; Huizinga, T.; Sie, S.T.
1989-06-06
The present invention is concerned with catalyst mixtures consisting of two catalysts, characterized in that one, which is based on zinc, is capable of catalysing the conversion of a H/sub 2//CO mixture into oxygen-containing organic compounds, and the other is a crystalline iron/boron silicate which, after one hour's calcination in air at 500/sup 0/C, has the following properties: a certain X-ray powder diffraction pattern and, in the formula that represents the composition of the silicate, expressed in moles of the oxides, a SiO/sub 2//Fe/sub 2/O/sub 3 molar ratio that is 20-2000, a SiO/sub 2//B/sub 2/O/sub 3/ molar ratio 50-5000, and a Fe/sub 2/O/sub 3//B/sub 2/O/sub 3/ molar ratio higher than 1.0. Said catalyst mixtures show higher aromatics selectivity in the preparation of hydrocarbon mixtures from H/sub 2//CO mixtures than such a mixture comprising an iron silicate instead of the above iron/boron silicates. 3 tabs.
Homogeneous cooling of mixtures of particle shapes
Hidalgo, R. C.; Serero, D.; Pöschel, T.
2016-07-01
In this work, we examine theoretically the cooling dynamics of binary mixtures of spheres and rods. To this end, we introduce a generalized mean field analytical theory, which describes the free cooling behavior of the mixture. The relevant characteristic time scale for the cooling process is derived, depending on the mixture composition and the aspect ratio of the rods. We simulate mixtures of spherocylinders and spheres using a molecular dynamics algorithm implemented on graphics processing unit (GPU) architecture. We systematically study mixtures composed of spheres and rods with several aspect ratios and varying the mixture composition. A homogeneous cooling state, where the time dependence of the system's intensive variables occurs only through a global granular temperature, is identified. We find cooling dynamics in excellent agreement with Haff's law, when using an adequate time scale. Using the scaling properties of the homogeneous cooling dynamics, we estimated numerically the efficiency of the energy interchange between rotational and translational degrees of freedom for collisions between spheres and rods.
When mixtures of hard-sphere-like colloids do not behave as mixtures of hard spheres.
Germain, Ph; Malherbe, J G; Amokrane, S
2004-10-01
The validity of the concept of "hard-sphere-like" particles for mixtures of colloids is questioned from a theoretical point of view. This concerns the class of pseudobinary mixtures in which the nonsteric interactions between the colloids are "residual" (with very small range and moderate strength). It is shown that contrary to common expectation, such interactions may have unexpected consequences on the theoretical phase diagram. The distinction between this situation and true solute-solvent mixtures is emphasized.
Directory of Open Access Journals (Sweden)
Sadiya A
2016-03-01
Full Text Available Amena Sadiya,1,* Sarah Abdi,1,* Salah Abusnana2 1Lifestyle Clinic, 2Research and Education Department, Rashid Center for Diabetes and Research, Ajman, United Arab Emirates *These authors contributed equally to this work Background: Lifestyle Intervention for Weight Loss (LIFE-8 is developed as a structured, group-based weight management program for Emiratis with obesity and type 2 diabetes. It is a 3-month program followed by a 1-year follow-up. The results from the first 2 years are presented here to indicate the possibility of its further adaptation and implementation in this region. Methodology: We recruited 45 participants with obesity and/or type 2 diabetes based on inclusion/exclusion criteria. The LIFE-8 program was executed by incorporating dietary modification, physical activity, and behavioral therapy, aiming to achieve up to 5% weight loss. The outcomes included body weight, fat mass, waist circumference, blood pressure, fasting blood glucose (FBG, hemoglobin A1c (HbA1c, and nutritional knowledge at 3 months and 12 months. Results: We observed a reduction of 5.0% in body weight (4.8±2.8 kg; 95% CI 3.7–5.8, fat mass (–7.8%, P<0.01, and waist circumference (Δ=4±4 cm, P<0.01 in the completed participants (n=28. An improvement (P<0.05 in HbA1c (7.1%±1.0% vs 6.6%±0.7% and FBG (8.2±2.0 mmol/L vs 6.8±0.8 mmol/L was observed in participants with obesity and type 2 diabetes after the program. Increase in nutritional knowledge (<0.01 and overall evaluation of the program (9/10 was favorable. On 1-year follow-up, we found that the participants could sustain weight loss (–4.0%, while obese, type 2 diabetic participants sustained HbA1c (6.6%±0.7% vs 6.4%±0.7% and further improved (P<0.05 the level of FBG (6.8±0.8 mmol/L vs 6.7±0.4 mmol/L. Conclusion: LIFE-8 could be an effective, affordable, acceptable, and adaptable lifestyle intervention program for the prevention and management of diabetes in Emiratis. It was successful not
Soon, Villu; Saarma, Urmas
2011-07-01
The ignita species group within the genus Chrysis includes over 100 cuckoo wasp species, which all lead a parasitic lifestyle and exhibit very similar morphology. The lack of robust, diagnostic morphological characters has hindered phylogenetic reconstructions and contributed to frequent misidentification and inconsistent interpretations of species in this group. Therefore, molecular phylogenetic analysis is the most suitable approach for resolving the phylogeny and taxonomy of this group. We present a well-resolved phylogeny of the Chrysis ignita species group based on mitochondrial sequence data from 41 ingroup and six outgroup taxa. Although our emphasis was on European taxa, we included samples from most of the distribution range of the C. ignita species group to test for monophyly. We used a continuous mitochondrial DNA sequence consisting of 16S rRNA, tRNA(Val), 12S rRNA and ND4. The location of the ND4 gene at the 3' end of this continuous sequence, following 12S rRNA, represents a novel mitochondrial gene arrangement for insects. Due to difficulties in aligning rRNA genes, two different Bayesian approaches were employed to reconstruct phylogeny: (1) using a reduced data matrix including only those positions that could be aligned with confidence; or (2) using the full sequence dataset while estimating alignment and phylogeny simultaneously. In addition maximum-parsimony and maximum-likelihood analyses were performed to test the robustness of the Bayesian approaches. Although all approaches yielded trees with similar topology, considerably more nodes were resolved with analyses using the full data matrix. Phylogenetic analysis supported the monophyly of the C. ignita species group and divided its species into well-supported clades. The resultant phylogeny was only partly in accordance with published subgroupings based on morphology. Our results suggest that several taxa currently treated as subspecies or names treated as synonyms may in fact constitute
Directory of Open Access Journals (Sweden)
Yoshio Nakata
2014-11-01
Full Text Available Objective: Our previous study, a 6-month randomised controlled trial, demonstrated that a group-based support promoted weight loss as compared to an education-only intervention. The purpose of this study was to examine weight loss maintenance for 2 years. Methods: Originally, 188 overweight Japanese adults, aged 40-65 years, were randomly assigned to 3 groups: control, education-only or group-based support. After the 6-month intervention, 125 participants in the education-only and the group-based support groups were followed up for 2 years. The primary outcome was the amount of weight lost. The participants were retrospectively grouped into quartiles of percent weight loss for secondary analyses. Results: At the end of follow-up, the amount of weight lost in the education-only and the group-based support groups was the same (3.3 kg. Secondary analyses using data of those who completed the study (n = 100 revealed that the participants in the highest quartile of percent weight loss significantly increased their step counts and moderate-to-vigorous physical activity compared with the lowest quartile. No significant differences were observed in the energy intake among the four groups. Conclusion: The effects of group-based support disappear within 2 years. Increasing physical activity may be a crucial factor for successful maintenance of weight loss.
Directory of Open Access Journals (Sweden)
Sven Zebel
2010-05-01
Full Text Available An examination of potential outgroup-focused predictors of group-based guilt relating to past colonial conflicts involving Portugal and the Netherlands, specifically, the role of the perceptions of the ingroup towards the victimized outgroup, as well as on outgroup identification and meta-perceptions (i.e. the ingroup's beliefs regarding the outgroup's perceptions of it. Using Structural Equation Modeling in a Portuguese sample (N = 178 and a Dutch sample (N = 157, we found that the experience of group-based guilt due to colonial conflicts can be positively predicted by outgroup perceptions and outgroup identification (Dutch sample only. Meta-perceptions were a negative predictor of group-based guilt (Dutch sample only. Furthermore, our results show that group-based guilt is positively associated with compensatory behavioral intentions and perceived importance of remembering past colonial conflicts. Results point to the important role of outgroup-focused variables in shaping group-based guilt experiences relating to past conflicts between groups. The findings suggest possible avenues of further research and ways to improve intergroup relations following conflict.
Institute of Scientific and Technical Information of China (English)
CHEN Xiaona; SURongguo; BAIYing; SHI Xiaoyong; YANG Rujun
2014-01-01
An in vivo three-dimensional fluorescence method for the determination of algae community structure was developed by parallel factor analysis (PARAFAC) and CHEMTAX. The PARAFAC model was applied to fluo-rescence excitation-emission matrix (EEM) of 60 algae species belonging to five divisions and 11 fluorescent components were identified according to the residual sum of squares and specificity of the composition profiles of fluorescent. By the 11 fluorescent components, the algae species at different growth stages were classified correctly at the division level using Bayesian discriminant analysis (BDA). Then the reference fluo-rescent component ratio matrix was constructed for CHEMTAX, and the EEM–PARAFAC–CHEMTAX method was developed to differentiate algae taxonomic groups. The correct discrimination ratios (CDRs) when the fluorometric method was used for single-species samples were 100% at the division level, except for Bacil-lariophyta with a CDR of 95.6%. The CDRs for the mixtures were above 94.0% for the dominant algae species and above 87.0% for the subdominant algae species. However, the CDRs of the subdominant algae species were too low to be unreliable when the relative abundance estimated was less than 15.0%. The fluorometric method was tested using the samples from the Jiaozhou Bay and the mesocosm experiments in the Xiaomai Island Bay in August 2007. The discrimination results of the dominant algae groups agreed with microscopy cell counts, as well as the subdominant algae groups of which the estimated relative abundance was above 15.0%. This technique would be of great aid when low-cost and rapid analysis is needed for samples in a large batch. The fluorometric technique has the ability to correctly identify dominant species with proper abundance both in vivo and in situ.
Shirazi, Mohammadali; Lord, Dominique; Dhavala, Soma Sekhar; Geedipally, Srinivas Reddy
2016-06-01
Crash data can often be characterized by over-dispersion, heavy (long) tail and many observations with the value zero. Over the last few years, a small number of researchers have started developing and applying novel and innovative multi-parameter models to analyze such data. These multi-parameter models have been proposed for overcoming the limitations of the traditional negative binomial (NB) model, which cannot handle this kind of data efficiently. The research documented in this paper continues the work related to multi-parameter models. The objective of this paper is to document the development and application of a flexible NB generalized linear model with randomly distributed mixed effects characterized by the Dirichlet process (NB-DP) to model crash data. The objective of the study was accomplished using two datasets. The new model was compared to the NB and the recently introduced model based on the mixture of the NB and Lindley (NB-L) distributions. Overall, the research study shows that the NB-DP model offers a better performance than the NB model once data are over-dispersed and have a heavy tail. The NB-DP performed better than the NB-L when the dataset has a heavy tail, but a smaller percentage of zeros. However, both models performed similarly when the dataset contained a large amount of zeros. In addition to a greater flexibility, the NB-DP provides a clustering by-product that allows the safety analyst to better understand the characteristics of the data, such as the identification of outliers and sources of dispersion.
Identifiability of large phylogenetic mixture models.
Rhodes, John A; Sullivant, Seth
2012-01-01
Phylogenetic mixture models are statistical models of character evolution allowing for heterogeneity. Each of the classes in some unknown partition of the characters may evolve by different processes, or even along different trees. Such models are of increasing interest for data analysis, as they can capture the variety of evolutionary processes that may be occurring across long sequences of DNA or proteins. The fundamental question of whether parameters of such a model are identifiable is difficult to address, due to the complexity of the parameterization. Identifiability is, however, essential to their use for statistical inference.We analyze mixture models on large trees, with many mixture components, showing that both numerical and tree parameters are indeed identifiable in these models when all trees are the same. This provides a theoretical justification for some current empirical studies, and indicates that extensions to even more mixture components should be theoretically well behaved. We also extend our results to certain mixtures on different trees, using the same algebraic techniques.
Relativistic mixtures of charged and uncharged particles
Energy Technology Data Exchange (ETDEWEB)
Kremer, Gilberto M. [Departamento de Física, Universidade Federal do Paraná, Curitiba (Brazil)
2014-01-14
Mixtures of relativistic gases within the framework of Boltzmann equation are analyzed. Three systems are considered. The first one refers to a mixture of uncharged particles by using Grad’s moment method, where the relativistic mixture is characterized by the moments of the distribution functions: particle four-flows, energy-momentum tensors, and third-order moment tensors. In the second Fick’s law for a mixture of relativistic gases of non-disparate rest masses in a Schwarzschild metric are derived from an extension of Marle and McCormack model equations applied to a relativistic truncated Grad’s distribution function, where it is shown the dependence of the diffusion coefficient on the gravitational potential. The third one consists in the derivation of the relativistic laws of Ohm and Fourier for a binary mixtures of electrons with protons and electrons with photons subjected to external electromagnetic fields and in presence of gravitational fields by using the Anderson and Witting model of the Boltzmann equation.
Microsiemens or Milligrams: Measures of Ionic Mixtures ...
In December of 2016, EPA released the Draft Field-Based Methods for Developing Aquatic Life Criteria for Specific Conductivity for public comment. Once final, states and authorized tribes may use these methods to derive field-based ecoregional ambient Aquatic Life Ambient Water Quality Criteria (AWQC) for specific conductivity (SC) in flowing waters. The methods provide flexible approaches for developing science-based SC criteria that reflect ecoregional or state specific factors. The concentration of a dissolved salt mixture can be measured in a number of ways including measurement of total dissolved solids, freezing point depression, refractive index, density, or the sum of the concentrations of individually measured ions. For the draft method, SC was selected as the measure because SC is a measure of all ions in the mixture; the measurement technology is fast, inexpensive, and accurate, and it measures only dissolved ions. When developing water quality criteria for major ions, some stakeholders may prefer to identify the ionic constituents as a measure of exposure instead of SC. A field-based method was used to derive example chronic and acute water quality criteria for SC and two anions a common mixture of ions (bicarbonate plus sulfate, [HCO3−] + [SO42−] in mg/L) that represent common mixtures in streams. These two anions are sufficient to model the ion mixture and SC (R2 = 0.94). Using [HCO3−] + [SO42−] does not imply that these two anions are the
ASPECTS OF THERMODYNAMICS OF POLYMER MIXTURES
Institute of Scientific and Technical Information of China (English)
CHAI Zhikuan
1987-01-01
In this brief review article some aspects of the thermodynamics of polymer mixtures are discussed,mainly based on the author's research. The studies of poly (methyl methacrylate)/chlorinated polyethylene (CPE), poly (butyl acrylate)/CPE and CPE/CPE (different chlorine content) mixture verify the "dissimilarity" and "similarity" principles for predicting miscibility of polymer mixtures. The sign of heat of mixing of oligomeric analogues is not sufficient in predicting the miscibility. The Flory equation of state theory has been applied to simulate the phase boundaries of polymer mixtures. The empirical entropy parameter Q12 plays an important role in the calculation, this reduces the usefulness of the theory. With energy parameter X12 ≠ 0 and Q12 ≠ 0 the spinodals so calculated are reasonable compared to experiments.A hole model was suggested for the statistics of polymer mixtures. The new hole theory combines the features of both the Flory equation of state theory and the Sanchez lattice fluid theory and can be reduced to them under some conditions.
A constitutive theory of reacting electrolyte mixtures
Costa Reis, Martina; Wang, Yongqi; Bono Maurizio Sacchi Bassi, Adalberto
2013-11-01
A constitutive theory of reacting electrolyte mixtures is formulated. The intermolecular interactions among the constituents of the mixture are accounted for through additional freedom degrees to each constituent of the mixture. Balance equations for polar reacting continuum mixtures are accordingly formulated and a proper set of constitutive equations is derived with basis in the Müller-Liu formulation of the second law of thermodynamics. Moreover, the non-equilibrium and equilibrium responses of the reacting mixture are investigated in detail by emphasizing the inner and reactive structures of the medium. From the balance laws and constitutive relations, the effects of molecular structure of constituents upon the fluid flow are studied. It is also demonstrated that the local thermodynamic equilibrium state can be reached without imposing that the set of independent constitutive variables is time independent, neither spatially homogeneous nor null. The resulting constitutive relations presented throughout this work are of relevance to many practical applications, such as swelling of clays, developing of bio and polymeric membranes, and use of electrorheological fluids in industrial processes. The first author acknowledges financial support from National Counsel of Technological and Scientific Development (CNPq) and German Academic Exchange Service (DAAD).
Asbestos Tailings as Aggregates for Asphalt Mixture
Institute of Scientific and Technical Information of China (English)
LIU Xinoming; XU Linrong
2011-01-01
To use many asbestos tailings collected in Ya-Lu highway, and to explore the feasibility of using asbestos tailings as aggregates in common asphalt mixtures, and properties of some asphalt mixtures were evaluated as well. X-ray diffraction (XRD), X-ray fluorescent (XRF), and atomic absorption spectrophotometry (AAS) were employed to determine the solid waste content of copper, zinc, lead, and cadmium. Volume properties and pavement performances of AC-25 asphalt mixture with asbestos tailings were also evaluated compared with those with basalt as aggregates.XRD and XRF measurement results infer that asbestos tailing is an excellent road material. Volume properties of AC-25 asphalt mixture with asbestos tailings satisfied the related specifications. No heavy metals and toxic pollution were detected in AAS test and the value of pH test is 8.23, which is help to the adhesion with asphalt in the asphalt concrete. When compared with basalt, high temperature property and the resistance to low temperature cracking of AC-25 asphalt mixture was improved by using asbestos tailings as aggregates. In-service AC-25 asphalt pavement with asbestos tailings also presented excellent performance and British Pendulum Number (BPN) coefficient of surface.
A cold energy mixture theory for the equation of state in solid and porous metal mixtures
Zhang, X. F.; Qiao, L.; Shi, A. S.; Zhang, J.; Guan, Z. W.
2011-07-01
Porous or solid multi-component mixtures are ubiquitous in nature and extensively used as industrial materials such as multifunctional energetic structural materials (MESMs), metallic and ceramic powder for shock consolidation, and porous armor materials. In order to analyze the dynamic behavior of a particular solid or porous metal mixture in any given situation, a model is developed to calculate the Hugoniot data for solid or porous mixtures using only static thermodynamic properties of the components. The model applies the cold energy mixture theory to calculate the isotherm of the components to avoid temperature effects on the mixtures. The isobaric contribution from the thermodynamic equation of state is used to describe the porous material Hugoniot. Dynamic shock responses of solid or porous powder mixtures compacted by shock waves have been analyzed based on the mixture theory and Hugoniot for porous materials. The model is tested on both single-component porous materials such as aluminum 2024, copper, and iron; and on multi-component mixtures such as W/Cu, Fe/Ni, and Al/Ni. The theoretical calculations agree well with the corresponding experimental and simulation results. The present model produces satisfactory correlation with the experimentally obtained Hugoniot data for solid porous materials over a wide pressure range.
Adaptive Mixture Methods Based on Bregman Divergences
Donmez, Mehmet A; Kozat, Suleyman S
2012-01-01
We investigate adaptive mixture methods that linearly combine outputs of $m$ constituent filters running in parallel to model a desired signal. We use "Bregman divergences" and obtain certain multiplicative updates to train the linear combination weights under an affine constraint or without any constraints. We use unnormalized relative entropy and relative entropy to define two different Bregman divergences that produce an unnormalized exponentiated gradient update and a normalized exponentiated gradient update on the mixture weights, respectively. We then carry out the mean and the mean-square transient analysis of these adaptive algorithms when they are used to combine outputs of $m$ constituent filters. We illustrate the accuracy of our results and demonstrate the effectiveness of these updates for sparse mixture systems.
Computer simulation of rod-sphere mixtures
Antypov, D
2003-01-01
Results are presented from a series of simulations undertaken to investigate the effect of adding small spherical particles to a fluid of rods which would otherwise represent a liquid crystalline (LC) substance. Firstly, a bulk mixture of Hard Gaussian Overlap particles with an aspect ratio of 3:1 and hard spheres with diameters equal to the breadth of the rods is simulated at various sphere concentrations. Both mixing-demixing and isotropic-nematic transition are studied using Monte Carlo techniques. Secondly, the effect of adding Lennard-Jones particles to an LC system modelled using the well established Gay-Berne potential is investigated. These rod-sphere mixtures are simulated using both the original set of interaction parameters and a modified version of the rod-sphere potential proposed in this work. The subject of interest is the internal structure of the binary mixture and its dependence on density, temperature, concentration and various parameters characterising the intermolecular interactions. Both...
Quasi-chemical approximation for polyatomic mixtures
Dávila, M V; Matoz-Fernandez, D A; Ramirez-Pastor, A J
2016-01-01
The statistical thermodynamics of binary mixtures of polyatomic species was developed on a generalization in the spirit of the lattice-gas model and the quasi-chemical approximation (QCA). The new theoretical framework is obtained by combining: (i) the exact analytical expression for the partition function of non-interacting mixtures of linear $k$-mers and $l$-mers (species occupying $k$ sites and $l$ sites, respectively) adsorbed in one dimension, and its extension to higher dimensions; and (ii) a generalization of the classical QCA for multicomponent adsorbates and multisite-occupancy adsorption. The process is analyzed through the partial adsorption isotherms corresponding to both species of the mixture. Comparisons with analytical data from Bragg-Williams approximation (BWA) and Monte Carlo simulations are performed in order to test the validity of the theoretical model. Even though a good fitting is obtained from BWA, it is found that QCA provides a more accurate description of the phenomenon of adsorpti...
Efficient radiative transfer in dust grain mixtures
Wolf, S
2003-01-01
The influence of a dust grain mixture consisting of spherical dust grains with different radii and/or chemical composition on the resulting temperature structure and spectral energy distribution of a circumstellar shell is investigated. The comparison with the results based on an approximation of dust grain parameters representing the mean optical properties of the corresponding dust grain mixture reveal that (1) the temperature dispersion of a real dust grain mixture decreases substantially with increasing optical depth, converging towards the temperature distribution resulting from the approximation of mean dust grain parameters, and (2) the resulting spectral energy distributions do not differ by more than 10% if >= 2^5 grain sizes are considered which justifies the mean parameter approximation and the many results obtained under its assumption so far. Nevertheless, the dust grain temperature dispersion at the inner boundary of a dust shell may amount to >>100K and has therefore to be considered in the cor...
Two-Microphone Separation of Speech Mixtures
DEFF Research Database (Denmark)
Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan
2008-01-01
Separation of speech mixtures, often referred to as the cocktail party problem, has been studied for decades. In many source separation tasks, the separation method is limited by the assumption of at least as many sensors as sources. Further, many methods require that the number of signals within...... the recorded mixtures be known in advance. In many real-world applications, these limitations are too restrictive. We propose a novel method for underdetermined blind source separation using an instantaneous mixing model which assumes closely spaced microphones. Two source separation techniques have been...... similar signals. Using two microphones, we can separate, in principle, an arbitrary number of mixed speech signals. We show separation results for mixtures with as many as seven speech signals under instantaneous conditions. We also show that the proposed method is applicable to segregate speech signals...
Modeling methods for mixture-of-mixtures experiments applied to a tablet formulation problem.
Piepel, G F
1999-01-01
During the past few years, statistical methods for the experimental design, modeling, and optimization of mixture experiments have been widely applied to drug formulation problems. Different methods are required for mixture-of-mixtures (MoM) experiments in which a formulation is a mixture of two or more "major" components, each of which is a mixture of one or more "minor" components. Two types of MoM experiments are briefly described. A tablet formulation optimization example from a 1997 article in this journal is used to illustrate one type of MoM experiment and corresponding empirical modeling methods. Literature references that discuss other methods for MoM experiments are also provided.
Mutation spectra of complex environmental mixtures
Energy Technology Data Exchange (ETDEWEB)
DeMarini, D.M. [EPA, Research Triangle Park, NC (United States)
1997-10-01
Bioassay-directed chemical analysis of complex environmental mixtures has indicated that much of the genotoxic activity of mixtures is due to the presence of one or a few classes or chemicals within the mixture. We have extended this observation to the molecular level by using colony probe hybridization and PCR/DNA sequence analysis to determine the mutation spectra of {approximately}8,000 revertants induced by a variety of complex mixtures and their chemical fractions in TA100 and TA98 of Salmonella. For urban air, >80% of mutagenic activity was due to a base/neutral fraction that contained primarily PAHs. The mutation spectrum induced by unfractionated urban air was not significantly different from that produced by a model PAH, B(a)P. The mutation spectrum induced by organic extracts of chlorinated drinking water were similar to those produced by the chlorinated furanone MX, which accounted for {approximately}20% of the mutagenic activity of the samples. The base/neutral fraction of municipal waste incinerator emissions accounted for the primary class of mutations induced by the emissions, and a polar neutral fraction accounted for the secondary class of mutations induced by the emissions. The primary class of mutations induced by cigarette smoke condensate in TA100 (GC {yields} TA) is also the primary class of mutations in the p53 gene of lung tumors of cigarette smokers. These results confirm at the molecular level that the mutations induced by a complex mixture reflect the dominance of one or a few classes of chemicals within the mixture.
Stratified spectral mixture analysis of medium resolution imagery for impervious surface mapping
Sun, Genyun; Chen, Xiaolin; Ren, Jinchang; Zhang, Aizhu; Jia, Xiuping
2017-08-01
Linear spectral mixture analysis (LSMA) is widely employed in impervious surface estimation, especially for estimating impervious surface abundance in medium spatial resolution images. However, it suffers from a difficulty in endmember selection due to within-class spectral variability and the variation in the number and the type of endmember classes contained from pixel to pixel, which may lead to over or under estimation of impervious surface. Stratification is considered as a promising process to address the problem. This paper presents a stratified spectral mixture analysis in spectral domain (Sp_SSMA) for impervious surface mapping. It categorizes the entire data into three groups based on the Combinational Build-up Index (CBI), the intensity component in the color space and the Normalized Difference Vegetation Index (NDVI) values. A suitable endmember model is developed for each group to accommodate the spectral variation from group to group. The unmixing into the associated subset (or full set) of endmembers in each group can make the unmixing adaptive to the types of endmember classes that each pixel actually contains. Results indicate that the Sp_SSMA method achieves a better performance than full-set-endmember SMA and prior-knowledge-based spectral mixture analysis (PKSMA) in terms of R, RMSE and SE.
Thermophysical Properties of Fluids and Fluid Mixtures
Energy Technology Data Exchange (ETDEWEB)
Sengers, Jan V.; Anisimov, Mikhail A.
2004-05-03
The major goal of the project was to study the effect of critical fluctuations on the thermophysical properties and phase behavior of fluids and fluid mixtures. Long-range fluctuations appear because of the presence of critical phase transitions. A global theory of critical fluctuations was developed and applied to represent thermodynamic properties and transport properties of molecular fluids and fluid mixtures. In the second phase of the project, the theory was extended to deal with critical fluctuations in complex fluids such as polymer solutions and electrolyte solutions. The theoretical predictions have been confirmed by computer simulations and by light-scattering experiments. Fluctuations in fluids in nonequilibrium states have also been investigated.
Paternity testing that involves a DNA mixture.
Mortera, Julia; Vecchiotti, Carla; Zoppis, Silvia; Merigioli, Sara
2016-07-01
Here we analyse a complex disputed paternity case, where the DNA of the putative father was extracted from his corpse that had been inhumed for over 20 years. This DNA was contaminated and appears to be a mixture of at least two individuals. Furthermore, the mother's DNA was not available. The DNA mixture was analysed so as to predict the most probable genotypes of each contributor. The major contributor's profile was then used to compute the likelihood ratio for paternity. We also show how to take into account a dropout allele and the possibility of mutation in paternity testing.
Mixture Distribution Approach In Financial Risk Analysis
Kocak, Keziban; Calis, Nazif; Unal, Deniz
2014-01-01
In recent years, major changes occurred in the prices of stock exchange appeared the necessity of measuring the financial risk. Nowadays, Value-atRisk (VaR) is often used to calculate the financial risk. Parametric methods which need normality are mostly used in the calculation of VaR.If the financial data does not fit the normal distribution, mixture of normal distribution models can be fitted to this data. In this study, the financial risk is calculated by using normal mixture distribution ...
Boiler derating for coal-water mixtures
Energy Technology Data Exchange (ETDEWEB)
Horney, F.A.; Nolte, F.S.
1983-11-01
The authors demonstrated a method for approximating the derating required when converting an oil or natural gas fired unit to a coal-water mixture. If the results show that a retrofit to coal-water mixture appears economically reasonable, then a more detailed analysis should be made by the boiler manufacturer whose methods are more precise than the methods of this paper. The expense of having the boiler manufacturer make a precise analysis can be avoided if the results of the analysis of this paper show conversion not to be viable.
Conditional Density Approximations with Mixtures of Polynomials
DEFF Research Database (Denmark)
Varando, Gherardo; López-Cruz, Pedro L.; Nielsen, Thomas Dyhre
2015-01-01
Mixtures of polynomials (MoPs) are a non-parametric density estimation technique especially designed for hybrid Bayesian networks with continuous and discrete variables. Algorithms to learn one- and multi-dimensional (marginal) MoPs from data have recently been proposed. In this paper we introduce...... is found. We illustrate and study the methods using data sampled from known parametric distributions, and we demonstrate their applicability by learning models based on real neuroscience data. Finally, we compare the performance of the proposed methods with an approach for learning mixtures of truncated...
Flows and chemical reactions in homogeneous mixtures
Prud'homme, Roger
2013-01-01
Flows with chemical reactions can occur in various fields such as combustion, process engineering, aeronautics, the atmospheric environment and aquatics. The examples of application chosen in this book mainly concern homogeneous reactive mixtures that can occur in propellers within the fields of process engineering and combustion: - propagation of sound and monodimensional flows in nozzles, which may include disequilibria of the internal modes of the energy of molecules; - ideal chemical reactors, stabilization of their steady operation points in the homogeneous case of a perfect mixture and c
Mixture for removing tar and paraffin deposits
Energy Technology Data Exchange (ETDEWEB)
kamenshchikov, F.A.; Frolov, M.A.; Golovin, I.N.; Khusainov, Z.M.; Smirnov, Ya.L.; Suchkov, B.M.
1981-05-23
Mixture is claimed for removing tar and paraffin deposits (TPD) on the basis of the butyl-benzene fraction (BBF), which is intended to more efficiently remove TPD from the surface of refinery equipment, additionally has piperylene, isoprene and isoamine with the following ratio of the components: piperylene, 19-31%; isoprene, 8-12%; isoamines, 8-12%, while BBF, the rest. The efficiency of the given compositions was assessed by the rate at which the plates were cleaned of TPD and pure commercial paraffin. It has been shown that BBF dissolves 4-6 times faster in the given mixture than in BBF and pyperylene.
Viscosity of oil and water mixtures
Energy Technology Data Exchange (ETDEWEB)
Corlett, A.E.; Hall, A.R.W. [National Engineering Laboratory, Glasgow (United Kingdom)
1999-07-01
A study was performed to investigate the apparent viscosity of oil and water mixtures using the pressure loss along a horizontal pipe. Water fractions between 100% to 5% were examined at three flow velocities and three temperatures. Four combinations of crude oil and saline solution were used. Tests found that the mixture viscosity exhibited a peak at the position of phase inversion. The value of this maximum viscosity depended upon the temperature and fluid combination used, but not the velocity. Physical properties of the fluids were important factors in the viscosity/water fraction behaviour. (author)
Stiggelbout, M.; Popkema, D.Y.; Hopman-Rock, M.; Greef, M. de; Mechelen, W. van
2004-01-01
Objectives: To determine the effects of gymnastics on the health related quality of life (HRQoL) and functional status of independently living people, aged 65 to 80 years. Gymnastics formed part of the More Exercise for Seniors (MBvO in Dutch) programme, a group based exercise programme for older
Stiggelbout, M.; Popkema, D.Y.; Hopman-Rock, M.; de Greef, M.; van Mechelen, W.
2004-01-01
OBJECTIVES: To determine the effects of gymnastics on the health related quality of life (HRQoL) and functional status of independently living people, aged 65 to 80 years. Gymnastics formed part of the More Exercise for Seniors (MBvO in Dutch) programme, a group based exercise programme for older
Vasquez, Eduardo A; Wenborne, Lisa; Peers, Madeline; Alleyne, Emma; Ellis, Kirsty
2015-05-01
In non-gang populations, the degree of identification with an in-group and perceptions of out-group entitativity, the perception of an out-group as bonded or unified, are important contributors to group-based aggression or vicarious retribution. The link between these factors and group-based aggression, however, has not been examined in the context of street gangs. The current study assessed the relationship among in-group identification, perceptions of out-group entitativity, and the willingness to retaliate against members of rival groups who did not themselves attack the in-group among juvenile gang and non-gang members in London. Our results showed the predicted membership (gang/non-gang) × in-group identification × entitativity interaction. Decomposition of the three-way interaction by membership revealed a significant identification × entitativity interaction for gang, but not for non-gang members. More specifically, gang members who identify more strongly with their gang and perceived a rival group as high on entitativity were more willing to retaliate against any of them. In addition, entitativity was a significant predictor of group-based aggression after controlling for gender, in-group identification, and gang membership. Our results are consistent with socio-psychological theories of group-based aggression and support the proposal that such theories are applicable for understanding gang-related violence. Aggr. Behav. 41:242-252, 2015. © 2015 Wiley Periodicals, Inc.
DEFF Research Database (Denmark)
Toft, Ulla; Kristoffersen, Lis; Ladelund, Steen;
2008-01-01
Few studies have investigated the specific effect of single intervention components in randomized controlled trials. The purpose was to investigate the effect of adding group-based diet and exercise counselling to individual life-style counselling on long-term changes in dietary habits....
Lee, I-Ching; Pratto, Felicia; Johnson, Blair T
2011-11-01
A meta-analysis examined the extent to which socio-structural and psycho-cultural characteristics of societies correspond with how much gender and ethnic/racial groups differ on their support of group-based hierarchy. Robustly, women opposed group-based hierarchy more than men did, and members of lower power ethnic/racial groups opposed group-based hierarchy more than members of higher power ethnic/racial groups did. As predicted by social dominance theory, gender differences were larger, more stable, and less variable from sample to sample than differences between ethnic/racial groups. Subordinate gender and ethnic/racial group members disagreed more with dominants in their views of group-based hierarchy in societies that can be considered more liberal and modern (e.g., emphasizing individualism and change from traditions), as well as in societies that enjoyed greater gender equality. The relations between gender and ethnic/racial groups are discussed, and implications are developed for social dominance theory, social role theory, biosocial theory, social identity theory, system justification theory, realistic group conflict theory, and relative deprivation theory. (PsycINFO Database Record (c) 2011 APA, all rights reserved).
O'Callaghan, Paul; Cunningham, Enda
2015-01-01
This pilot study examined the impact of a 10 session, group-based, early-intervention cognitive behavioural therapy (CBT) programme (Cool Connections) on anxiety, depression and self-concept in nine 8-11 year old pupils in Northern Ireland. The intervention was facilitated by a teacher, education welfare officer and two classroom assistants, with…
Stiggelbout, M.; Popkema, D.Y.; Hopman-Rock, M.; de Greef, M.; van Mechelen, W.
2004-01-01
OBJECTIVES: To determine the effects of gymnastics on the health related quality of life (HRQoL) and functional status of independently living people, aged 65 to 80 years. Gymnastics formed part of the More Exercise for Seniors (MBvO in Dutch) programme, a group based exercise programme for older ad
Kweekel, L.; Gerrits, T.; Rijnders, M.; Brown, P.R.
2016-01-01
Background CenteringPregnancy (CP) is a specific model of group-based prenatal care for women, implemented in 44 midwifery practices in The Netherlands since 2011. Women have evaluated CP positively, especially in terms of social support, and improvements have been made in birthweight and preterm-bi
Figueiredo, A.; Doosje, B.; Pires Valentim, J.; Zebel, S.
2010-01-01
An examination of potential outgroup-focused predictors of group-based guilt relating to past colonial conflicts involving Portugal and the Netherlands, specifically, the role of the perceptions of the ingroup towards the victimized outgroup, as well as on outgroup identification and meta-perception
Zwikker, H.E.; Ende, C.H. van den; Lankveld, W.G. van; Broeder, A.A. den; Hoogen, F.H. van den; Mosselaar, B. van de; Dulmen, S. van; Bemt, B.J. van den
2014-01-01
Objective: To assess the effect of a group-based intervention on the balance between necessity beliefs and concern beliefs about medication and on medication non-adherence in patients with rheumatoid arthritis (RA). Methods: Non-adherent RA patients using disease-modifying anti-rheumatic drugs (DMAR
Lee, I-Ching; Pratto, Felicia; Johnson, Blair T.
2011-01-01
A meta-analysis examined the extent to which socio-structural and psycho-cultural characteristics of societies correspond with how much gender and ethnic/racial groups differ on their support of group-based hierarchy. Robustly, women opposed group-based hierarchy more than men did and members of lower-power ethnic/racial groups opposed group-based hierarchy more than members of higher-power ethnic/racial groups. As predicted by social dominance theory, gender differences were larger, more stable, and less variable from sample to sample than differences between ethnic/racial groups. Subordinate gender and ethnic/racial group members disagreed more with dominants in their views of group-based hierarchy in societies that can be considered more liberal and modern (e.g., emphasizing individualism and change from traditions), as well as in societies that enjoyed greater gender equality. The relations between gender and ethnic/racial groups are discussed and implications are developed for social dominance theory, social role theory and biosocial theory, social identity theory, system justification theory, realistic group conflict theory and relative deprivation theory. PMID:22023142
George, Daniel R.; Stuckey, Heather L.; Dillon, Caroline F.; Whitehead, Megan M.
2011-01-01
Purpose: To evaluate whether medical student participation in TimeSlips (TS), a creative group-based storytelling program, with persons affected by dementia would improve student attitudes toward this patient population. Design and Methods: Fifteen fourth-year medical students from Penn State College of Medicine participated in a month-long…
Institute of Scientific and Technical Information of China (English)
刘新乐
2016-01-01
缺失数据模型问题和纵向数据模型问题一直是统计学的热点之一，但对于纵向数据缺失情况的模型研究较少。本文针对纵向数据缺失情况提出了缺失纵向数据下的半参数回归模型，使用CC（Complete－Case）方法将所有含数据缺失的项删除，仅对余下的“完全”样本按二阶段估计的方法进行统计推断，得到了参数向量和非参数向量的二阶段估计的最终估计βr＾和gr （＾t），并证明这些估计量满足渐近正态性质。并且通过数据模拟形式说明了这个估计方法的可行性。%The issues of the missing data model and the longitudinal data model have been one of the hotspots of the statistics,but the study of the model of missing longitudinal data is very few.The semi-parametric re-gression model of missing longitudinal data is proposed in this thesis and the solutions is given:For missing longitudinal data,all items will be deleted in this thesis which contains lossing data using the CC method,and only remaining“full”sample.By the second stage estination method for statistical inference,the ultimate esti-mates of parametric and nonparametric vector are got by using the two stages estimate.And the asymptotic nor-mal properties of these estimators is proved.And the data simulation shows that the estimation method is feasi-ble.
MixtureTree annotator: a program for automatic colorization and visual annotation of MixtureTree.
Directory of Open Access Journals (Sweden)
Shu-Chuan Chen
Full Text Available The MixtureTree Annotator, written in JAVA, allows the user to automatically color any phylogenetic tree in Newick format generated from any phylogeny reconstruction program and output the Nexus file. By providing the ability to automatically color the tree by sequence name, the MixtureTree Annotator provides a unique advantage over any other programs which perform a similar function. In addition, the MixtureTree Annotator is the only package that can efficiently annotate the output produced by MixtureTree with mutation information and coalescent time information. In order to visualize the resulting output file, a modified version of FigTree is used. Certain popular methods, which lack good built-in visualization tools, for example, MEGA, Mesquite, PHY-FI, TreeView, treeGraph and Geneious, may give results with human errors due to either manually adding colors to each node or with other limitations, for example only using color based on a number, such as branch length, or by taxonomy. In addition to allowing the user to automatically color any given Newick tree by sequence name, the MixtureTree Annotator is the only method that allows the user to automatically annotate the resulting tree created by the MixtureTree program. The MixtureTree Annotator is fast and easy-to-use, while still allowing the user full control over the coloring and annotating process.
MixtureTree annotator: a program for automatic colorization and visual annotation of MixtureTree.
Chen, Shu-Chuan; Ogata, Aaron
2015-01-01
The MixtureTree Annotator, written in JAVA, allows the user to automatically color any phylogenetic tree in Newick format generated from any phylogeny reconstruction program and output the Nexus file. By providing the ability to automatically color the tree by sequence name, the MixtureTree Annotator provides a unique advantage over any other programs which perform a similar function. In addition, the MixtureTree Annotator is the only package that can efficiently annotate the output produced by MixtureTree with mutation information and coalescent time information. In order to visualize the resulting output file, a modified version of FigTree is used. Certain popular methods, which lack good built-in visualization tools, for example, MEGA, Mesquite, PHY-FI, TreeView, treeGraph and Geneious, may give results with human errors due to either manually adding colors to each node or with other limitations, for example only using color based on a number, such as branch length, or by taxonomy. In addition to allowing the user to automatically color any given Newick tree by sequence name, the MixtureTree Annotator is the only method that allows the user to automatically annotate the resulting tree created by the MixtureTree program. The MixtureTree Annotator is fast and easy-to-use, while still allowing the user full control over the coloring and annotating process.
A Skew-Normal Mixture Regression Model
Liu, Min; Lin, Tsung-I
2014-01-01
A challenge associated with traditional mixture regression models (MRMs), which rest on the assumption of normally distributed errors, is determining the number of unobserved groups. Specifically, even slight deviations from normality can lead to the detection of spurious classes. The current work aims to (a) examine how sensitive the commonly…
Uniform design of experiments with mixtures
Institute of Scientific and Technical Information of China (English)
王元; 方开泰
1996-01-01
Consider a design of experiments with mixtures:0≤ai
Modeling text with generalizable Gaussian mixtures
DEFF Research Database (Denmark)
Hansen, Lars Kai; Sigurdsson, Sigurdur; Kolenda, Thomas
2000-01-01
We apply and discuss generalizable Gaussian mixture (GGM) models for text mining. The model automatically adapts model complexity for a given text representation. We show that the generalizability of these models depends on the dimensionality of the representation and the sample size. We discuss...
The Coffee-Milk Mixture Problem Revisited
Marion, Charles F.
2015-01-01
This analysis of a problem that is frequently posed at professional development workshops, in print, and on the Web--the coffee-milk mixture riddle--illustrates the timeless advice of George Pólya's masterpiece on problem solving in mathematics, "How to Solve It." In his book, Pólya recommends that problems previously solved and put…
Quantification of complex mixtures by NMR
Duynhoven, van J.P.M.; Velzen, van E.; Jacobs, D.M.
2013-01-01
NMR has firmly established itself as an analytical tool that can quantify analyte concentrations in complex mixtures in a rapid, cost-effective, accurate and precise manner. Here, the technological advances with respect to instrumentation, sample preparation, data acquisition and data processing ove
Toxicology of chemical mixtures: International perspective
Feron, V.J.; Cassee, F.R.; Groten, J.P.
1998-01-01
This paper reviews major activities outside the United States on human health issues related to chemical mixtures. In Europe an international study group on combination effects has been formed and has started by defining synergism and antagonism. Successful research programs in Europe include the de
Mixture toxicity of PBT-like chemicals
DEFF Research Database (Denmark)
Syberg, Kristian; Dai, Lina; Ramskov, Tina
beyond that of the individual components. Firstly, the effects of three chemicals with PBT-like properties (acetyl cedrene, pyrene and triclosan) was examined on the freshwater snail, Potamopyrgus antipodarum. Secondly, mixture bioaccumulation of the same three chemicals were assessed experimentally...
Concrete mixture characterization. Cementitious barriers partnership
Energy Technology Data Exchange (ETDEWEB)
Langton, C. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Protiere, Yannick [SIMCO Technologies, Inc., Quebec (Canada)
2014-12-01
This report summarizes the characterization study performed on two concrete mixtures used for radioactive waste storage. Both mixtures were prepared with approximately 425 kg of binder. The testing protocol mostly focused on determining the transport properties of the mixtures; volume of permeable voids (porosity), diffusion coefficients, and water permeability were evaluated. Tests were performed after different curing durations. In order to obtain data on the statistical distribution of transport properties, the measurements after 2 years of curing were performed on 10+ samples. Overall, both mixtures exhibited very low tortuosities and permeabilities, a direct consequence of their low water-to-binder ratio and the use of supplementary cementitious materials. The data generated on 2-year old samples showed that porosity, tortuosity and permeability follow a normal distribution. Chloride ponding tests were also performed on test samples. They showed limited chloride ingress, in line with measured transport properties. These test results also showed that both materials react differently with chloride, a consequence of the differences in the binder chemical compositions.
Predicting diffusivities in dense fluid mixtures
Directory of Open Access Journals (Sweden)
C. DARIVA
1999-09-01
Full Text Available In this work the Enskog solution of the Boltzmann equation, as corrected by Speedy, together with the Weeks-Chandler-Andersen (WCA perturbation theory of liquids is employed in correlating and predicting self-diffusivities of dense fluids. Afterwards this theory is used to estimate mutual diffusion coefficients of solutes at infinite dilution in sub and supercritical solvents. We have also investigated the behavior of Fick diffusion coefficients in the proximity of a binary vapor-liquid critical point since this subject is of great interest for extraction purposes. The approach presented here, which makes use of a density and temperature dependent hard-sphere diameter, is shown to be excellent for predicting diffusivities in dense pure fluids and fluid mixtures. The calculations involved highly nonideal mixtures as well as systems with high molecular asymmetry. The predicted diffusivities are in good agreement with the experimental data for the pure and binary systems. The methodology proposed here makes only use of pure component information and density of mixtures. The simple algebraic relations are proposed without any binary adjustable parameters and can be readily used for estimating diffusivities in multicomponent mixtures.
Self-assembly models for lipid mixtures
Singh, Divya; Porcar, Lionel; Butler, Paul; Perez-Salas, Ursula
2006-03-01
Solutions of mixed long and short (detergent-like) phospholipids referred to as ``bicelle'' mixtures in the literature, are known to form a variety of different morphologies based on their total lipid composition and temperature in a complex phase diagram. Some of these morphologies have been found to orient in a magnetic field, and consequently bicelle mixtures are widely used to study the structure of soluble as well as membrane embedded proteins using NMR. In this work, we report on the low temperature phase of the DMPC and DHPC bicelle mixture, where there is agreement on the discoid structures but where molecular packing models are still being contested. The most widely accepted packing arrangement, first proposed by Vold and Prosser had the lipids completely segregated in the disk: DHPC in the rim and DMPC in the disk. Using data from small angle neutron scattering (SANS) experiments, we show how radius of the planar domain of the disks is governed by the effective molar ratio qeff of lipids in aggregate and not the molar ratio q (q = [DMPC]/[DHPC] ) as has been understood previously. We propose a new quantitative (packing) model and show that in this self assembly scheme, qeff is the real determinant of disk sizes. Based on qeff , a master equation can then scale the radii of disks from mixtures with varying q and total lipid concentration.
Flexible Rasch Mixture Models with Package psychomix
Directory of Open Access Journals (Sweden)
Hannah Frick
2012-05-01
Full Text Available Measurement invariance is an important assumption in the Rasch model and mixture models constitute a flexible way of checking for a violation of this assumption by detecting unobserved heterogeneity in item response data. Here, a general class of Rasch mixture models is established and implemented in R, using conditional maximum likelihood estimation of the item parameters (given the raw scores along with flexible specification of two model building blocks: (1 Mixture weights for the unobserved classes can be treated as model parameters or based on covariates in a concomitant variable model. (2 The distribution of raw score probabilities can be parametrized in two possible ways, either using a saturated model or a specification through mean and variance. The function raschmix( in the R package psychomix provides these models, leveraging the general infrastructure for fitting mixture models in the flexmix package. Usage of the function and its associated methods is illustrated on artificial data as well as empirical data from a study of verbally aggressive behavior.
Spinodal decomposition of chemically reactive binary mixtures
Lamorgese, A.; Mauri, R.
2016-08-01
We simulate the influence of a reversible isomerization reaction on the phase segregation process occurring after spinodal decomposition of a deeply quenched regular binary mixture, restricting attention to systems wherein material transport occurs solely by diffusion. Our theoretical approach follows a diffuse-interface model of partially miscible binary mixtures wherein the coupling between reaction and diffusion is addressed within the frame of nonequilibrium thermodynamics, leading to a linear dependence of the reaction rate on the chemical affinity. Ultimately, the rate for an elementary reaction depends on the local part of the chemical potential difference since reaction is an inherently local phenomenon. Based on two-dimensional simulation results, we express the competition between segregation and reaction as a function of the Damköhler number. For a phase-separating mixture with components having different physical properties, a skewed phase diagram leads, at large times, to a system converging to a single-phase equilibrium state, corresponding to the absolute minimum of the Gibbs free energy. This conclusion continues to hold for the critical phase separation of an ideally perfectly symmetric binary mixture, where the choice of final equilibrium state at large times depends on the initial mean concentration being slightly larger or less than the critical concentration.
Toxicity of metal mixtures to chick embryos
Energy Technology Data Exchange (ETDEWEB)
Birge, W.J.; Roberts, O.W.; Black, J.A.
1976-09-01
The toxic effects of mercury/selenium and certain other metal mixtures on the chick embryo are examined to determine whether antagonistic, additive or synergistic interactions occur. White Plymouth Rock chicken eggs were treated by yolk injection with cadmium chloride, mercuric chloride, zinc chloride and sodium selenate. Test aliquots were injected prior to incubation using the needle track procedure. Using a sample size of 200, percent survival was determined as hatchability of experimental eggs/controls. Metal mixtures used included mercury/cadmium, mercury/selenium, mercury/zinc, cadmium/selenium, and cadmium/zinc. Except for mercury/selenium, all other metal mixtures gave actual values that were within 5% of those for additive toxic effects. Actual hatchability frequencies for test concentrations of mercury/selenium indicated a moderate degree of synergism. Results indicate that the strong mercury/selenium synergism which affects embryonic development in the carp does not apply for the chick embryo; that most two-way combinations of cadmium, mercury, selenium and zinc exert purely additive effects on chick hatchability; and that these metal mixtures give no discernible antagonistic interactions which affect survival of chick embryos. (MFB)
Using Regression Mixture Analysis in Educational Research
Directory of Open Access Journals (Sweden)
Cody S. Ding
2006-11-01
Full Text Available Conventional regression analysis is typically used in educational research. Usually such an analysis implicitly assumes that a common set of regression parameter estimates captures the population characteristics represented in the sample. In some situations, however, this implicit assumption may not be realistic, and the sample may contain several subpopulations such as high math achievers and low math achievers. In these cases, conventional regression models may provide biased estimates since the parameter estimates are constrained to be the same across subpopulations. This paper advocates the applications of regression mixture models, also known as latent class regression analysis, in educational research. Regression mixture analysis is more flexible than conventional regression analysis in that latent classes in the data can be identified and regression parameter estimates can vary within each latent class. An illustration of regression mixture analysis is provided based on a dataset of authentic data. The strengths and limitations of the regression mixture models are discussed in the context of educational research.
Two-microphone Separation of Speech Mixtures
DEFF Research Database (Denmark)
2006-01-01
of Speech Mixtures," 2006, submited for journal publication. See also, [2] Michael Syskind Pedersen, DeLiang Wang, Jan Larsen and Ulrik Kjems: "Overcomplete Blind Source Separation by Combining ICA and Binary Time-Frequency Masking," in proceedings of IEEE International workshop on Machine Learning...
Structure of cholesterol/ceramide monolayer mixtures
DEFF Research Database (Denmark)
Scheffer, L.; Solomonov, I.; Weygand, M.J.
2005-01-01
The structure of monolayers of cholesterol/ ceramide mixtures was investigated using grazing incidence x-ray diffraction, immunofluorescence, and atomic force microscopy techniques. Grazing incidence x-ray diffraction measurements showed the existence of a crystalline mixed phase of the two...
Mixture model analysis of complex samples
Wedel, M; ter Hofstede, F; Steenkamp, JBEM
1998-01-01
We investigate the effects of a complex sampling design on the estimation of mixture models. An approximate or pseudo likelihood approach is proposed to obtain consistent estimates of class-specific parameters when the sample arises from such a complex design. The effects of ignoring the sample desi
Numerical Solution of Hard-Core Mixtures
Buhot, Arnaud; Krauth, Werner
1997-01-01
We study the equilibrium phase diagram of binary mixtures of hard spheres as well as of parallel hard cubes. A superior cluster algorithm allows us to establish and to access the demixed phase for both systems and to investigate the subtle interplay between short-range depletion and long-range demixing.
Pool Boiling of Hydrocarbon Mixtures on Water
Energy Technology Data Exchange (ETDEWEB)
Boee, R.
1996-09-01
In maritime transport of liquefied natural gas (LNG) there is a risk of spilling cryogenic liquid onto water. The present doctoral thesis discusses transient boiling experiments in which liquid hydrocarbons were poured onto water and left to boil off. Composition changes during boiling are believed to be connected with the initiation of rapid phase transition in LNG spilled on water. 64 experimental runs were carried out, 14 using pure liquid methane, 36 using methane-ethane, and 14 using methane-propane binary mixtures of different composition. The water surface was open to the atmosphere and covered an area of 200 cm{sup 2} at 25 - 40{sup o}C. The heat flux was obtained by monitoring the change of mass vs time. The void fraction in the boiling layer was measured with a gamma densitometer, and a method for adapting this measurement concept to the case of a boiling cryogenic liquid mixture is suggested. Significant differences in the boil-off characteristics between pure methane and binary mixtures revealed by previous studies are confirmed. Pure methane is in film boiling, whereas the mixtures appear to enter the transitional boiling regime with only small amounts of the second component added. The results indicate that the common assumption that LNG will be in film boiling on water because of the high temperature difference, may be questioned. Comparison with previous work shows that at this small scale the results are influenced by the experimental apparatus and procedures. 66 refs., 76 figs., 28 tabs.
Mixtures of Ultracold Fermions with Unequal Masses
de Melo, Carlos A. R. Sa
2008-05-01
The quantum phases of ultracold fermions with unequal masses are discussed in continuum and lattice models for a wide variety of mixtures which exhibit Feshbach resonances, e.g., mixtures of ^6Li and ^40K. The evolution of superfluidity from the Bardeen-Cooper-Schrieffer (BCS) to the Bose-Einstein condensation (BEC) regime in the continuum is analyzed as a function of scattering parameter, population imbalance and mass anisotropy. In the continuum case, regions corresponding to normal, phase-separated or coexisting uniform-superfluid/excess-fermion phases are identified and the possibility of topological phase transitions is discussed [1]. For optical lattices, the phase diagrams as a function of interaction strength, population imbalance, filling fraction and tunneling parameters are presented [2]. In addition to the characteristic phases of the continuum, a series of insulating phases emerge in the phase diagrams of optical lattices, including a Bose-Mott insulator (BMI), a Fermi-Pauli insulator (FPI), a phase-separated BMI/FPI mixture, and a Bose-Fermi checkerboard (BFC) phase. Lastly, the effects of harmonic traps and the emergence of unusual shell structures are discussed for mixtures of fermions with unequal masses. [1] M. Iskin, and C. A. R. S' a de Melo, Phys. Rev. Lett 97, 100404 (2006); [2] M. Iskin, and C. A. R. S' a de Melo, Phys. Rev. Lett. 99, 080403 (2007).
Cementitious barriers partnership concrete mixture characterization
Energy Technology Data Exchange (ETDEWEB)
Langton, C. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Protiere, Yannick [SIMCO Technologies, Inc., Quebec (Canada)
2014-12-01
This report summarizes the characterization study performed on two concrete mixtures used for radioactive waste storage. Both mixtures were prepared with approximately 425 kg of binder. The testing protocol mostly focused on determining the transport properties of the mixtures; volume of permeable voids (porosity), diffusion coefficients, and water permeability were evaluated. Tests were performed after different curing durations. In order to obtain data on the statistical distribution of transport properties, the measurements after 2 years of curing were performed on 10+ samples. Overall, both mixtures exhibited very low tortuosities and permeabilities, a direct consequence of their low water-to-binder ratio and the use of supplementary cementitious materials. The data generated on 2-year old samples showed that porosity, tortuosity and permeability follow a normal distribution. Chloride ponding tests were also performed on test samples. They showed limited chloride ingress, in line with measured transport properties. These test results also showed that both materials react differently with chloride, a consequence of the differences in the binder chemical compositions.
Some aspects of symmetric Gamma process mixtures
Naulet, Zacharie; Barat, Eric
2015-01-01
In this article, we present some specific aspects of symmetric Gamma process mixtures for use in regression models. We propose a new Gibbs sampler for simulating the posterior and we establish adaptive posterior rates of convergence related to the Gaussian mean regression problem.
The Coffee-Milk Mixture Problem Revisited
Marion, Charles F.
2015-01-01
This analysis of a problem that is frequently posed at professional development workshops, in print, and on the Web--the coffee-milk mixture riddle--illustrates the timeless advice of George Pólya's masterpiece on problem solving in mathematics, "How to Solve It." In his book, Pólya recommends that problems previously solved and put…
Theory of dynamic arrest in colloidal mixtures.
Juárez-Maldonado, R; Medina-Noyola, M
2008-05-01
We present a first-principles theory of dynamic arrest in colloidal mixtures based on the multicomponent self-consistent generalized Langevin equation theory of colloid dynamics [M. A. Chávez-Rojo and M. Medina-Noyola, Phys. Rev. E 72, 031107 (2005); M. A. Chávez-Rojo and M. Medina-Noyola, Phys. Rev. E76, 039902 (2007)]. We illustrate its application with a description of dynamic arrest in two simple model colloidal mixtures: namely, hard-sphere and repulsive Yukawa binary mixtures. Our results include observation of the two patterns of dynamic arrest, one in which both species become simultaneously arrested and the other involving the sequential arrest of the two species. The latter case gives rise to mixed states in which one species is arrested while the other species remains mobile. We also derive the ("bifurcation" or fixed-point") equations for the nonergodic parameters of the system, which takes the surprisingly simple form of a system of coupled equations for the localization length of the particles of each species. The solution of this system of equations indicates unambiguously which species is arrested (finite localization length) and which species remains ergodic (infinite localization length). As a result, we are able to draw the entire ergodic-nonergodic phase diagram of the binary hard-sphere mixture.
Toxicology of chemical mixtures: International perspective
Feron, V.J.; Cassee, F.R.; Groten, J.P.
1998-01-01
This paper reviews major activities outside the United States on human health issues related to chemical mixtures. In Europe an international study group on combination effects has been formed and has started by defining synergism and antagonism. Successful research programs in Europe include the
Computer simulation of rod-sphere mixtures
Energy Technology Data Exchange (ETDEWEB)
Antypov, Dmytro
2003-07-01
Results are presented from a series of simulations undertaken to investigate the effect of adding small spherical particles to a fluid of rods which would otherwise represent a liquid crystalline (LC) substance. Firstly, a bulk mixture of Hard Gaussian Overlap particles with an aspect ratio of 3:1 and hard spheres with diameters equal to the breadth of the rods is simulated at various sphere concentrations. Both mixing-demixing and isotropic-nematic transition are studied using Monte Carlo techniques. Secondly, the effect of adding Lennard-Jones particles to an LC system modelled using the well established Gay-Berne potential is investigated. These rod-sphere mixtures are simulated using both the original set of interaction parameters and a modified version of the rod-sphere potential proposed in this work. The subject of interest is the internal structure of the binary mixture and its dependence on density, temperature, concentration and various parameters characterising the intermolecular interactions. Both the mixing-demixing behaviour and the transitions between the isotropic and any LC phases have been studied for four systems which differ in the interaction potential between unlike particles. A range of contrasting microphase separated structures including bicontinuous, cubic, and micelle-like arrangement have been observed in bulk. Thirdly, the four types of mixtures previously studied in bulk are subjected to a static magnetic field. A variety of novel phases are observed for the cases of positive and negative anisotropy in the magnetic susceptibility. These include a lamellar structure, in which layers of rods are separated by layers of spheres, and a configuration with a self-assembling hexagonal array of spheres. Finally, two new models are presented to study liquid crystal mixtures in the presence of curved substrates. These are implemented for the cases of convex and concave spherical surfaces. The simulation results obtained in these geometries
Experiments with Mixtures Designs, Models, and the Analysis of Mixture Data
Cornell, John A
2011-01-01
The most comprehensive, single-volume guide to conducting experiments with mixtures"If one is involved, or heavily interested, in experiments on mixtures of ingredients, one must obtain this book. It is, as was the first edition, the definitive work."-Short Book Reviews (Publication of the International Statistical Institute)"The text contains many examples with worked solutions and with its extensive coverage of the subject matter will prove invaluable to those in the industrial and educational sectors whose work involves the design and analysis of mixture experiments."-Journal of the Royal S
Properties of Direct Coal Liquefaction Residue Modified Asphalt Mixture
Directory of Open Access Journals (Sweden)
Jie Ji
2017-01-01
Full Text Available The objectives of this paper are to use Direct Coal Liquefaction Residue (DLCR to modify the asphalt binders and mixtures and to evaluate the performance of modified asphalt mixtures. The dynamic modulus and phase angle of DCLR and DCLR-composite modified asphalt mixture were analyzed, and the viscoelastic properties of these modified asphalt mixtures were compared to the base asphalt binder SK-90 and Styrene-Butadiene-Styrene (SBS modified asphalt mixtures. The master curves of the asphalt mixtures were shown, and dynamic and viscoelastic behaviors of asphalt mixtures were described using the Christensen-Anderson-Marasteanu (CAM model. The test results show that the dynamic moduli of DCLR and DCLR-composite asphalt mixtures are higher than those of the SK-90 and SBS modified asphalt mixtures. Based on the viscoelastic parameters of CAM models of the asphalt mixtures, the high- and low-temperature performance of DLCR and DCLR-composite modified asphalt mixtures are obviously better than the SK-90 and SBS modified asphalt mixtures. In addition, the DCLR and DCLR-composite modified asphalt mixtures are more insensitive to the frequency compared to SK-90 and SBS modified asphalt mixtures.
Thermodiffusion in binary and ternary nonpolar hydrocarbon + alcohol mixtures
Eslamian, Morteza; Saghir, M. Ziad
2012-12-01
Thermodiffusion in complex mixtures, such as associating, molten metal, and polymer mixtures is difficult to model usually owing to the occurrence of a sign change in the thermodiffusion coefficient when the mixture concentration and temperature change. A mixture comprised of a nonpolar hydrocarbon and an alcohol is a complex and highly non-ideal mixture. In this paper an existing binary non-equilibrium thermodynamics model (Eslamian and Saghir, Physical Review E 80, 061201, 2009) developed for aqueous mixtures of alcohols is examined against the experimental data of binary nonpolar hydrocarbon and alcohol mixtures. For ternary mixtures, non-equilibrium thermodynamic expressions developed by the authors for aqueous mixtures of alcohols (Eslamian and Saghir, Canadian Journal of Chemical Engineering, DOI 10.1002/cjce.20581) is used to predict thermodiffusion coefficients of ternary nonpolar hydrocarbon and alcohol mixtures. The rationale behind the sign change is elucidated and attributed to an anomalous change in the molecular structure and therefore viscosity of such mixtures. Model predictions of thermodiffusion coefficients of binary mixtures predict a sign change consistent with the experimental data although the model is still too primitive to capture all structural complexities. For instance, in the methanol-benzene mixture where the model predictions are poorest, the viscosity data show that when concentration varies, the mixture's molecular structure experiences a severe change twice, the first major change leading to a maximum in the thermodiffusion coefficient, whereas the second change causes a sign change.
Schoenfuss, Heiko L.; Furlong, Edward T.; Phillips, Patrick J.; Scott, Tia-Marie; Kolpin, Dana W.; Cetkovic-Cvrlje, Marina; Lesteberg, Kelsey E.; Rearick, Daniel C.
2016-01-01
Pharmaceuticals are present in low concentrations (tramadol), a muscle relaxant (methocarbamol), a simple antidepressant mixture (fluoxetine, paroxetine, venlafaxine), a sleep aid (temazepam), or a complex mixture of all compounds. Larval minnow response to effluent exposure was not consistent. The 2010 exposures resulted in shorter exposed minnow larvae, whereas the larvae exposed in 2012 exhibited altered escape behavior. Mature minnows exhibited altered hepatosomatic indices, with the strongest effects in females and in mixture exposures. In addition, laboratory-exposed, mature male minnows exposed to all pharmaceuticals (except the selective serotonin reuptake inhibitor mixture) defended nest sites less rigorously than fish in the control group. Tramadol or antidepressant mixture exposure resulted in increased splenic T lymphocytes. Only male minnows exposed to whole effluent responded with increased plasma vitellogenin concentrations. Female minnows exposed to pharmaceuticals (except the opioid mixture) had larger livers, likely as a compensatory result of greater prominence of vacuoles in liver hepatocytes. The observed alteration of apical endpoints central to sustaining fish populations confirms that effluents containing waste streams from pharmaceutical formulation facilities can adversely impact fish populations but that the effects may not be temporally consistent. The present study highlights the importance of including diverse biological endpoints spanning levels of biological organization and life stages when assessing contaminant interactions.
Phase structure of liposome in lipid mixtures.
Zhang, Tianxi; Li, Yuzhuo; Mueller, Anja
2011-11-01
Gas microbubbles present in ultrasound imaging contrast agents are stabilized by lipid aggregates that typically contain a mixture of lipids. In this study, the phase structure of the lipid mixtures that contained two or three lipids was investigated using three different methods: dynamic light scattering, (1)H NMR, and microfluidity measurements with fluorescence probes. Three lipids that are commonly present in imaging agents (DPPC, DPPE-PEG, and DPPA) were used. Two types of systems, two-lipid model systems and simulated imaging systems were investigated. The results show that liposomes were the dominant aggregates in all the samples studied. The polar PEG side chains from the PEGylated lipid lead to the formation of micelles and micellar aggregates in small sizes. In the ternary lipid systems, almost all the lipids were present in bilayers with micelles absent and free lipids at very low concentration. These results suggest that liposomes, not micelles, contribute to the stabilization of microbubbles in an ultrasound imaging contrast agent.
Molecular thermodiffusion (thermophoresis) in liquid mixtures.
Semenov, Semen N; Schimpf, Martin E
2005-10-01
Thermodiffusion (thermophoresis) in liquid mixtures is theoretically examined using a hydrodynamic approach. Thermodiffusion is related to the local temperature-induced pressure gradient in the liquid layer surrounding the selected molecule and to the secondary macroscopic pressure gradient established in the system. The local pressure gradient is produced by excess pressure due to the asymmetry of interactions with surrounding molecules in a nonuniform temperature field. The secondary pressure gradient is considered an independent parameter related to the concentration gradient formed by volume forces, calculated from the generalized equations for mass transfer. Values of Soret coefficients for mixtures of toluene and -hexane are calculated using parameters in the literature. When the molecules are assumed to be similar in shape, the calculated Soret coefficients are lower than the empirical values found in the literature. However, by introducing an asymmetry parameter, which is calculated from independent measurements of component diffusion in the literature, very good agreement is obtained.
Quantum state smoothing for classical mixtures
Tan, D; Mølmer, K; Murch, K W
2016-01-01
In quantum mechanics, wave functions and density matrices represent our knowledge about a quantum system and give probabilities for the outcomes of measurements. If the combined dynamics and measurements on a system lead to a density matrix $\\rho(t)$ with only diagonal elements in a given basis $\\{|n\\rangle\\}$, it may be treated as a classical mixture, i.e., a system which randomly occupies the basis states $|n\\rangle$ with probabilities $\\rho_{nn}(t)$. Fully equivalent to so-called smoothing in classical probability theory, subsequent probing of the occupation of the states $|n\\rangle$ improves our ability to retrodict what was the outcome of a projective state measurement at time $t$. Here, we show with experiments on a superconducting qubit that the smoothed probabilities do not, in the same way as the diagonal elements of $\\rho$, permit a classical mixture interpretation of the state of the system at the past time $t$.
Excess compressibility in binary liquid mixtures.
Aliotta, F; Gapiński, J; Pochylski, M; Ponterio, R C; Saija, F; Salvato, G
2007-06-14
Brillouin scattering experiments have been carried out on some mixtures of molecular liquids. From the measurement of the hypersonic velocities we have evaluated the adiabatic compressibility as a function of the volume fraction. We show how the quadratic form of the excess compressibility dependence on the solute volume fraction can be derived by simple statistical effects and does not imply any interaction among the components of the system other than excluded volume effects. This idea is supported by the comparison of the experimental results with a well-established prototype model, consisting of a binary mixture of hard spheres with a nonadditive interaction potential. This naive model turns out to be able to produce a very wide spectrum of structural and thermodynamic features depending on values of its parameters. An attempt has made to understand what kind of structural information can be gained through the analysis of the volume fraction dependence of the compressibility.
The Supervised Learning Gaussian Mixture Model
Institute of Scientific and Technical Information of China (English)
马继涌; 高文
1998-01-01
The traditional Gaussian Mixture Model(GMM)for pattern recognition is an unsupervised learning method.The parameters in the model are derived only by the training samples in one class without taking into account the effect of sample distributions of other classes,hence,its recognition accuracy is not ideal sometimes.This paper introduces an approach for estimating the parameters in GMM in a supervising way.The Supervised Learning Gaussian Mixture Model(SLGMM)improves the recognition accuracy of the GMM.An experimental example has shown its effectiveness.The experimental results have shown that the recognition accuracy derived by the approach is higher than those obtained by the Vector Quantization(VQ)approach,the Radial Basis Function (RBF) network model,the Learning Vector Quantization (LVQ) approach and the GMM.In addition,the training time of the approach is less than that of Multilayer Perceptrom(MLP).
Sum of Bernoulli Mixtures: Beyond Conditional Independence
Directory of Open Access Journals (Sweden)
Taehan Bae
2014-01-01
Full Text Available We consider the distribution of the sum of Bernoulli mixtures under a general dependence structure. The level of dependence is measured in terms of a limiting conditional correlation between two of the Bernoulli random variables. The conditioning event is that the mixing random variable is larger than a threshold and the limit is with respect to the threshold tending to one. The large-sample distribution of the empirical frequency and its use in approximating the risk measures, value at risk and conditional tail expectation, are presented for a new class of models which we call double mixtures. Several illustrative examples with a Beta mixing distribution, are given. As well, some data from the area of credit risk are fit with the models, and comparisons are made between the new models and also the classical Beta-binomial model.
Robust classification using mixtures of dependency networks
DEFF Research Database (Denmark)
Gámez, José A.; Mateo, Juan L.; Nielsen, Thomas Dyhre
2008-01-01
Dependency networks have previously been proposed as alternatives to e.g. Bayesian networks by supporting fast algorithms for automatic learning. Recently dependency networks have also been proposed as classiﬁcation models, but as with e.g. general probabilistic inference, the reported speed......-ups are often obtained at the expense of accuracy. In this paper we try to address this issue through the use of mixtures of dependency networks. To reduce learning time and improve robustness when dealing with data sparse classes, we outline methods for reusing calculations across mixture components. Finally......, the proposed model is empirically compared to other state-of-the-art classiﬁers, both in terms of accuracy and learning time....
Klein, Angela S; Skinner, Jeremy B; Hawley, Kristin M
2013-12-01
The current study examined two condensed adaptations of dialectical behavior therapy (DBT) for binge eating. Women with full- or sub-threshold variants of either binge eating disorder or bulimia nervosa were randomly assigned to individually supported self-monitoring using adapted DBT diary cards (DC) or group-based DBT, each 15 sessions over 16 weeks. DC sessions focused on problem-solving diary card completion issues, praising diary card completion, and supporting nonjudgmental awareness of eating-related habits and urges, but not formally teaching DBT skills. Group-based DBT included eating mindfulness, progressing through graded exposure; mindfulness, emotion regulation, and distress tolerance skills; and coaching calls between sessions. Both treatments evidenced large and significant improvements in binge eating, bulimic symptoms, and interoceptive awareness. For group-based DBT, ineffectiveness, drive for thinness, body dissatisfaction, and perfectionism also decreased significantly, with medium to large effect sizes. For DC, results were not significant but large in effect size for body dissatisfaction and medium in effect size for ineffectiveness and drive for thinness. Retention for both treatments was higher than recent trends for eating disorder treatment in fee-for-service practice and for similar clinic settings, but favored DC, with the greater attrition of group-based DBT primarily attributed to its more intensive and time-consuming nature, and dropout overall associated with less pretreatment impairment and greater interoceptive awareness. This preliminary investigation suggests that with both abbreviated DBT-based treatments, substantial improvement in core binge eating symptoms is possible, enhancing potential avenues for implementation beyond more time-intensive DBT.
Hurley, D.A.; Currie Murphy, L.; Hayes, D.; Hall, A. M.; Toomey, E; McDonough, S.M.; Lonsdale, C; Walsh, N.; Guerin, S.; Matthews, J.
2016-01-01
Background The Medical Research Council framework provides a useful general approach to designing and evaluating complex interventions, but does not provide detailed guidance on how to do this and there is little evidence of how this framework is applied in practice. This study describes the use of intervention mapping (IM) in the design of a theory-driven, group-based complex intervention to support self-management (SM) of patients with osteoarthritis (OA) and chronic low back pain (CLBP) in...
Lovato, Nicole; Lack, Leon; Wright, Helen; Kennaway, David J
2013-09-01
Cognitive behavior therapy is an effective nonpharmacologic treatment for insomnia. However, individualized administration is costly and often results in substantial variability in treatment response across individual patients, particularly so for older adults. Group-based administration has demonstrated impressive potential for a brief and inexpensive answer to the effective treatment of insomnia in the older population. It is important to identify potential predictors of response to such a treatment format to guide clinicians when selecting the most suitable treatment for their patients. The aim of our study was to identify factors that predict subjective sleep quality of older adults following group-based administration of cognitive behavior therapy for insomnia (CBT-I). Eighty-six adults (41 men; mean age, 64.10 y; standard deviation [SD], 6.80) with sleep maintenance or early morning awakening insomnia were selected from a community-based sample to participate in a 4-week group-based treatment program of CBT-I. Participants were required to complete 7-day sleep diaries and a comprehensive battery of questionnaires related to sleep quality and daytime functioning. Hierarchical multiple regression analyses were used to identify factors predicting subjective sleep quality immediately following treatment and at 3-month follow-up. Sleep diaries reported average nightly sleep efficiency (SE), which was used as the outcome measure of sleep quality. Participants with the greatest SE following treatment while controlling for pretreatment SE were relatively younger and had more confidence in their ability to sleep at pretreatment. These characteristics may be useful to guide clinicians when considering the use of a group-based CBT-I for sleep maintenance or early morning awakening insomnia in older adults. Copyright © 2013 Elsevier B.V. All rights reserved.
Smith Lisa; Pisinger Charlotta; Lau Cathrine; Ovesen Lars; Ladelund Steen; Kristoffersen Lis; Toft Ulla; Borch-Johnsen Knut; Jørgensen Torben
2008-01-01
Abstract Background Few studies have investigated the specific effect of single intervention components in randomized controlled trials. The purpose was to investigate the effect of adding group-based diet and exercise counselling to individual life-style counselling on long-term changes in dietary habits. Methods The study was a randomized controlled intervention study. From a general Danish population, aged 30 to 60 years (n = 61,301), two random sample were drawn (group A, n = 11,708; grou...
DEFF Research Database (Denmark)
Vadstrup, Eva S; Frølich, Anne; Perrild, Hans;
2011-01-01
Type 2 diabetes can seriously affect patients' health-related quality of life and their self-rated health. Most often, evaluation of diabetes interventions assess effects on glycemic control with little consideration of quality of life. The aim of the current study was to study the effectiveness...... of group-based rehabilitation versus individual counselling on health-related quality of life (HRQOL) and self-rated health in type 2 diabetes patients....
Wittkowski, Anja; Dowling, Hannah; Smith, Debbie M.
2016-01-01
As the preschool years are a formative period for long-term physical and mental health, this period is recognised as an important window for early effective intervention. Parenting behaviour is a key factor to target in order to optimise child development. Group-based interventions for parents are considered efficient and cost effective methods of early intervention and have been found to improve child behaviour and adjustment. Self-efficacy is key to behaviour change and as such parental sel...
DEFF Research Database (Denmark)
Vadstrup, Eva Soelberg; Frølich, Anne; Perrild, Hans Jørgen Duckert
2012-01-01
Type 2 diabetes can seriously affect patients' health-related quality of life and their self-rated health. Most often, evaluation of diabetes interventions assess effects on glycemic control with little consideration of quality of life. The aim of the current study was to study the effectiveness ...... of group-based rehabilitation versus individual counselling on health-related quality of life (HRQOL) and self-rated health in type 2 diabetes patients....
George, Daniel R.; Stuckey, Heather L.; Dillon, Caroline F.; Whitehead, Megan M.
2011-01-01
Purpose: To evaluate whether medical student participation in TimeSlips (TS), a creative group-based storytelling program, with persons affected by dementia would improve student attitudes toward this patient population. Design and Methods: Fifteen fourth-year medical students from Penn State College of Medicine participated in a month-long regimen of TS sessions at a retirement community. Student course evaluations were analyzed at the conclusion of the program to examine perceived qualitati...
Lattice Model for water-solute mixtures
Furlan, A. P.; Almarza, N. G.; M. C. Barbosa
2016-01-01
A lattice model for the study of mixtures of associating liquids is proposed. Solvent and solute are modeled by adapting the associating lattice gas (ALG) model. The nature of interaction solute/solvent is controlled by tuning the energy interactions between the patches of ALG model. We have studied three set of parameters, resulting on, hydrophilic, inert and hydrophobic interactions. Extensive Monte Carlo simulations were carried out and the behavior of pure components and the excess proper...
Fluorous Mixture Synthesis of Asymmetric Dendrimers
Jiang, Zhong-Xing; Yu, Yihua Bruce
2010-01-01
A divergent fluorous mixture synthesis (FMS) of asymmetric fluorinated dendrimers has been developed. Four generations of fluorinated dendrimers with the same fluorinated moiety were prepared with high efficiency, yield and purity. Comparison of the physicochemical properties of these dendrimers provided valuable information for their application and future optimization. This strategy has not only provided a practical method for the synthesis and purification of dendrimers, but also established the possibility of utilizing the same fluorinated moiety for FMS. PMID:20170088
Nitrocarburising in ammonia-hydrocarbon gas mixtures
DEFF Research Database (Denmark)
Pedersen, Hanne; Christiansen, Thomas; Somers, Marcel A. J.
2010-01-01
The present work investigates the possibility of nitrocarburising in ammonia-acetylene-hydrogen and ammoniapropene- hydrogen gas mixtures, where unsaturated hydrocarbon gas is the carbon source during nitrocarburising. Consequently, nitrocarburising is carried out in a reducing atmosphere...... microscopy and X-ray diffraction analysis. It is shown that the use of unsaturated hydrocarbon gas in nitrocarburising processes is a viable alternative to traditional nitrocarburising methods....
Nitrocarburizing in ammonia-hydrocarbon gas mixtures
DEFF Research Database (Denmark)
Pedersen, Hanne; Christiansen, Thomas; Somers, Marcel A. J.
2011-01-01
The present work investigates the possibility of nitrocarburising in ammonia-acetylene-hydrogen and ammonia-propene-hydrogen gas mixtures, where unsaturated hydrocarbon gas is the carbon source during nitrocarburising. Consequently, nitrocarburising is carried out in a reducing atmosphere...... microscopy and X-ray diffraction analysis. It is shown that the use of unsaturated hydrocarbon gas in nitrocarburising processes is a viable alternative to traditional nitrocarburising methods....
Endocrine activity of mycotoxins and mycotoxin mixtures.
Demaegdt, Heidi; Daminet, Britt; Evrard, Annick; Scippo, Marie-Louise; Muller, Marc; Pussemier, Luc; Callebaut, Alfons; Vandermeiren, Karine
2016-10-01
Reporter gene assays incorporating nuclear receptors (estrogen, androgen, thyroid β and PPARγ2) have been implemented to assess the endocrine activity of 13 mycotoxins and their mixtures. As expected, zearalenone and its metabolites α-zearalenol and β- zearalenol turned out to have the strongest estrogenic potency (EC50 8,7 10-10 ± 0,8; 3,1 10-11 ± 0,5 and 1,3 10-8 ± 0,3 M respectively). The metabolite of deoxynivalenol, 3-acetyl-deoxynivalenol also had estrogenic activity (EC50 3,8 10-7 ± 1,1 M). Furthermore, most of the mycotoxins (and their mixtures) showed anti-androgenic effects (15-acetyldeoxynivalenol, 3-acetyl-deoxynivalenol and α-zearalenol with potencies within one order of magnitude of that of the reference compound flutamide). In particular, deoxynivalenol and 15-acetyl-deoxynivalenol acted as antagonists for the PPARy2 receptor. When testing mixtures of mycotoxins on the same cell systems, we showed that most of the mixtures reacted as predicted by the concentration addition (CA) theory. Generally, the CA was within the 95% confidence interval of the observed ones, only minor deviations were detected. Although these reporter gene tests cannot be directly extrapolated in vivo, they can be the basis for further research. Especially the additive effects of ZEN and its metabolites are of importance and could have repercussions in vivo.
Method for Predicting Hypergolic Mixture Flammability Limits
2017-02-01
AFRL-AFOSR-UK-TR-2017-0003 Method for Predicting Hypergolic Mixture Flammability Limits Laurent Catoire Ecole Nat Sup De Techniques Avancees Final...TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Ecole Nat Sup De Techniques Avancees 828, Boulevard Des Marechaux...provides a mitigation strategy to reduce the risk of failure for the insertion of IL fuel technology into the small satellite market as AFRL/RQRP
Population mixture model for nonlinear telomere dynamics
Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl
2008-12-01
Telomeres are DNA repeats protecting chromosomal ends which shorten with each cell division, eventually leading to cessation of cell growth. We present a population mixture model that predicts an exponential decrease in telomere length with time. We analytically solve the dynamics of the telomere length distribution. The model provides an excellent fit to available telomere data and accounts for the previously unexplained observation of telomere elongation following stress and bone marrow transplantation, thereby providing insight into the nature of the telomere clock.
Hierarchical mixture models for assessing fingerprint individuality
Dass, Sarat C.; Li, Mingfei
2009-01-01
The study of fingerprint individuality aims to determine to what extent a fingerprint uniquely identifies an individual. Recent court cases have highlighted the need for measures of fingerprint individuality when a person is identified based on fingerprint evidence. The main challenge in studies of fingerprint individuality is to adequately capture the variability of fingerprint features in a population. In this paper hierarchical mixture models are introduced to infer the extent of individua...
Odgers-Jewell, Kate; Isenring, Elisabeth A; Thomas, Rae; Reidlinger, Dianne P
2017-01-01
The objective of this study was to explore the experiences of individuals who participated in a group-based education program, including their motivators in relation to their diabetes management, and the perceived impact of group interactions on participants' experiences and motivation for self-management. Understanding individuals diagnosed with diabetes experiences of group-based education for the management of type 2 diabetes mellitus may guide the development and facilitation of these programs. Semi-structured interviews were conducted with all individuals who participated in the intervention. Using thematic analysis underpinned by self-determination theory, we developed themes that explored participants' motivators in relation to diabetes management and the impact of group interactions on their experiences and motivation. The key themes included knowledge, experience, group interactions and motivation. Participants perceived that the group interactions facilitated further learning and increased motivation, achieved through normalization, peer identification or by talking with, and learning from the experience of others. The results support the use of patient-centred programs that prioritize group interactions over the didactic presentation of content, which may address relevant psychological needs of people diagnosed with type 2 diabetes mellitus, and improve their motivation and health behaviours. Future group-based education programs may benefit from the use of self-determination theory as a framework for intervention design to enhance participant motivation.
Broszkiewicz, Marzenna; Drygas, Wojciech
2009-01-01
The efficacy and cost-effectiveness of behavioral treatments compare favorably with the pharmacotherapies and community-based interventions. Group-based behavioral programs have been scientifically proven as the effective smoking cessation intervention. Aim of the study was identifying predictors of the efficacy of smoking cessation in health factors: health status and motivation and doctor's advice. Program is a multicomponent group-based behavioral intervention with the elements recommended by the US Public Health Service as the most effective. 517 smokers were included into the program in the outpatient clinic setting in years 2001-2007. A point prevalence abstinence (PPA) was estimated by self-reported smoking cessation. Three homogeneous groups of patients according to their status health were established: participants with tobacco-related diseases n = 182, with psychiatric disorders n = 101 and healthy ones n = 150. 59.6% of participants stopped smoking during four-week program. Program was effective in smoking cessation both for sick and healthy participants. Motivational factors, among others health motivation did not distinguish for whole population as well as for participants with tobacco-related diseases. Lack of doctor's advice increased efficacy of smoking cessation both for the whole population and for group with tobacco-related diseases. Nor health status and motivation neither doctor's advice were predictors of behavioral group-based treatment for tobacco smokers.
Statistical mechanical theory of fluid mixtures
Zhao, Yueqiang; Wu, Zhengming; Liu, Weiwei
2014-01-01
A general statistical mechanical theory of fluid mixtures (liquid mixtures and gas mixtures) is developed based on the statistical mechanical expression of chemical potential of components in the grand canonical ensemble, which gives some new relationships between thermodynamic quantities (equilibrium ratio Ki, separation factor α and activity coefficient γi) and ensemble average potential energy u for one molecule. The statistical mechanical expressions of separation factor α and activity coefficient γi derived in this work make the fluid phase equilibrium calculations can be performed by molecular simulation simply and efficiently, or by the statistical thermodynamic approach (based on the saturated-vapor pressure of pure substance) that does not need microscopic intermolecular pair potential functions. The physical meaning of activity coefficient γi in the liquid phase is discussed in detail from a viewpoint of molecular thermodynamics. The calculated Vapor-Liquid Equilibrium (VLE) properties of argon-methane, methanol-water and n-hexane-benzene systems by this model fit well with experimental data in references, which indicates that this model is accurate and reliable in the prediction of VLE properties for small, large and strongly associating molecules; furthermore the statistical mechanical expressions of separation factor α and activity coefficient γi have good compatibility with classical thermodynamic equations and quantum mechanical COSMO-SAC approach.
Familial searching on DNA mixtures with dropout.
Slooten, K
2016-05-01
Familial searching, the act of searching a database for a relative of an unknown individual whose DNA profile has been obtained, is usually restricted to cases where the DNA profile of that person has been unambiguously determined. Therefore, it is normally applied only with a good quality single source profile as starting point. In this article we investigate the performance of the method if applied to mixtures with and without allelic dropout, when likelihood ratios are computed with a semi-continuous (binary) model. We show that mixtures with dropout do not necessarily perform worse than mixtures without, especially if some separation between the donors is possible due to their different dropout probabilities. The familial searching true and false positive rates of mixed profiles on 15 loci are in some cases better than those of single source profiles on 10 loci. Thus, the information loss due to the fact that the person of interest's DNA has been mixed with that of other, and is affected by dropout, can be less than the loss of information corresponding to having 5 fewer loci available for a single source trace. Profiles typed on 10 autosomal loci are often involved in familial searching casework since many databases, including the Dutch one, in part consist of such profiles. Therefore, from this point of view, there seems to be no objection to extend familial searching to mixed or degraded profiles.
Ethane-xenon mixtures under shock conditions
Flicker, Dawn; Magyar, Rudolph; Root, Seth; Cochrane, Kyle; Mattsson, Thomas
2015-06-01
Mixtures of light and heavy elements arise in inertial confinement fusion and planetary science. We present results on the physics of molecular scale mixing through a validation study of equation of state (EOS) properties. Density functional theory molecular dynamics (DFT/QMD) at elevated-temperature and pressure is used to obtain the properties of pure xenon, ethane, and various compressed mixture compositions along their principal Hugoniots. To validate the QMD simulations, we performed high-precision shock compression experiments using Sandia's Z-Machine. A bond tracking analysis of the simulations correlates the sharp rise in the Hugoniot curve with completion of dissociation in ethane. DFT-based simulation results compare well with experimental data and are used to provide insight into the dissociation as a function of mixture composition. Interestingly, we find that the compression ratio for complete dissociation is similar for ethane, Xe-ethane, polymethyl-pentene, and polystyrene, suggesting that a limiting compression exists for C-C bonded systems. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Company, Security Administration under contract DE-AC04-94AL85000.
Crowding in polymer-nanoparticle mixtures.
Denton, Alan R
2014-01-01
The cell nucleus is a highly crowded environment, filled with a multicomponent, polydisperse mixture of biopolymers and nuclear bodies dispersed in a viscous solvent. With volume fractions approaching 20%, excluded-volume interactions play a key role in determining the structure, dynamics, and function of macromolecules in vivo. Under such constraints, the ensembles of macromolecular conformations can differ substantially from those prevailing in dilute solutions. Crowding thus can affect protein and RNA folding, conformational stability, and reaction kinetics, as well as phase stability of macromolecular mixtures. From the perspective of soft matter physics, this chapter reviews recent studies on crowding in polymer-nanoparticle mixtures, seeking to demonstrate the utility of simple physical models for addressing challenging issues in cell biology. The focus is on applications of free-volume theory and Monte Carlo simulation, based on geometrical models of polymers as fluctuating spheres or ellipsoids. Ideal polymer coils respond to hard-sphere crowding agents by compactifying, reducing their radius of gyration, and becoming more spherical. At sufficiently high concentrations, polymers and crowders phase-separate. The goal of this review is to identify universal principles governing macromolecular crowding and to establish a general framework for future explorations of more realistic models that may include nonsteric (e.g., electrostatic) interactions. © 2014 Elsevier Inc. All rights reserved.
Tandem mass spectrometry: analysis of complex mixtures
Energy Technology Data Exchange (ETDEWEB)
Singleton, K.E.
1985-01-01
Applications of tandem mass spectrometry (MS/MS) for the analysis of complex mixtures results in increased specificity and selectivity by using a variety of reagent gases in both negative and positive ion modes. Natural isotopic abundance ratios were examined in both simple and complex mixtures using parent, daughter and neutral loss scans. MS/MS was also used to discover new compounds. Daughter scans were used to identify seven new alkaloids in a cactus species. Three of these alkaloids were novel compounds, and included the first simple, fully aromatic isoquinoline alkaloids reported in Cactaceae. MS/MS was used to characterize the chemical reaction products of coal in studies designed to probe its macromolecular structure. Negative ion chemical ionization was utilized to study reaction products resulting from the oxidation of coal. Possible structural units in the precursor coal were predicted based on the reaction products identified, aliphatic and aromatic acids and their anhydrides. The MS/MS method was also used to characterize reaction products resulting from coal liquefaction and/or extraction. These studies illustrate the types of problems for which MS/MS is useful. Emphasis has been placed on characterization of complex mixtures by selecting experimental parameters which enhance the information obtained. The value of using MS/MS in conjunction with other analytical techniques as well as the chemical pretreatment is demonstrated.
Confusion of concepts in mixture toxicology.
Könemann, W H; Pieters, M N
1996-01-01
Regulatory limit values are generally set for single compounds. However, humans are exposed both simultaneously and sequentially to a wide variety of compounds. Some concepts on mixture toxicology are discussed in this introduction to the European Conference on Combination Toxicology. Studies on mixtures are often accompanied by statements about the type of combined action, which can be, for example, additive, synergistic or antagonistic. Unfortunately, comparison of results is hardly possible for various reasons. First, the terminology for indicating combined action is far from consistent. Bearing this in mind, researchers should be explicit in the definitions of terms. Secondly, depending on the model, different conclusions may be drawn from the same results. It is therefore important to provide clear definitions of the null hypothesis. Thirdly, adequate statistical methods should be used for testing the null hypothesis. In the past, many mixtures studies either used no statistics or used statistics incorrectly. Last, but not least, the study should be designed in such a way that it should be possible to obtain clear answers. In this introduction, it is stressed that environmental toxicologists should focus on the low-dose region of the dose-effect curves. It appears that interactions are less plausible at low doses. Dose additivity, however, cannot be excluded.
Mixture risk assessment: a case study of Monsanto experiences.
Nair, R S; Dudek, B R; Grothe, D R; Johannsen, F R; Lamb, I C; Martens, M A; Sherman, J H; Stevens, M W
1996-01-01
Monsanto employs several pragmatic approaches for evaluating the toxicity of mixtures. These approaches are similar to those recommended by many national and international agencies. When conducting hazard and risk assessments, priority is always given to using data collected directly on the mixture of concern. To provide an example of the first tier of evaluation, actual data on acute respiratory irritation studies on mixtures were evaluated to determine whether the principle of additivity was applicable to the mixture evaluated. If actual data on the mixture are unavailable, extrapolation across similar mixtures is considered. Because many formulations are quite similar in composition, the toxicity data from one mixture can be extended to a closely related mixture in a scientifically justifiable manner. An example of a family of products where such extrapolations have been made is presented to exemplify this second approach. Lastly, if data on similar mixtures are unavailable, data on component fractions are used to predict the toxicity of the mixture. In this third approach, process knowledge and scientific judgement are used to determine how the known toxicological properties of the individual fractions affect toxicity of the mixture. Three examples of plant effluents where toxicological data on fractions were used to predict the toxicity of the mixture are discussed. The results of the analysis are used to discuss the predictive value of each of the above mentioned toxicological approaches for evaluating chemical mixtures.
Physical Compatibility of Propofol-Sufentanil Mixtures.
Zbytovská, Jarmila; Gallusová, Jana; Vidlářová, Lucie; Procházková, Kamila; Šimek, Jan; Štěpánek, František
2017-03-01
Combined infusions of propofol and sufentanil preparations are frequently used in clinical practice to induce anesthesia and analgesia. However, the stability of propofol emulsions can be affected by dilution with another preparation, sometimes leading to particle coalescence and enlargement. Such unwanted effects can lead to fat embolism syndrome after intravenous application. This study describes the physical stability of 5 commercially available propofol preparations mixed with sufentanil citrate solutions. Two common markers of emulsion stability were used in this study; namely, the zeta potential and size distribution of the emulsion droplets. Both were measured using dynamic light scattering. The data for the pure propofol preparations and their mixtures with sufentanil citrate solution were compared. The absolute value of zeta potential decreased in 4 of the 5 propofol preparations after they had been mixed with sufentanil citrate. This effect indicates a lowering of repulsive interactions between the emulsion droplets. Although this phenomenon tends to cause agglomeration, none of the studied mixtures displayed a substantial increase in droplet size within 24 hours of blending. However, our long-term stability study revealed the instability of some of the propofol-sufentanil samples. Two of the 5 studied mixtures displayed a continual increase in particle size. The same 2 preparations showed the greatest reductions in the absolute value of zeta potential, thereby confirming the correlation of both measurement methods. The increase in particle size was more distinct in the samples stored at higher temperatures and with higher sufentanil concentrations. To ensure the microbial stability of an emulsion infusion preparation, clinical regulations require that such preparations should be applied to patients within 12 hours of opening. In this respect, we can confirm that during this period, none of the studied propofol-sufentanil mixtures displayed any physical
Separation of gas mixtures by supported complexes
Energy Technology Data Exchange (ETDEWEB)
Nelson, D.A.; Lilga, M.A.; Hallen, R.T.; Lyke, S.E.
1986-08-01
The goal of this program is to determine the feasibility of solvent-dissolved coordination complexes for the separation of gas mixtures under bench-scale conditions. In particular, mixtures such as low-Btu gas are examined for CO and H/sub 2/ separation. Two complexes, Pd/sub 2/(dpm)/sub 2/Br/sub 2/ and Ru(CO)/sub 2/(PPh/sub 3/)/sub 3/, were examined in a bench-scale apparatus for the separation of binary (CO-N/sub 2/ or H/sub 2/-N/sub 2/) and quinary (H/sub 2/, CO, CO/sub 2/, CH/sub 4/, and N/sub 2/) mixtures. The separation of CO-N/sub 2/ was enhanced by the presence of the palladium complex in the 1,1,2-trichloroethane (TCE) solvent, especially at high gas and low liquid rates. The five-component gas mixture separation with the palladium complex in TCE provided quite unexpected results based on physical solubility and chemical coordination. The complex retained CO, while the solvent retained CO/sub 2/, CH/sub 4/, and N/sub 2/ to varying degrees. This allowed the hydrogen content to be enhanced due to its low solubility in TCE and inertness to the complex. Thus, a one-step, hydrogen separation can be achieved from gas mixtures with compositions similar to that of oxygen-blown coal gas. A preliminary economic evaluation of hydrogen separation was made for a system based on the palladium complex. The palladium system has a separation cost of 50 to 60 cents/MSCF with an assumed capital investment of $1.60/MSCF of annual capacity charged at 30% per year. This assumes a 3 to 4 year life for the complex. Starting with a 90% hydrogen feed, PSA separation costs are in the range of 30 to 50 cents/MSCF. The ruthenium complex was not as successful for hydrogen or carbon monoxide separation due to unfavorable kinetics. The palladium complex was found to strip hydrogen gas from H/sub 2/S. The complex could be regenerated with mild oxidants which removed the sulfur as SO/sub 2/. 24 refs., 26 figs., 10 tabs.
Mixtures as a fungicide resistance management tactic.
van den Bosch, Frank; Paveley, Neil; van den Berg, Femke; Hobbelen, Peter; Oliver, Richard
2014-12-01
We have reviewed the experimental and modeling evidence on the use of mixtures of fungicides of differing modes of action as a resistance management tactic. The evidence supports the following conclusions. 1. Adding a mixing partner to a fungicide that is at-risk of resistance (without lowering the dose of the at-risk fungicide) reduces the rate of selection for fungicide resistance. This holds for the use of mixing partner fungicides that have either multi-site or single-site modes of action. The resulting predicted increase in the effective life of the at-risk fungicide can be large enough to be of practical relevance. The more effective the mixing partner (due to inherent activity and/or dose), the larger the reduction in selection and the larger the increase in effective life of the at-risk fungicide. 2. Adding a mixing partner while lowering the dose of the at-risk fungicide reduces the selection for fungicide resistance, without compromising effective disease control. The very few studies existing suggest that the reduction in selection is more sensitive to lowering the dose of the at-risk fungicide than to increasing the dose of the mixing partner. 3. Although there are very few studies, the existing evidence suggests that mixing two at-risk fungicides is also a useful resistance management tactic. The aspects that have received too little attention to draw generic conclusions about the effectiveness of fungicide mixtures as resistance management strategies are as follows: (i) the relative effect of the dose of the two mixing partners on selection for fungicide resistance, (ii) the effect of mixing on the effective life of a fungicide (the time from introduction of the fungicide mode of action to the time point where the fungicide can no longer maintain effective disease control), (iii) polygenically determined resistance, (iv) mixtures of two at-risk fungicides, (v) the emergence phase of resistance evolution and the effects of mixtures during this phase
Investigation of rheological properties of mixtures of soft ice cream
Directory of Open Access Journals (Sweden)
L. V. Golubeva
2012-01-01
Full Text Available The paper presents the study of the rheological properties of multicomponent mixtures for soft ice cream enriched with various stabilizers to facilitate evaluation and selection of the optimal mixture.
Methods for Assessing Curvature and Interaction in Mixture Experiments
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.(BATTELLE (PACIFIC NW LAB)); Hicks, Ruel D.(ASSOC WESTERN UNIVERSITY); Szychowski, Jeffrey M.(ASSOC WESTERN UNIVERSITY); Loeppky, Jason L.(ASSOC WESTERN UNIVERSITY)
2002-05-01
The terms curvature and interaction traditionally are not defined or used in the context of mixture experiments because curvature and interaction effects are partially confounded due to the mixture constrain that the component proportions sum to 1.
Mixture Density Mercer Kernels: A Method to Learn Kernels
National Aeronautics and Space Administration — This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian...
Optimal (Solvent) Mixture Design through a Decomposition Based CAMD methodology
DEFF Research Database (Denmark)
Achenie, L.; Karunanithi, Arunprakash T.; Gani, Rafiqul
2004-01-01
Computer Aided Molecular/Mixture design (CAMD) is one of the most promising techniques for solvent design and selection. A decomposition based CAMD methodology has been formulated where the mixture design problem is solved as a series of molecular and mixture design sub-problems. This approach is...... is able to overcome most of the difficulties associated with the solution of mixture design problems. The new methodology has been illustrated with the help of a case study involving the design of solvent-anti solvent binary mixtures for crystallization of Ibuprofen.......Computer Aided Molecular/Mixture design (CAMD) is one of the most promising techniques for solvent design and selection. A decomposition based CAMD methodology has been formulated where the mixture design problem is solved as a series of molecular and mixture design sub-problems. This approach...
Investigation of a Gamma model for mixture STR samples
DEFF Research Database (Denmark)
Christensen, Susanne; Bøttcher, Susanne Gammelgaard; Lauritzen, Steffen L.
The behaviour of PCR Amplification Kit, when used for mixture STR samples, is investigated. A model based on the Gamma distribution is fitted to the amplifier output for constructed mixtures, and the assumptions of the model is evaluated via residual analysis.......The behaviour of PCR Amplification Kit, when used for mixture STR samples, is investigated. A model based on the Gamma distribution is fitted to the amplifier output for constructed mixtures, and the assumptions of the model is evaluated via residual analysis....
Quantum phases of Fermi-Fermi mixtures in optical lattices
Iskin, M.; de Melo, C. A. R. Sa
2007-01-01
The ground state phase diagram of Fermi-Fermi mixtures in optical lattices is analyzed as a function of interaction strength, population imbalance, filling fraction and tunneling parameters. It is shown that population imbalanced Fermi-Fermi mixtures reduce to strongly interacting Bose-Fermi mixtures in the molecular limit, in sharp contrast to homogeneous or harmonically trapped systems where the resulting Bose-Fermi mixture is weakly interacting. Furthermore, insulating phases are found in ...
Continuous mixtures with bathtub-shaped failure rates
Block, Henry W.; LI, YULIN; Savits, Thomas H.; Wang, Jie
2008-01-01
The failure rate of a mixture of even the most standard distributions used in reliability can have a complicated shape. However, failure rates of mixtures of two carefully selected distributions will have the well-known bathtub shape. Here we show that mixtures of whole families of distribtions can have a bathtub-shaped failure rate.
Lessons learned in managing alfalfa-grass mixtures
Grass-alfalfa mixtures have a number of benefits that make them attractive to producers. However, they can be problematic to establish and maintain. Research programs have made progress in understanding the benefits and challenges of alfalfa-grass mixtures. Mixtures may have greater winter survival ...
40 CFR 721.5769 - Mixture of nitrated alkylated phenols.
2010-07-01
... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Mixture of nitrated alkylated phenols... Substances § 721.5769 Mixture of nitrated alkylated phenols. (a) Chemical substance and significant new uses subject to reporting. (1) The chemical substance identified as a mixture of nitrated alkylated...
21 CFR 864.8625 - Hematology quality control mixture.
2010-04-01
... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Hematology quality control mixture. 864.8625 Section 864.8625 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES... quality control mixture. (a) Identification. A hematology quality control mixture is a device used...
TEMPERATURE INFLUENCE ON PHASE STABILITY OF ETHANOL-GASOLINE MIXTURES
Directory of Open Access Journals (Sweden)
Valerian Cerempei
2011-06-01
Full Text Available The article investigates phase stability of ethanol-gasoline mixtures depending on their composition, water concentration in ethanol and ethanol-gasoline mixture and temperature. There have been determined the perfect functioning conditions of spark ignition engines fueled with ethanol-gasoline mixtures.
46 CFR 154.1735 - Methyl acetylene-propadiene mixture.
2010-10-01
... 46 Shipping 5 2010-10-01 2010-10-01 false Methyl acetylene-propadiene mixture. 154.1735 Section... Operating Requirements § 154.1735 Methyl acetylene-propadiene mixture. (a) The composition of the methyl acetylene-propadiene mixture at loading must be within the following limits or specially approved by...