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

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Skrondal, Anders; Rabe-Hesketh, Sophia

2004-01-01

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

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

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

2009-01-01

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

Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

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Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

2017-01-01

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses

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Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini

2012-01-01

The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…

The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities

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Bauer, Daniel J.; Curran, Patrick J.

2004-01-01

Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

Partial Granger causality--eliminating exogenous inputs and latent variables.

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Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng

2008-07-15

Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.

Hidden Markov latent variable models with multivariate longitudinal data.

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Song, Xinyuan; Xia, Yemao; Zhu, Hongtu

2017-03-01

Cocaine addiction is chronic and persistent, and has become a major social and health problem in many countries. Existing studies have shown that cocaine addicts often undergo episodic periods of addiction to, moderate dependence on, or swearing off cocaine. Given its reversible feature, cocaine use can be formulated as a stochastic process that transits from one state to another, while the impacts of various factors, such as treatment received and individuals' psychological problems on cocaine use, may vary across states. This article develops a hidden Markov latent variable model to study multivariate longitudinal data concerning cocaine use from a California Civil Addict Program. The proposed model generalizes conventional latent variable models to allow bidirectional transition between cocaine-addiction states and conventional hidden Markov models to allow latent variables and their dynamic interrelationship. We develop a maximum-likelihood approach, along with a Monte Carlo expectation conditional maximization (MCECM) algorithm, to conduct parameter estimation. The asymptotic properties of the parameter estimates and statistics for testing the heterogeneity of model parameters are investigated. The finite sample performance of the proposed methodology is demonstrated by simulation studies. The application to cocaine use study provides insights into the prevention of cocaine use. © 2016, The International Biometric Society.

Linear latent variable models: the lava-package

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Holst, Klaus Kähler; Budtz-Jørgensen, Esben

2013-01-01

are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation......An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...

Reduction of Non-stationary Noise using a Non-negative Latent Variable Decomposition

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Schmidt, Mikkel Nørgaard; Larsen, Jan

2008-01-01

We present a method for suppression of non-stationary noise in single channel recordings of speech. The method is based on a non-negative latent variable decomposition model for the speech and noise signals, learned directly from a noisy mixture. In non-speech regions an over complete basis...... is learned for the noise that is then used to jointly estimate the speech and the noise from the mixture. We compare the method to the classical spectral subtraction approach, where the noise spectrum is estimated as the average over non-speech frames. The proposed method significantly outperforms...

The application of seasonal latent variable in forecasting electricity demand as an alternative method

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Sumer, Kutluk Kagan; Goktas, Ozlem; Hepsag, Aycan

2009-01-01

In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with seasonal latent variable in forecasting electricity demand by using data that belongs to 'Kayseri and Vicinity Electricity Joint-Stock Company' over the 1997:1-2005:12 periods. This study tries to examine the advantages of forecasting with ARIMA, SARIMA methods and with the model has seasonal latent variable to each other. The results support that ARIMA and SARIMA models are unsuccessful in forecasting electricity demand. The regression model with seasonal latent variable used in this study gives more successful results than ARIMA and SARIMA models because also this model can consider seasonal fluctuations and structural breaks

New approaches for examining associations with latent categorical variables: applications to substance abuse and aggression.

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Feingold, Alan; Tiberio, Stacey S; Capaldi, Deborah M

2014-03-01

Assessments of substance use behaviors often include categorical variables that are frequently related to other measures using logistic regression or chi-square analysis. When the categorical variable is latent (e.g., extracted from a latent class analysis [LCA]), classification of observations is often used to create an observed nominal variable from the latent one for use in a subsequent analysis. However, recent simulation studies have found that this classical 3-step analysis championed by the pioneers of LCA produces underestimates of the associations of latent classes with other variables. Two preferable but underused alternatives for examining such linkages-each of which is most appropriate under certain conditions-are (a) 3-step analysis, which corrects the underestimation bias of the classical approach, and (b) 1-step analysis. The purpose of this article is to dissuade researchers from conducting classical 3-step analysis and to promote the use of the 2 newer approaches that are described and compared. In addition, the applications of these newer models-for use when the independent, the dependent, or both categorical variables are latent-are illustrated through substantive analyses relating classes of substance abusers to classes of intimate partner aggressors.

Abstract: Inference and Interval Estimation for Indirect Effects With Latent Variable Models.

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Falk, Carl F; Biesanz, Jeremy C

2011-11-30

Models specifying indirect effects (or mediation) and structural equation modeling are both popular in the social sciences. Yet relatively little research has compared methods that test for indirect effects among latent variables and provided precise estimates of the effectiveness of different methods. This simulation study provides an extensive comparison of methods for constructing confidence intervals and for making inferences about indirect effects with latent variables. We compared the percentile (PC) bootstrap, bias-corrected (BC) bootstrap, bias-corrected accelerated (BC a ) bootstrap, likelihood-based confidence intervals (Neale & Miller, 1997), partial posterior predictive (Biesanz, Falk, and Savalei, 2010), and joint significance tests based on Wald tests or likelihood ratio tests. All models included three reflective latent variables representing the independent, dependent, and mediating variables. The design included the following fully crossed conditions: (a) sample size: 100, 200, and 500; (b) number of indicators per latent variable: 3 versus 5; (c) reliability per set of indicators: .7 versus .9; (d) and 16 different path combinations for the indirect effect (α = 0, .14, .39, or .59; and β = 0, .14, .39, or .59). Simulations were performed using a WestGrid cluster of 1680 3.06GHz Intel Xeon processors running R and OpenMx. Results based on 1,000 replications per cell and 2,000 resamples per bootstrap method indicated that the BC and BC a bootstrap methods have inflated Type I error rates. Likelihood-based confidence intervals and the PC bootstrap emerged as methods that adequately control Type I error and have good coverage rates.

Latent variable method for automatic adaptation to background states in motor imagery BCI

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Dagaev, Nikolay; Volkova, Ksenia; Ossadtchi, Alexei

2018-02-01

Objective. Brain-computer interface (BCI) systems are known to be vulnerable to variabilities in background states of a user. Usually, no detailed information on these states is available even during the training stage. Thus there is a need in a method which is capable of taking background states into account in an unsupervised way. Approach. We propose a latent variable method that is based on a probabilistic model with a discrete latent variable. In order to estimate the model’s parameters, we suggest to use the expectation maximization algorithm. The proposed method is aimed at assessing characteristics of background states without any corresponding data labeling. In the context of asynchronous motor imagery paradigm, we applied this method to the real data from twelve able-bodied subjects with open/closed eyes serving as background states. Main results. We found that the latent variable method improved classification of target states compared to the baseline method (in seven of twelve subjects). In addition, we found that our method was also capable of background states recognition (in six of twelve subjects). Significance. Without any supervised information on background states, the latent variable method provides a way to improve classification in BCI by taking background states into account at the training stage and then by making decisions on target states weighted by posterior probabilities of background states at the prediction stage.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

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Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and

Inverse Ising problem in continuous time: A latent variable approach

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Donner, Christian; Opper, Manfred

2017-12-01

We consider the inverse Ising problem: the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form which allows for simple iterative inference algorithms with analytical updates. The variables are (1) Poisson variables to linearize an exponential term which is typical for point process likelihoods and (2) Pólya-Gamma variables, which make the likelihood quadratic in the coupling parameters. Using the augmented likelihood, we derive an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimate of network parameters. Using a third set of latent variables we extend the EM algorithm to sparse couplings via L1 regularization. Finally, we develop an efficient approximate Bayesian inference algorithm using a variational approach. We demonstrate the performance of our algorithms on data simulated from an Ising model. For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.

Confidence Intervals for a Semiparametric Approach to Modeling Nonlinear Relations among Latent Variables

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Pek, Jolynn; Losardo, Diane; Bauer, Daniel J.

2011-01-01

Compared to parametric models, nonparametric and semiparametric approaches to modeling nonlinearity between latent variables have the advantage of recovering global relationships of unknown functional form. Bauer (2005) proposed an indirect application of finite mixtures of structural equation models where latent components are estimated in the…

Explicit estimating equations for semiparametric generalized linear latent variable models

KAUST Repository

Ma, Yanyuan

2010-07-05

We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n consistency and asymptotic normality. We explain the computational implementation of our method and illustrate the numerical performance of the estimators in finite sample situations via extensive simulation studies. The advantage of our estimators over the existing likelihood approach is also shown via numerical comparison. We employ the method to analyse a real data example from economics. © 2010 Royal Statistical Society.

Incorporating Latent Variables into Discrete Choice Models - A Simultaneous Estimation Approach Using SEM Software

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Dirk Temme

2008-12-01

Full Text Available Integrated choice and latent variable (ICLV models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

On the Integrity of Online Testing for Introductory Statistics Courses: A Latent Variable Approach

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Alan Fask

2015-04-01

Full Text Available There has been a remarkable growth in distance learning courses in higher education. Despite indications that distance learning courses are more vulnerable to cheating behavior than traditional courses, there has been little research studying whether online exams facilitate a relatively greater level of cheating. This article examines this issue by developing an approach using a latent variable to measure student cheating. This latent variable is linked to both known student mastery related variables and variables unrelated to student mastery. Grade scores from a proctored final exam and an unproctored final exam are used to test for increased cheating behavior in the unproctored exam

Measurement Uncertainty in Racial and Ethnic Identification among Adolescents of Mixed Ancestry: A Latent Variable Approach

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Tracy, Allison J.; Erkut, Sumru; Porche, Michelle V.; Kim, Jo; Charmaraman, Linda; Grossman, Jennifer M.; Ceder, Ineke; Garcia, Heidie Vazquez

2010-01-01

In this article, we operationalize identification of mixed racial and ethnic ancestry among adolescents as a latent variable to (a) account for measurement uncertainty, and (b) compare alternative wording formats for racial and ethnic self-categorization in surveys. Two latent variable models were fit to multiple mixed-ancestry indicator data from…

Assessing Factors Related to Waist Circumference and Obesity: Application of a Latent Variable Model

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Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah

2015-01-01

Background. Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Methods. Data included 18,990 Iranian individuals aged 20–65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variabl...

A latent class distance association model for cross-classified data with a categorical response variable.

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Vera, José Fernando; de Rooij, Mark; Heiser, Willem J

2014-11-01

In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low-dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented. © 2014 The British Psychological Society.

Childhood malnutrition in Egypt using geoadditive Gaussian and latent variable models.

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Khatab, Khaled

2010-04-01

Major progress has been made over the last 30 years in reducing the prevalence of malnutrition amongst children less than 5 years of age in developing countries. However, approximately 27% of children under the age of 5 in these countries are still malnourished. This work focuses on the childhood malnutrition in one of the biggest developing countries, Egypt. This study examined the association between bio-demographic and socioeconomic determinants and the malnutrition problem in children less than 5 years of age using the 2003 Demographic and Health survey data for Egypt. In the first step, we use separate geoadditive Gaussian models with the continuous response variables stunting (height-for-age), underweight (weight-for-age), and wasting (weight-for-height) as indicators of nutritional status in our case study. In a second step, based on the results of the first step, we apply the geoadditive Gaussian latent variable model for continuous indicators in which the 3 measurements of the malnutrition status of children are assumed as indicators for the latent variable "nutritional status".

Realist identification of group-level latent variables for perinatal social epidemiology theory building.

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Eastwood, John Graeme; Jalaludin, Bin Badrudin; Kemp, Lynn Ann; Phung, Hai Ngoc

2014-01-01

We have previously reported in this journal on an ecological study of perinatal depressive symptoms in South Western Sydney. In that article, we briefly reported on a factor analysis that was utilized to identify empirical indicators for analysis. In this article, we report on the mixed method approach that was used to identify those latent variables. Social epidemiology has been slow to embrace a latent variable approach to the study of social, political, economic, and cultural structures and mechanisms, partly for philosophical reasons. Critical realist ontology and epistemology have been advocated as an appropriate methodological approach to both theory building and theory testing in the health sciences. We describe here an emergent mixed method approach that uses qualitative methods to identify latent constructs followed by factor analysis using empirical indicators chosen to measure identified qualitative codes. Comparative analysis of the findings is reported together with a limited description of realist approaches to abstract reasoning.

Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

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Hoyle, R H

1991-02-01

Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.

Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models

DEFF Research Database (Denmark)

Vehtari, Aki; Mononen, Tommi; Tolvanen, Ville

2016-01-01

The future predictive performance of a Bayesian model can be estimated using Bayesian cross-validation. In this article, we consider Gaussian latent variable models where the integration over the latent values is approximated using the Laplace method or expectation propagation (EP). We study...... the properties of several Bayesian leave-one-out (LOO) cross-validation approximations that in most cases can be computed with a small additional cost after forming the posterior approximation given the full data. Our main objective is to assess the accuracy of the approximative LOO cross-validation estimators...

Latent variable models an introduction to factor, path, and structural equation analysis

CERN Document Server

Loehlin, John C

2004-01-01

This fourth edition introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. The book is intended for advanced students and researchers in the areas of social, educational, clinical, ind

Intraclass Correlation Coefficients in Hierarchical Designs: Evaluation Using Latent Variable Modeling

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Raykov, Tenko

2011-01-01

Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…

Investigating Factorial Invariance of Latent Variables Across Populations When Manifest Variables Are Missing Completely.

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Widaman, Keith F; Grimm, Kevin J; Early, Dawnté R; Robins, Richard W; Conger, Rand D

2013-07-01

Difficulties arise in multiple-group evaluations of factorial invariance if particular manifest variables are missing completely in certain groups. Ad hoc analytic alternatives can be used in such situations (e.g., deleting manifest variables), but some common approaches, such as multiple imputation, are not viable. At least 3 solutions to this problem are viable: analyzing differing sets of variables across groups, using pattern mixture approaches, and a new method using random number generation. The latter solution, proposed in this article, is to generate pseudo-random normal deviates for all observations for manifest variables that are missing completely in a given sample and then to specify multiple-group models in a way that respects the random nature of these values. An empirical example is presented in detail comparing the 3 approaches. The proposed solution can enable quantitative comparisons at the latent variable level between groups using programs that require the same number of manifest variables in each group.

INCLUSION OF THE LATENT PERSONALITY VARIABLE IN MULTINOMIAL LOGIT MODELS USING THE 16PF PSYCHOMETRIC TEST

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JORGE E. CÓRDOBA MAQUILÓN

2012-01-01

Full Text Available Los modelos de demanda de viajes utilizan principalmente los atributos modales y las características socioeconómicas como variables explicativas. También se ha establecido que las actitudes y percepciones influyen en el comportamiento de los usuarios. Sin embargo, las variables psicológicas del individuo condicionan la conducta del usuario. En este estudio se incluyó la variable latente personalidad, en la estimación del modelo híbrido de elección discreta, el cual constituye una buena alternativa para incorporar los efectos de los factores subjetivos. La variable latente personalidad se evaluó con la prueba psicométrica 16PF de validez internacional. El artículo analiza los resultados de la aplicación de este modelo a una población de empleados y docentes universitarios, y también propone un camino para la utilización de pruebas psicométricas en los modelos híbridos de elección discreta. Nuestros resultados muestran que los modelos híbridos que incluyen variables latentes psicológicas son superiores a los modelos tradicionales que ignoran los efectos de la conducta de los usuarios.

A Comparison of Approaches for the Analysis of Interaction Effects between Latent Variables Using Partial Least Squares Path Modeling

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Henseler, Jorg; Chin, Wynne W.

2010-01-01

In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches as well as their suitability. This article…

Monoamine Oxidase A (MAOA Gene and Personality Traits from Late Adolescence through Early Adulthood: A Latent Variable Investigation

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Man K. Xu

2017-10-01

Full Text Available Very few molecular genetic studies of personality traits have used longitudinal phenotypic data, therefore molecular basis for developmental change and stability of personality remains to be explored. We examined the role of the monoamine oxidase A gene (MAOA on extraversion and neuroticism from adolescence to adulthood, using modern latent variable methods. A sample of 1,160 male and 1,180 female participants with complete genotyping data was drawn from a British national birth cohort, the MRC National Survey of Health and Development (NSHD. The predictor variable was based on a latent variable representing genetic variations of the MAOA gene measured by three SNPs (rs3788862, rs5906957, and rs979606. Latent phenotype variables were constructed using psychometric methods to represent cross-sectional and longitudinal phenotypes of extraversion and neuroticism measured at ages 16 and 26. In males, the MAOA genetic latent variable (AAG was associated with lower extraversion score at age 16 (β = −0.167; CI: −0.289, −0.045; p = 0.007, FDRp = 0.042, as well as greater increase in extraversion score from 16 to 26 years (β = 0.197; CI: 0.067, 0.328; p = 0.003, FDRp = 0.036. No genetic association was found for neuroticism after adjustment for multiple testing. Although, we did not find statistically significant associations after multiple testing correction in females, this result needs to be interpreted with caution due to issues related to x-inactivation in females. The latent variable method is an effective way of modeling phenotype- and genetic-based variances and may therefore improve the methodology of molecular genetic studies of complex psychological traits.

Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters

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Hoshino, Takahiro; Shigemasu, Kazuo

2008-01-01

The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…

Evaluation of Validity and Reliability for Hierarchical Scales Using Latent Variable Modeling

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Raykov, Tenko; Marcoulides, George A.

2012-01-01

A latent variable modeling method is outlined, which accomplishes estimation of criterion validity and reliability for a multicomponent measuring instrument with hierarchical structure. The approach provides point and interval estimates for the scale criterion validity and reliability coefficients, and can also be used for testing composite or…

Bayesian modeling of ChIP-chip data using latent variables.

KAUST Repository

Wu, Mingqi

2009-10-26

BACKGROUND: The ChIP-chip technology has been used in a wide range of biomedical studies, such as identification of human transcription factor binding sites, investigation of DNA methylation, and investigation of histone modifications in animals and plants. Various methods have been proposed in the literature for analyzing the ChIP-chip data, such as the sliding window methods, the hidden Markov model-based methods, and Bayesian methods. Although, due to the integrated consideration of uncertainty of the models and model parameters, Bayesian methods can potentially work better than the other two classes of methods, the existing Bayesian methods do not perform satisfactorily. They usually require multiple replicates or some extra experimental information to parametrize the model, and long CPU time due to involving of MCMC simulations. RESULTS: In this paper, we propose a Bayesian latent model for the ChIP-chip data. The new model mainly differs from the existing Bayesian models, such as the joint deconvolution model, the hierarchical gamma mixture model, and the Bayesian hierarchical model, in two respects. Firstly, it works on the difference between the averaged treatment and control samples. This enables the use of a simple model for the data, which avoids the probe-specific effect and the sample (control/treatment) effect. As a consequence, this enables an efficient MCMC simulation of the posterior distribution of the model, and also makes the model more robust to the outliers. Secondly, it models the neighboring dependence of probes by introducing a latent indicator vector. A truncated Poisson prior distribution is assumed for the latent indicator variable, with the rationale being justified at length. CONCLUSION: The Bayesian latent method is successfully applied to real and ten simulated datasets, with comparisons with some of the existing Bayesian methods, hidden Markov model methods, and sliding window methods. The numerical results indicate that the

Use of latent variables representing psychological motivation to explore citizens’ intentions with respect to congestion charging reform in Jakarta

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Sugiarto Sugiarto

2015-01-01

Full Text Available The aim of this paper is to investigate the intentions of Jakarta citizens with respect to the electronic road pricing (ERP reform proposed by the city government. Utilizing data from a stated preference survey conducted in 2013, we construct six variables representing latent psychological motivations (appropriateness of ERP adoption; recognition that ERP can mitigate congestion and improve the environment; car dependency (CDC; awareness of the problems of cars in society; inhibition of freedom movement caused by ERP; and doubts about the ability of ERP to mitigate congestion and environment problems. A multiple-indicators multiple-causes (MIMIC model is developed to investigate the effects of respondents’ socio-demographics (causes on the latent constructs in order to gain better understanding of the relationship between respondents’ intentions and the observed individual’s responses (indicators obtained from the stated preference survey. The MIMIC model offers a good account of whether and how socio-demographic attributes and individual indicators predict the latent variables of psychological motivation constructs. Then, we further verify the influences of the latent variables, combining them with levy rate patterns and daily mobility attributes to investigate significant determining factors for social acceptance of the ERP proposal. A latent variable representations based on the generalized ordered response model are employed in our investigations to allow more flexibility in parameter estimation across outcomes. The results confirm that there is a strong correlation between latent psychological motivations and daily mobility attributes and the level of social acceptance for the ERP proposal. This empirical investigation demonstrates that the latent variables play more substantial role in determining scheme’s acceptance. Moreover, elasticity measures show that latent attributes are more sensitive compared to levies and daily mobility

Measuring behaviours for escaping from house fires: use of latent variable models to summarise multiple behaviours.

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Ploubidis, G B; Edwards, P; Kendrick, D

2015-12-15

This paper reports the development and testing of a construct measuring parental fire safety behaviours for planning escape from a house fire. Latent variable modelling of data on parental-reported fire safety behaviours and plans for escaping from a house fire and multivariable logistic regression to quantify the association between groups defined by the latent variable modelling and parental-report of having a plan for escaping from a house fire. Data comes from 1112 participants in a cluster randomised controlled trial set in children's centres in 4 study centres in the UK. A two class model provided the best fit to the data, combining responses to five fire safety planning behaviours. The first group ('more behaviours for escaping from a house fire') comprised 86% of participants who were most likely to have a torch, be aware of how their smoke alarm sounds, to have external door and window keys accessible, and exits clear. The second group ('fewer behaviours for escaping from a house fire') comprised 14% of participants who were less likely to report these five behaviours. After adjusting for potential confounders, participants allocated to the 'more behaviours for escaping from a house fire group were 2.5 times more likely to report having an escape plan (OR 2.48; 95% CI 1.59-3.86) than those in the "fewer behaviours for escaping from a house fire" group. Multiple fire safety behaviour questions can be combined into a single binary summary measure of fire safety behaviours for escaping from a house fire. Our findings will be useful to future studies wishing to use a single measure of fire safety planning behaviour as measures of outcome or exposure. NCT 01452191. Date of registration 13/10/2011.

Mixture simultaneous factor analysis for capturing differences in latent variables between higher level units of multilevel data

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De Roover, K.; Vermunt, J.K.; Timmerman, Marieke E.; Ceulemans, Eva

2017-01-01

Given multivariate data, many research questions pertain to the covariance structure: whether and how the variables (for example, personality measures) covary. Exploratory factor analysis (EFA) is often used to look for latent variables that may explain the covariances among variables; for example,

A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.

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Mo, Qianxing; Shen, Ronglai; Guo, Cui; Vannucci, Marina; Chan, Keith S; Hilsenbeck, Susan G

2018-01-01

Identification of clinically relevant tumor subtypes and omics signatures is an important task in cancer translational research for precision medicine. Large-scale genomic profiling studies such as The Cancer Genome Atlas (TCGA) Research Network have generated vast amounts of genomic, transcriptomic, epigenomic, and proteomic data. While these studies have provided great resources for researchers to discover clinically relevant tumor subtypes and driver molecular alterations, there are few computationally efficient methods and tools for integrative clustering analysis of these multi-type omics data. Therefore, the aim of this article is to develop a fully Bayesian latent variable method (called iClusterBayes) that can jointly model omics data of continuous and discrete data types for identification of tumor subtypes and relevant omics features. Specifically, the proposed method uses a few latent variables to capture the inherent structure of multiple omics data sets to achieve joint dimension reduction. As a result, the tumor samples can be clustered in the latent variable space and relevant omics features that drive the sample clustering are identified through Bayesian variable selection. This method significantly improve on the existing integrative clustering method iClusterPlus in terms of statistical inference and computational speed. By analyzing TCGA and simulated data sets, we demonstrate the excellent performance of the proposed method in revealing clinically meaningful tumor subtypes and driver omics features. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Assessing factors related to waist circumference and obesity: application of a latent variable model.

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Dalvand, Sahar; Koohpayehzadeh, Jalil; Karimlou, Masoud; Asgari, Fereshteh; Rafei, Ali; Seifi, Behjat; Niksima, Seyed Hassan; Bakhshi, Enayatollah

2015-01-01

Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Data included 18,990 Iranian individuals aged 20-65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variable model, we estimated the relation of two correlated responses (waist circumference and obesity) with independent variables including age, gender, PR (Place of Residence), PA (physical activity), smoking status, SBP (Systolic Blood Pressure), DBP (Diastolic Blood Pressure), CHOL (cholesterol), FBG (Fasting Blood Glucose), diabetes, and FHD (family history of diabetes). All variables were related to both obesity and waist circumference (WC). Older age, female sex, being an urban resident, physical inactivity, nonsmoking, hypertension, hypercholesterolemia, hyperglycemia, diabetes, and having family history of diabetes were significant risk factors that increased WC and obesity. Findings from this study of Iranian adult settings offer more insights into factors associated with high WC and high prevalence of obesity in this population.

Assessing Factors Related to Waist Circumference and Obesity: Application of a Latent Variable Model

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Sahar Dalvand

2015-01-01

Full Text Available Background. Because the use of BMI (Body Mass Index alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome and obesity (binary outcome among Iranian adults. Methods. Data included 18,990 Iranian individuals aged 20–65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variable model, we estimated the relation of two correlated responses (waist circumference and obesity with independent variables including age, gender, PR (Place of Residence, PA (physical activity, smoking status, SBP (Systolic Blood Pressure, DBP (Diastolic Blood Pressure, CHOL (cholesterol, FBG (Fasting Blood Glucose, diabetes, and FHD (family history of diabetes. Results. All variables were related to both obesity and waist circumference (WC. Older age, female sex, being an urban resident, physical inactivity, nonsmoking, hypertension, hypercholesterolemia, hyperglycemia, diabetes, and having family history of diabetes were significant risk factors that increased WC and obesity. Conclusions. Findings from this study of Iranian adult settings offer more insights into factors associated with high WC and high prevalence of obesity in this population.

Single-Cell RNA-Seq Reveals Transcriptional Heterogeneity in Latent and Reactivated HIV-Infected Cells.

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Golumbeanu, Monica; Cristinelli, Sara; Rato, Sylvie; Munoz, Miguel; Cavassini, Matthias; Beerenwinkel, Niko; Ciuffi, Angela

2018-04-24

Despite effective treatment, HIV can persist in latent reservoirs, which represent a major obstacle toward HIV eradication. Targeting and reactivating latent cells is challenging due to the heterogeneous nature of HIV-infected cells. Here, we used a primary model of HIV latency and single-cell RNA sequencing to characterize transcriptional heterogeneity during HIV latency and reactivation. Our analysis identified transcriptional programs leading to successful reactivation of HIV expression. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

On Latent Growth Models for Composites and Their Constituents.

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Hancock, Gregory R; Mao, Xiulin; Kher, Hemant

2013-09-01

Over the last decade and a half, latent growth modeling has become an extremely popular and versatile technique for evaluating longitudinal change and its determinants. Most common among the models applied are those for a single measured variable over time. This model has been extended in a variety of ways, most relevant for the current work being the multidomain and the second-order latent growth models. Whereas the former allows for growth function characteristics to be modeled for multiple outcomes simultaneously, with the degree of growth characteristics' relations assessed within the model (e.g., cross-domain slope factor correlations), the latter models growth in latent outcomes, each of which has effect indicators repeated over time. But what if one has an outcome that is believed to be formative relative to its indicator variables rather than latent? In this case, where the outcome is a composite of multiple constituents, modeling change over time is less straightforward. This article provides analytical and applied details for simultaneously modeling growth in composites and their constituent elements, including a real data example using a general computer self-efficacy questionnaire.

Global Convergence of the EM Algorithm for Unconstrained Latent Variable Models with Categorical Indicators

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Weissman, Alexander

2013-01-01

Convergence of the expectation-maximization (EM) algorithm to a global optimum of the marginal log likelihood function for unconstrained latent variable models with categorical indicators is presented. The sufficient conditions under which global convergence of the EM algorithm is attainable are provided in an information-theoretic context by…

Cognitive Preconditions of Early Reading and Spelling: A Latent-Variable Approach with Longitudinal Data

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Preßler, Anna-Lena; Könen, Tanja; Hasselhorn, Marcus; Krajewski, Kristin

2014-01-01

The aim of the present study was to empirically disentangle the interdependencies of the impact of nonverbal intelligence, working memory capacities, and phonological processing skills on early reading decoding and spelling within a latent variable approach. In a sample of 127 children, these cognitive preconditions were assessed before the onset…

A Second-Order Conditionally Linear Mixed Effects Model with Observed and Latent Variable Covariates

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Harring, Jeffrey R.; Kohli, Nidhi; Silverman, Rebecca D.; Speece, Deborah L.

2012-01-01

A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a…

The Relationship between Executive Functions and Language Abilities in Children: A Latent Variables Approach

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Kaushanskaya, Margarita; Park, Ji Sook; Gangopadhyay, Ishanti; Davidson, Meghan M.; Weismer, Susan Ellis

2017-01-01

Purpose: We aimed to outline the latent variables approach for measuring nonverbal executive function (EF) skills in school-age children, and to examine the relationship between nonverbal EF skills and language performance in this age group. Method: Seventy-one typically developing children, ages 8 through 11, participated in the study. Three EF…

Impact of marriage on HIV/AIDS risk behaviors among impoverished, at-risk couples: a multilevel latent variable approach.

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Stein, Judith A; Nyamathi, Adeline; Ullman, Jodie B; Bentler, Peter M

2007-01-01

Studies among normative samples generally demonstrate a positive impact of marriage on health behaviors and other related attitudes. In this study, we examine the impact of marriage on HIV/AIDS risk behaviors and attitudes among impoverished, highly stressed, homeless couples, many with severe substance abuse problems. A multilevel analysis of 368 high-risk sexually intimate married and unmarried heterosexual couples assessed individual and couple-level effects on social support, substance use problems, HIV/AIDS knowledge, perceived HIV/AIDS risk, needle-sharing, condom use, multiple sex partners, and HIV/AIDS testing. More variance was explained in the protective and risk variables by couple-level latent variable predictors than by individual latent variable predictors, although some gender effects were found (e.g., more alcohol problems among men). The couple-level variable of marriage predicted lower perceived risk, less deviant social support, and fewer sex partners but predicted more needle-sharing.

Application of latent variable model in Rosenberg self-esteem scale.

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Leung, Shing-On; Wu, Hui-Ping

2013-01-01

Latent Variable Models (LVM) are applied to Rosenberg Self-Esteem Scale (RSES). Parameter estimations automatically give negative signs hence no recoding is necessary for negatively scored items. Bad items can be located through parameter estimate, item characteristic curves and other measures. Two factors are extracted with one on self-esteem and the other on the degree to take moderate views, with the later not often being covered in previous studies. A goodness-of-fit measure based on two-way margins is used but more works are needed. Results show that scaling provided by models with more formal statistical ground correlated highly with conventional method, which may provide justification for usual practice.

ltm: An R Package for Latent Variable Modeling and Item Response Analysis

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Dimitris Rizopoulos

2006-11-01

Full Text Available The R package ltm has been developed for the analysis of multivariate dichotomous and polytomous data using latent variable models, under the Item Response Theory approach. For dichotomous data the Rasch, the Two-Parameter Logistic, and Birnbaum's Three-Parameter models have been implemented, whereas for polytomous data Semejima's Graded Response model is available. Parameter estimates are obtained under marginal maximum likelihood using the Gauss-Hermite quadrature rule. The capabilities and features of the package are illustrated using two real data examples.

Comparing the Measured and Latent Dark Triad: Are Three Measures Better than One?

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Peter K. Jonason

2011-10-01

Full Text Available Could measurement level be a factor worth considering when studying the Dark Triad (i.e., narcissism, psychopathy, and Machiavellianism? In two studies (N  = 465, we compared the relative fit of two Dark Triad models: one that treats the three measures as separate-yet-related personality traits and another that treats the measures as tapping a single, latent construct. Mid-level personality traits, such as mate-retention strategies (Study 1 were best explained by a three-measure model, whereas the higher-order trait of sociosexuality (Study 2, were best explained by a single, latent-factor model. When considering mid-level measurement in personality, the three traits may provide independent effects for interpersonal relationships, whereas at the higher-order level, the three traits may function as a single entity relating to other higher-order traits. We suggest one should consider level of measurement between the predictor and criterion variables to better predict correlations among variables such as the Dark Triad. DOI: 10.2458/azu_jmmss.v2i1.12363

Latent Variable Regression 4-Level Hierarchical Model Using Multisite Multiple-Cohorts Longitudinal Data. CRESST Report 801

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Choi, Kilchan

2011-01-01

This report explores a new latent variable regression 4-level hierarchical model for monitoring school performance over time using multisite multiple-cohorts longitudinal data. This kind of data set has a 4-level hierarchical structure: time-series observation nested within students who are nested within different cohorts of students. These…

Latent Transition Analysis with a Mixture Item Response Theory Measurement Model

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Cho, Sun-Joo; Cohen, Allan S.; Kim, Seock-Ho; Bottge, Brian

2010-01-01

A latent transition analysis (LTA) model was described with a mixture Rasch model (MRM) as the measurement model. Unlike the LTA, which was developed with a latent class measurement model, the LTA-MRM permits within-class variability on the latent variable, making it more useful for measuring treatment effects within latent classes. A simulation…

On the Latent Variable Interpretation in Sum-Product Networks.

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Peharz, Robert; Gens, Robert; Pernkopf, Franz; Domingos, Pedro

2017-10-01

One of the central themes in Sum-Product networks (SPNs) is the interpretation of sum nodes as marginalized latent variables (LVs). This interpretation yields an increased syntactic or semantic structure, allows the application of the EM algorithm and to efficiently perform MPE inference. In literature, the LV interpretation was justified by explicitly introducing the indicator variables corresponding to the LVs' states. However, as pointed out in this paper, this approach is in conflict with the completeness condition in SPNs and does not fully specify the probabilistic model. We propose a remedy for this problem by modifying the original approach for introducing the LVs, which we call SPN augmentation. We discuss conditional independencies in augmented SPNs, formally establish the probabilistic interpretation of the sum-weights and give an interpretation of augmented SPNs as Bayesian networks. Based on these results, we find a sound derivation of the EM algorithm for SPNs. Furthermore, the Viterbi-style algorithm for MPE proposed in literature was never proven to be correct. We show that this is indeed a correct algorithm, when applied to selective SPNs, and in particular when applied to augmented SPNs. Our theoretical results are confirmed in experiments on synthetic data and 103 real-world datasets.

Latent Fundamentals Arbitrage with a Mixed Effects Factor Model

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Andrei Salem Gonçalves

2012-09-01

Full Text Available We propose a single-factor mixed effects panel data model to create an arbitrage portfolio that identifies differences in firm-level latent fundamentals. Furthermore, we show that even though the characteristics that affect returns are unknown variables, it is possible to identify the strength of the combination of these latent fundamentals for each stock by following a simple approach using historical data. As a result, a trading strategy that bought the stocks with the best fundamentals (strong fundamentals portfolio and sold the stocks with the worst ones (weak fundamentals portfolio realized significant risk-adjusted returns in the U.S. market for the period between July 1986 and June 2008. To ensure robustness, we performed sub period and seasonal analyses and adjusted for trading costs and we found further empirical evidence that using a simple investment rule, that identified these latent fundamentals from the structure of past returns, can lead to profit.

Identification of Nevirapine-Resistant HIV-1 in the Latent Reservoir after Single-Dose Nevirapine to Prevent Mother-to-Child Transmission of HIV-1

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Wind-Rotolo, Megan; Durand, Christine; Cranmer, Lisa; Reid, Alison; Martinson, Neil; Doherty, Meg; Jilek, Benjamin L.; Kagaayi, Joseph; Kizza, Allan; Pillay, Visva; Laeyendecker, Oliver; Reynolds, Steven J.; Eshleman, Susan H.; Lau, Bryan; Ray, Stuart C.; Siliciano, Janet D.; Quinn, Thomas C.; Siliciano, Robert F.

2009-01-01

Background Intrapartum single-dose nevirapine decreases mother-to-child transmission of human immunodeficiency virus type 1 (HIV-1) but promotes nevirapine resistance. Although resistant viruses fade to undetectable levels in plasma, they may persist as stably integrated proviruses within the latent reservoir in resting CD4+ T cells, potentially complicating future treatment. Methods Blood samples were collected from 60 women from South Africa and Uganda >6 months after they had received single-dose nevirapine. To selectively analyze the stable latent form of HIV-1, resting CD4+ T cells were isolated and activated in the presence of reverse-transcriptase inhibitors and integrase inhibitors, which allows for the specific isolation of viruses produced by cells with stably integrated proviral DNA. These viruses were then analyzed for nevirapine resistance. Results Although only a small number of latently infected cells were present in each blood sample (mean, 162 cells), nevirapine resistance mutations (K103N and G190A) were detected in the latent reservoir of 4 (8%) of 50 evaluable women. Conclusions A single dose of nevirapine can establish antiretroviral resistance within the latent reservoir. This results in a potentially lifelong risk of reemergence of nevirapine-resistant virus and highlights the need for strategies to prevent transmission that do not compromise successful future treatment. PMID:19338474

Identification of Chinese medicine syndromes in persistent insomnia associated with major depressive disorder: a latent tree analysis.

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Yeung, Wing-Fai; Chung, Ka-Fai; Zhang, Nevin Lian-Wen; Zhang, Shi Ping; Yung, Kam-Ping; Chen, Pei-Xian; Ho, Yan-Yee

2016-01-01

Chinese medicine (CM) syndrome (zheng) differentiation is based on the co-occurrence of CM manifestation profiles, such as signs and symptoms, and pulse and tongue features. Insomnia is a symptom that frequently occurs in major depressive disorder despite adequate antidepressant treatment. This study aims to identify co-occurrence patterns in participants with persistent insomnia and major depressive disorder from clinical feature data using latent tree analysis, and to compare the latent variables with relevant CM syndromes. One hundred and forty-two participants with persistent insomnia and a history of major depressive disorder completed a standardized checklist (the Chinese Medicine Insomnia Symptom Checklist) specially developed for CM syndrome classification of insomnia. The checklist covers symptoms and signs, including tongue and pulse features. The clinical features assessed by the checklist were analyzed using Lantern software. CM practitioners with relevant experience compared the clinical feature variables under each latent variable with reference to relevant CM syndromes, based on a previous review of CM syndromes. The symptom data were analyzed to build the latent tree model and the model with the highest Bayes information criterion score was regarded as the best model. This model contained 18 latent variables, each of which divided participants into two clusters. Six clusters represented more than 50 % of the sample. The clinical feature co-occurrence patterns of these six clusters were interpreted as the CM syndromes Liver qi stagnation transforming into fire, Liver fire flaming upward, Stomach disharmony, Hyperactivity of fire due to yin deficiency, Heart-kidney noninteraction, and Qi deficiency of the heart and gallbladder. The clinical feature variables that contributed significant cumulative information coverage (at least 95 %) were identified. Latent tree model analysis on a sample of depressed participants with insomnia revealed 13 clinical

Diagnostic value of a single blood pressure reading for the detection of latent hypertension in children with chronic kidney diseases

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M. E. Aksenova

2017-01-01

Full Text Available Hypertension is a modifiable risk factor for cardiovascular diseases. The data of  24-hour ambulatory blood pressure monitoring (ABPM largely correlate with target organ lesions; however, the availability of 24-hour ABPM remains low in clinical practice.Objective. to determine the diagnostic value of a single office blood pressure measurement for the detection of latent hypertension in children with chronic kidney diseasesSubjects and methods. A single office blood pressure measurement and 24-hour ABPM were carried out in 359 children (boys/girls, 0,51/0,49; median age, 13 years (5; 17 with chronic kidney diseases (a glomerular filtration rate of 84,18±29,6 ml min/1,73m2 (median, 86 ml/min/1,73m2 estimated using the Schwartz equation. To rule out the impact of antihypertensive and/or immunosuppressive therapy on the results of the study, the investigators identified a group of 108 patients (boys/girls, 0,52/0,48; median age, 12 years (5; 16, estimated median glomerular filtration rate, 84 ml/min/1,73m2 who did not receive the above treatment.Results. Office blood pressure measurements revealed prehypertension in 14,5% of cases, hypertension in 27,5%, which was consistent with white coat hypertension in 5% of cases. According to 24-hour ABPM, hypertension was present in 48,7% of the children, including those with latent hypertension (26%. Children with latent hypertension (56,4% had more frequently elevated blood pressure only at night. The level of office blood pressure was weakly correlated with that of the mean diastolic blood pressure during the day, regardless of the presence/absence of antihypertensive and/or immunosuppressive therapy. Latent hypertension was detected in approximately one-fifth of children with different blood pressure levels in the normal range and its frequency significantly increased 1,5–2-fold in patients with higher-normal blood pressure (90‰ ≤ AP <95‰. The children who did not receive

Interexaminer variation of minutia markup on latent fingerprints.

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Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn

2016-07-01

Latent print examiners often differ in the number of minutiae they mark during analysis of a latent, and also during comparison of a latent with an exemplar. Differences in minutia counts understate interexaminer variability: examiners' markups may have similar minutia counts but differ greatly in which specific minutiae were marked. We assessed variability in minutia markup among 170 volunteer latent print examiners. Each provided detailed markup documenting their examinations of 22 latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. An average of 12 examiners marked each latent. The primary factors associated with minutia reproducibility were clarity, which regions of the prints examiners chose to mark, and agreement on value or comparison determinations. In clear areas (where the examiner was "certain of the location, presence, and absence of all minutiae"), median reproducibility was 82%; in unclear areas, median reproducibility was 46%. Differing interpretations regarding which regions should be marked (e.g., when there is ambiguity in the continuity of a print) contributed to variability in minutia markup: especially in unclear areas, marked minutiae were often far from the nearest minutia marked by a majority of examiners. Low reproducibility was also associated with differences in value or comparison determinations. Lack of standardization in minutia markup and unfamiliarity with test procedures presumably contribute to the variability we observed. We have identified factors accounting for interexaminer variability; implementing standards for detailed markup as part of documentation and focusing future training efforts on these factors may help to facilitate transparency and reduce subjectivity in the examination process. Published by Elsevier Ireland Ltd.

Class Evolution Tree: A Graphical Tool to Support Decisions on the Number of Classes in Exploratory Categorical Latent Variable Modeling for Rehabilitation Research

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Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa

2011-01-01

The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was…

Students' views on mathematics in single-sex and coed classrooms in Ghana

OpenAIRE

Bofah, Emmanuel Adu-Tutu; Hannula, Markku S.

2016-01-01

In this study, we investigated students’ views on themselves as learners of mathematics as a function of school-by-sex (N = 2034, MAge = 18.49, SDAge = 1.25; 12th-grade; 58.2% girls). Using latent variable Structural Equation Modeling (SEM), the measurement and structural equivalence as well as the equality of latent means of scores across single-sex and coed schools were tested. Findings regarding the latent mean differences revealed that girls in single-sex schools had significantly higher ...

Improvement in latent variable indirect response modeling of multiple categorical clinical endpoints: application to modeling of guselkumab treatment effects in psoriatic patients.

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Hu, Chuanpu; Randazzo, Bruce; Sharma, Amarnath; Zhou, Honghui

2017-10-01

Exposure-response modeling plays an important role in optimizing dose and dosing regimens during clinical drug development. The modeling of multiple endpoints is made possible in part by recent progress in latent variable indirect response (IDR) modeling for ordered categorical endpoints. This manuscript aims to investigate the level of improvement achievable by jointly modeling two such endpoints in the latent variable IDR modeling framework through the sharing of model parameters. This is illustrated with an application to the exposure-response of guselkumab, a human IgG1 monoclonal antibody in clinical development that blocks IL-23. A Phase 2b study was conducted in 238 patients with psoriasis for which disease severity was assessed using Psoriasis Area and Severity Index (PASI) and Physician's Global Assessment (PGA) scores. A latent variable Type I IDR model was developed to evaluate the therapeutic effect of guselkumab dosing on 75, 90 and 100% improvement of PASI scores from baseline and PGA scores, with placebo effect empirically modeled. The results showed that the joint model is able to describe the observed data better with fewer parameters compared with the common approach of separately modeling the endpoints.

Interaction between Helicobacter pylori and latent toxoplasmosis and demographic variables on cognitive function in young to middle-aged adults.

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Gale, Shawn D; Erickson, Lance D; Brown, Bruce L; Hedges, Dawson W

2015-01-01

Helicobacter pylori and latent toxoplasmosis are widespread diseases that have been associated with cognitive deficits and Alzheimer's disease. We sought to determine whether interactions between Helicobacter pylori and latent toxoplasmosis, age, race-ethnicity, educational attainment, economic status, and general health predict cognitive function in young and middle-aged adults. To do so, we used multivariable regression and multivariate models to analyze data obtained from the United States' National Health and Nutrition Examination Survey from the Centers for Disease Control and Prevention, which can be weighted to represent the US population. In this sample, we found that 31.6 percent of women and 36.2 percent of men of the overall sample had IgG Antibodies against Helicobacter pylori, although the seroprevalence of Helicobacter pylori varied with sociodemographic variables. There were no main effects for Helicobacter pylori or latent toxoplasmosis for any of the cognitive measures in models adjusting for age, sex, race-ethnicity, educational attainment, economic standing, and self-rated health predicting cognitive function. However, interactions between Helicobacter pylori and race-ethnicity, educational attainment, latent toxoplasmosis in the fully adjusted models predicted cognitive function. People seropositive for both Helicobacter pylori and latent toxoplasmosis - both of which appear to be common in the general population - appear to be more susceptible to cognitive deficits than are people seropositive for either Helicobacter pylori and or latent toxoplasmosis alone, suggesting a synergistic effect between these two infectious diseases on cognition in young to middle-aged adults.

Interaction between Helicobacter pylori and latent toxoplasmosis and demographic variables on cognitive function in young to middle-aged adults.

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Shawn D Gale

Full Text Available Helicobacter pylori and latent toxoplasmosis are widespread diseases that have been associated with cognitive deficits and Alzheimer's disease. We sought to determine whether interactions between Helicobacter pylori and latent toxoplasmosis, age, race-ethnicity, educational attainment, economic status, and general health predict cognitive function in young and middle-aged adults. To do so, we used multivariable regression and multivariate models to analyze data obtained from the United States' National Health and Nutrition Examination Survey from the Centers for Disease Control and Prevention, which can be weighted to represent the US population. In this sample, we found that 31.6 percent of women and 36.2 percent of men of the overall sample had IgG Antibodies against Helicobacter pylori, although the seroprevalence of Helicobacter pylori varied with sociodemographic variables. There were no main effects for Helicobacter pylori or latent toxoplasmosis for any of the cognitive measures in models adjusting for age, sex, race-ethnicity, educational attainment, economic standing, and self-rated health predicting cognitive function. However, interactions between Helicobacter pylori and race-ethnicity, educational attainment, latent toxoplasmosis in the fully adjusted models predicted cognitive function. People seropositive for both Helicobacter pylori and latent toxoplasmosis - both of which appear to be common in the general population - appear to be more susceptible to cognitive deficits than are people seropositive for either Helicobacter pylori and or latent toxoplasmosis alone, suggesting a synergistic effect between these two infectious diseases on cognition in young to middle-aged adults.

Heteroscedastic Latent Trait Models for Dichotomous Data.

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Molenaar, Dylan

2015-09-01

Effort has been devoted to account for heteroscedasticity with respect to observed or latent moderator variables in item or test scores. For instance, in the multi-group generalized linear latent trait model, it could be tested whether the observed (polychoric) covariance matrix differs across the levels of an observed moderator variable. In the case that heteroscedasticity arises across the latent trait itself, existing models commonly distinguish between heteroscedastic residuals and a skewed trait distribution. These models have valuable applications in intelligence, personality and psychopathology research. However, existing approaches are only limited to continuous and polytomous data, while dichotomous data are common in intelligence and psychopathology research. Therefore, in present paper, a heteroscedastic latent trait model is presented for dichotomous data. The model is studied in a simulation study, and applied to data pertaining alcohol use and cognitive ability.

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

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Hayduk Leslie A

2012-10-01

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

An introduction to latent variable growth curve modeling concepts, issues, and application

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Duncan, Terry E; Strycker, Lisa A

2013-01-01

This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader's familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book's CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples.Updated throughout, the second edition features three new chapters-growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group is...

A new model of wheezing severity in young children using the validated ISAAC wheezing module: A latent variable approach with validation in independent cohorts.

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Brunwasser, Steven M; Gebretsadik, Tebeb; Gold, Diane R; Turi, Kedir N; Stone, Cosby A; Datta, Soma; Gern, James E; Hartert, Tina V

2018-01-01

The International Study of Asthma and Allergies in Children (ISAAC) Wheezing Module is commonly used to characterize pediatric asthma in epidemiological studies, including nearly all airway cohorts participating in the Environmental Influences on Child Health Outcomes (ECHO) consortium. However, there is no consensus model for operationalizing wheezing severity with this instrument in explanatory research studies. Severity is typically measured using coarsely-defined categorical variables, reducing power and potentially underestimating etiological associations. More precise measurement approaches could improve testing of etiological theories of wheezing illness. We evaluated a continuous latent variable model of pediatric wheezing severity based on four ISAAC Wheezing Module items. Analyses included subgroups of children from three independent cohorts whose parents reported past wheezing: infants ages 0-2 in the INSPIRE birth cohort study (Cohort 1; n = 657), 6-7-year-old North American children from Phase One of the ISAAC study (Cohort 2; n = 2,765), and 5-6-year-old children in the EHAAS birth cohort study (Cohort 3; n = 102). Models were estimated using structural equation modeling. In all cohorts, covariance patterns implied by the latent variable model were consistent with the observed data, as indicated by non-significant χ2 goodness of fit tests (no evidence of model misspecification). Cohort 1 analyses showed that the latent factor structure was stable across time points and child sexes. In both cohorts 1 and 3, the latent wheezing severity variable was prospectively associated with wheeze-related clinical outcomes, including physician asthma diagnosis, acute corticosteroid use, and wheeze-related outpatient medical visits when adjusting for confounders. We developed an easily applicable continuous latent variable model of pediatric wheezing severity based on items from the well-validated ISAAC Wheezing Module. This model prospectively associates with

Visualizing Confidence Bands for Semiparametrically Estimated Nonlinear Relations among Latent Variables

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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…

Labour market participants’ competitiveness assessment based on latent variables theory

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T. V. Sabetova

2017-01-01

Full Text Available The article suggests innovative model for assessment of labour market subjects’ competitiveness, or successfulness. The authors state that general complex indicator for individual competitiveness within the labour market cannot be identified. Instead, precise enough assessment of such competitiveness can be based on some variables, though different for in-house and external labour market. The model of latent variables’ assessment based on Rasch’s method was selected as the base for the suggested method. The assessment model gives unbiased generalized values of subjects’ competitiveness on the linear non-dimensional scale based on the partial estimates of the selected criteria. The free choice of these criteria allows the model’s appliance for various labour market segments. The article demonstrates the mathematical grounding for the model; methodic of the assessment criteria selection; the way of assessment performance using MS Excel. It also analyses the features of the obtained estimates and shows their comparison with the estimates obtained by traditional methods. The model suggested by the authors can introduce any quantitative parameter of competitiveness as a variable after analysis of the factors affecting it. The quantitative estimates of these factors become the model’s criteria, but the assessment precision does not alter.

Integrated Multiscale Latent Variable Regression and Application to Distillation Columns

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Muddu Madakyaru

2013-01-01

Full Text Available Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions, which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR techniques, such as principal component regression (PCR, partial least squares (PLS, and regularized canonical correlation analysis (RCCA. Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.

Decomposing the heterogeneity of depression at the person-, symptom-, and time-level : Latent variable models versus multimode principal component analysis

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de Vos, Stijn; Wardenaar, Klaas J.; Bos, Elisabeth H.; Wit, Ernst C.; de Jonge, Peter

2015-01-01

Background: Heterogeneity of psychopathological concepts such as depression hampers progress in research and clinical practice. Latent Variable Models (LVMs) have been widely used to reduce this problem by identification of more homogeneous factors or subgroups. However, heterogeneity exists at

Internet Gamblers Differ on Social Variables: A Latent Class Analysis.

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Khazaal, Yasser; Chatton, Anne; Achab, Sophia; Monney, Gregoire; Thorens, Gabriel; Dufour, Magali; Zullino, Daniele; Rothen, Stephane

2017-09-01

Online gambling has gained popularity in the last decade, leading to an important shift in how consumers engage in gambling and in the factors related to problem gambling and prevention. Indebtedness and loneliness have previously been associated with problem gambling. The current study aimed to characterize online gamblers in relation to indebtedness, loneliness, and several in-game social behaviors. The data set was obtained from 584 Internet gamblers recruited online through gambling websites and forums. Of these gamblers, 372 participants completed all study assessments and were included in the analyses. Questionnaires included those on sociodemographics and social variables (indebtedness, loneliness, in-game social behaviors), as well as the Gambling Motives Questionnaire, Gambling Related Cognitions Scale, Internet Addiction Test, Problem Gambling Severity Index, Short Depression-Happiness Scale, and UPPS-P Impulsive Behavior Scale. Social variables were explored with a latent class model. The clusters obtained were compared for psychological measures and three clusters were found: lonely indebted gamblers (cluster 1: 6.5%), not lonely not indebted gamblers (cluster 2: 75.4%), and not lonely indebted gamblers (cluster 3: 18%). Participants in clusters 1 and 3 (particularly in cluster 1) were at higher risk of problem gambling than were those in cluster 2. The three groups differed on most assessed variables, including the Problem Gambling Severity Index, the Short Depression-Happiness Scale, and the UPPS-P subscales (except the sensation seeking subscore). Results highlight significant between-group differences, suggesting that Internet gamblers are not a homogeneous group. Specific intervention strategies could be implemented for groups at risk.

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

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Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

Can Social History Variables Predict Prison Inmates’ Risk for Latent Tuberculosis Infection?

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Tyler E. Weant

2012-01-01

Full Text Available Improved screening and treatment of latent tuberculosis infection (LTBI in correctional facilities may improve TB control. The Ohio Department of Rehabilitation and Correction (ODRC consists of 32 prisons. Inmates are screened upon entry to ODRC and yearly thereafter. The objective of the study was to determine if social history factors such as tobacco, alcohol, and drug use are significant predictors of LTBI and treatment outcomes. We reviewed the medical charts of inmates and randomly selected age-matched controls at one ODRC facility for 2009. We used a conditional logistic regression to assess associations between selected social history variables and LTBI diagnosis. Eighty-nine inmates with a history of LTBI and 88 controls were identified. No social history variable was a significant predictor of LTBI. Medical comorbidities such as asthma, rheumatoid arthritis, and hepatitis C were significantly higher in inmates with LTBI. 84% of inmates diagnosed with LTBI had either completed or were on treatment. Annual TB screening may not be cost-effective in all inmate populations. Identification of factors to help target screening populations at risk for TB is critical. Social history variables did not predict LTBI in our inmate population. Additional studies are needed to identify inmates for the targeted TB testing.

Data on the interexaminer variation of minutia markup on latent fingerprints.

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Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn

2016-09-01

The data in this article supports the research paper entitled "Interexaminer variation of minutia markup on latent fingerprints" [1]. The data in this article describes the variability in minutia markup during both analysis of the latents and comparison between latents and exemplars. The data was collected in the "White Box Latent Print Examiner Study," in which each of 170 volunteer latent print examiners provided detailed markup documenting their examinations of latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. Each examiner examined 22 latent-exemplar pairs; an average of 12 examiners marked each latent.

Latent class analysis of the Yale-Brown Obsessive-Compulsive Scale symptoms in obsessive-compulsive disorder.

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Delucchi, Kevin L; Katerberg, Hilga; Stewart, S Evelyn; Denys, Damiaan A J P; Lochner, Christine; Stack, Denise E; den Boer, Johan A; van Balkom, Anton J L M; Jenike, Michael A; Stein, Dan J; Cath, Danielle C; Mathews, Carol A

2011-01-01

Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous, and findings of underlying structure classification based on symptom grouping have been ambiguous to date. Variable-centered approaches, primarily factor analysis, have been used to identify homogeneous groups of symptoms; but person-centered latent methods have seen little use. This study was designed to uncover sets of homogeneous groupings within 1611 individuals with OCD based on symptoms. Latent class analysis models using 61 obsessive-compulsive symptoms collected from the Yale-Brown Obsessive-Compulsive Scale were fit. Relationships between latent class membership and treatment response, sex, symptom severity, and comorbid tic disorders were tested for relationship to class membership. Latent class analysis models of best fit yielded 3 classes. Classes differed only in frequency of symptom endorsement. Classes with higher symptom endorsement were associated with earlier age of onset, being male, higher Yale-Brown Obsessive-Compulsive Scale symptom severity scores, and comorbid tic disorders. There were no differences in treatment response between classes. These results provide support for the validity of a single underlying latent OCD construct, in addition to the distinct symptom factors identified previously via factor analyses. Copyright © 2011 Elsevier Inc. All rights reserved.

Cognitive psychology meets psychometric theory: on the relation between process models for decision making and latent variable models for individual differences

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van der Maas, H.L.J.; Molenaar, D.; Maris, G.; Kievit, R.A.; Borsboom, D.

2011-01-01

This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual

Temporal analysis of text data using latent variable models

DEFF Research Database (Denmark)

Mølgaard, Lasse Lohilahti; Larsen, Jan; Goutte, Cyril

2009-01-01

Detecting and tracking of temporal data is an important task in multiple applications. In this paper we study temporal text mining methods for Music Information Retrieval. We compare two ways of detecting the temporal latent semantics of a corpus extracted from Wikipedia, using a stepwise...

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

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Jeban Ganesalingam

2009-09-01

Full Text Available Amyotrophic lateral sclerosis (ALS is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes.Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method.The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001. Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb and time from symptom onset to diagnosis (p<0.00001.The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.

High-Performance Psychometrics: The Parallel-E Parallel-M Algorithm for Generalized Latent Variable Models. Research Report. ETS RR-16-34

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von Davier, Matthias

2016-01-01

This report presents results on a parallel implementation of the expectation-maximization (EM) algorithm for multidimensional latent variable models. The developments presented here are based on code that parallelizes both the E step and the M step of the parallel-E parallel-M algorithm. Examples presented in this report include item response…

Latent lifestyle preferences and household location decisions

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Walker, Joan L.; Li, Jieping

2007-04-01

Lifestyle, indicating preferences towards a particular way of living, is a key driver of the decision of where to live. We employ latent class choice models to represent this behavior, where the latent classes are the lifestyles and the choice model is the choice of residential location. Thus, we simultaneously estimate lifestyle groups and how lifestyle impacts location decisions. Empirical results indicate three latent lifestyle segments: suburban dwellers, urban dwellers, and transit-riders. The suggested lifestyle segments have intriguing policy implications. Lifecycle characteristics are used to predict lifestyle preferences, although there remain significant aspects that cannot be explained by observable variables.

Are depression and frailty overlapping syndromes in mid- and late-life? A latent variable analysis.

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Mezuk, Briana; Lohman, Matthew; Dumenci, Levent; Lapane, Kate L

2013-06-01

Depression and frailty both predict disability and morbidity in later life. However, it is unclear to what extent these common geriatric syndromes represent overlapping constructs. To examine the joint relationship between the constructs of depression and frailty. Data come from 2004-2005 wave of the Baltimore Epidemiologic Catchment Area Study, and the analysis is limited to participants 40 years and older, with complete data on frailty and depression indicators (N = 683). Depression was measured using the Diagnostic Interview Schedule, and frailty was indexed by modified Fried criteria. A series of confirmatory latent class analyses were used to assess the degree to which depression and frailty syndromes identify the same populations. A latent kappa coefficient (κl) was also estimated between the constructs. Confirmatory latent class analyses indicated that depression and frailty represent distinct syndromes rather than a single construct. The joint modeling of the two constructs supported a three-class solution for depression and two-class solution for frailty, with 2.9% categorized as severely depressed, 19.4% as mildly depressed, and 77.7% as not depressed, and 21.1% categorized as frail and 78.9% as not frail. The chance-corrected agreement statistic indicated moderate correspondence between the depression and frailty constructs (κl: 66, 95% confidence interval: 0.58-0.74). Results suggest that depression and frailty are interrelated concepts, yet their operational criteria identify substantively overlapping subpopulations. These findings have implications for understanding factors that contribute to the etiology and prognosis of depression and frailty in later life. Copyright © 2013 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Cognitive Psychology Meets Psychometric Theory: On the Relation between Process Models for Decision Making and Latent Variable Models for Individual Differences

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van der Maas, Han L. J.; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A.; Borsboom, Denny

2011-01-01

This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line…

Dynamic Latent Classification Model

DEFF Research Database (Denmark)

Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre

as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

Estimators for longitudinal latent exposure models: examining measurement model assumptions.

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Sánchez, Brisa N; Kim, Sehee; Sammel, Mary D

2017-06-15

Latent variable (LV) models are increasingly being used in environmental epidemiology as a way to summarize multiple environmental exposures and thus minimize statistical concerns that arise in multiple regression. LV models may be especially useful when multivariate exposures are collected repeatedly over time. LV models can accommodate a variety of assumptions but, at the same time, present the user with many choices for model specification particularly in the case of exposure data collected repeatedly over time. For instance, the user could assume conditional independence of observed exposure biomarkers given the latent exposure and, in the case of longitudinal latent exposure variables, time invariance of the measurement model. Choosing which assumptions to relax is not always straightforward. We were motivated by a study of prenatal lead exposure and mental development, where assumptions of the measurement model for the time-changing longitudinal exposure have appreciable impact on (maximum-likelihood) inferences about the health effects of lead exposure. Although we were not particularly interested in characterizing the change of the LV itself, imposing a longitudinal LV structure on the repeated multivariate exposure measures could result in high efficiency gains for the exposure-disease association. We examine the biases of maximum likelihood estimators when assumptions about the measurement model for the longitudinal latent exposure variable are violated. We adapt existing instrumental variable estimators to the case of longitudinal exposures and propose them as an alternative to estimate the health effects of a time-changing latent predictor. We show that instrumental variable estimators remain unbiased for a wide range of data generating models and have advantages in terms of mean squared error. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A Latent Class Approach to Estimating Test-Score Reliability

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van der Ark, L. Andries; van der Palm, Daniel W.; Sijtsma, Klaas

2011-01-01

This study presents a general framework for single-administration reliability methods, such as Cronbach's alpha, Guttman's lambda-2, and method MS. This general framework was used to derive a new approach to estimating test-score reliability by means of the unrestricted latent class model. This new approach is the latent class reliability…

Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots

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Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.

2013-01-01

Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…

Conceptualising computerized adaptive testing for measurement of latent variables associated with physical objects

International Nuclear Information System (INIS)

Camargo, F R; Henson, B

2015-01-01

The notion of that more or less of a physical feature affects in different degrees the users' impression with regard to an underlying attribute of a product has frequently been applied in affective engineering. However, those attributes exist only as a premise that cannot directly be measured and, therefore, inferences based on their assessment are error-prone. To establish and improve measurement of latent attributes it is presented in this paper the concept of a stochastic framework using the Rasch model for a wide range of independent variables referred to as an item bank. Based on an item bank, computerized adaptive testing (CAT) can be developed. A CAT system can converge into a sequence of items bracketing to convey information at a user's particular endorsement level. It is through item banking and CAT that the financial benefits of using the Rasch model in affective engineering can be realised

A developmental study of latent absolute pitch memory.

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Jakubowski, Kelly; Müllensiefen, Daniel; Stewart, Lauren

2017-03-01

The ability to recall the absolute pitch level of familiar music (latent absolute pitch memory) is widespread in adults, in contrast to the rare ability to label single pitches without a reference tone (overt absolute pitch memory). The present research investigated the developmental profile of latent absolute pitch (AP) memory and explored individual differences related to this ability. In two experiments, 288 children from 4 to12 years of age performed significantly above chance at recognizing the absolute pitch level of familiar melodies. No age-related improvement or decline, nor effects of musical training, gender, or familiarity with the stimuli were found in regard to latent AP task performance. These findings suggest that latent AP memory is a stable ability that is developed from as early as age 4 and persists into adulthood.

LATENT STRUCTURE OF MOTOR ABILITIES AND SKILLS OF DEAF CHILDREN

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Husnija Hasanbegović

2012-04-01

Full Text Available In this work surveys of latent motility abilities and skills of school children are shown. The sample for this survey was consisted of two subsamples. First one has consisted of deaf children N=29, and the second one has consisted hearing children of same age N=69. Subsamples of deaf is chosen according to model of applied sample, and subsample is chosen randomly, so two stages group sample N=90 has been created. After quantitative differences have been discovered between subsamples, hearing pupils have shown statistically better results at motility skills and techniques than deaf children and cumulative results have been subjected to inter correlation of variables. The target of using this method was determination of saturation of common variability through saturation of variables and their correlation by Ortoblique rotation for determination of latent information that are going to serve as practical guides at education and deaf children treatment, because of improvement of their motility abilities and skills according to hearing children. Three factors have been singled out as main preview of measurement on manifest variables. According to first review of measuring it has been established that at deaf children is needed to work on improving of physical abilities and mobility and then developed motility abilities and skills. Their information has been gained most probably by non system fluctuations as information about ability of balance maintaining which is most probably non dependable of motility abilities and skills as at deaf and hearing children too. According to this survey by entering the structure of measuring instrument it is possible to create programs for improving motility abilities and skills at deaf children.

Using structural equation modeling to investigate relationships among ecological variables

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Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.

2000-01-01

Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0

a Latent Variable Path Analysis Model of Secondary Physics Enrollments in New York State.

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Sobolewski, Stanley John

The Percentage of Enrollment in Physics (PEP) at the secondary level nationally has been approximately 20% for the past few decades. For a more scientifically literate citizenry as well as specialists to continue scientific research and development, it is desirable that more students enroll in physics. Some of the predictor variables for physics enrollment and physics achievement that have been identified previously includes a community's socioeconomic status, the availability of physics, the sex of the student, the curriculum, as well as teacher and student data. This study isolated and identified predictor variables for PEP of secondary schools in New York. Data gathered by the State Education Department for the 1990-1991 school year was used. The source of this data included surveys completed by teachers and administrators on student characteristics and school facilities. A data analysis similar to that done by Bryant (1974) was conducted to determine if the relationships between a set of predictor variables related to physics enrollment had changed in the past 20 years. Variables which were isolated included: community, facilities, teacher experience, number of type of science courses, school size and school science facilities. When these variables were isolated, latent variable path diagrams were proposed and verified by the Linear Structural Relations computer modeling program (LISREL). These diagrams differed from those developed by Bryant in that there were more manifest variables used which included achievement scores in the form of Regents exam results. Two criterion variables were used, percentage of students enrolled in physics (PEP) and percent of students enrolled passing the Regents physics exam (PPP). The first model treated school and community level variables as exogenous while the second model treated only the community level variables as exogenous. The goodness of fit indices for the models was 0.77 for the first model and 0.83 for the second

The "g" Factor and Cognitive Test Session Behavior: Using a Latent Variable Approach in Examining Measurement Invariance Across Age Groups on the WJ III

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Frisby, Craig L.; Wang, Ze

2016-01-01

Data from the standardization sample of the Woodcock-Johnson Psychoeducational Battery--Third Edition (WJ III) Cognitive standard battery and Test Session Observation Checklist items were analyzed to understand the relationship between g (general mental ability) and test session behavior (TSB; n = 5,769). Latent variable modeling methods were used…

Study The role of latent variables in lost working days by Structural Equation Modeling Approach

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Meysam Heydari

2016-12-01

Full Text Available Background: Based on estimations, each year about 250 million work-related injuries and many temporary or permanent disabilities occur which most are preventable. Oil and Gas industries are among industries with high incidence of injuries in the world. The aim of this study has investigated  the role and effect of different risk management variables on lost working days (LWD in the seismic projects. Methods: This study was a retrospective, cross-sectional and systematic analysis, which was carried out on occupational accidents between 2008-2015(an 8 years period in different seismic projects for oilfield exploration at Dana Energy (Iranian Seismic Company. The preliminary sample size of the study were 487accidents. A systems analysis approach were applied by using root case analysis (RCA and structural equation modeling (SEM. Tools for the data analysis were included, SPSS23 and AMOS23  software. Results: The mean of lost working days (LWD, was calculated 49.57, the final model of structural equation modeling showed that latent variables of, safety and health training factor(-0.33, risk assessment factor(-0.55 and risk control factor (-0.61 as direct causes significantly affected of lost working days (LWD in the seismic industries (p< 0.05. Conclusion: The finding of present study revealed that combination of variables affected in lost working days (LWD. Therefore,the role of these variables in accidents should be investigated and suitable programs should be considered for them.

Multilevel Latent Class Analysis: Parametric and Nonparametric Models

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Finch, W. Holmes; French, Brian F.

2014-01-01

Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture…

A Review of the Latent and Manifest Benefits (LAMB) Scale

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Muller, Juanita; Waters, Lea

2012-01-01

The latent and manifest benefits (LAMB) scale (Muller, Creed, Waters & Machin, 2005) was designed to measure the latent and manifest benefits of employment and provide a single scale to test Jahoda's (1981) and Fryer's (1986) theories of unemployment. Since its publication in 2005 there have been 13 studies that have used the scale with 5692…

Using latent variable approach to estimate China's economy-wide energy rebound effect over 1954–2010

International Nuclear Information System (INIS)

Shao, Shuai; Huang, Tao; Yang, Lili

2014-01-01

The energy rebound effect has been a significant issue in China, which is undergoing economic transition, since it reflects the effectiveness of energy-saving policy relying on improved energy efficiency. Based on the IPAT equation and Brookes' explanation of the rebound effect, this paper develops an alternative estimation model of the rebound effect. By using the estimation model and latent variable approach, which is achieved through a time-varying coefficient state space model, we estimate China's economy-wide energy rebound effect over 1954–2010. The results show that the rebound effect evidently exists in China as a result of the annual average of 39.73% over 1954–2010. Before and after the implementation of China's reform and opening-up policy in 1978, the rebound effects are 47.24% and 37.32%, with a strong fluctuation and a circuitously downward trend, respectively, indicating that a stable political environment and the development of market economy system facilitate the effectiveness of energy-saving policy. Although the energy-saving effect of improving energy efficiency has been partly realised, there remains a large energy-saving potential in China. - Highlights: • We present an improved estimation methodology of economy-wide energy rebound effect. • We use the latent variable approach to estimate China's economy-wide rebound effect. • The rebound exists in China and varies before and after reform and opening-up. • After 1978, the average rebound is 37.32% with a circuitously downward trend. • Traditional Solow remainder method underestimates the rebound in most cases

Alexithymia and psychosocial problems among Italian preadolescents. A latent class analysis approach.

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Mannarini, Stefania; Balottin, Laura; Toldo, Irene; Gatta, Michela

2016-10-01

The study, conducted on Italian preadolscents aged 11 to 13 belonging to the general population, aims to investigate the relationship between the emotional functioning, namely, alexithymia, and the risk of developing behavioral and emotional problems measured using the Strength and Difficulty Questionnaire. The latent class analysis approach allowed to identify two latent variables, accounting for the internalizing (emotional symptoms and difficulties in emotional awareness) and for the externalizing problems (conduct problems and hyperactivity, problematic relationships with peers, poor prosocial behaviors and externally oriented thinking). The two latent variables featured two latent classes: the difficulty in dealing with problems and the strength to face problems that was representative of most of the healthy participants with specific gender differences. Along with the analysis of psychopathological behaviors, the study of resilience and strengths can prove to be a key step in order to develop valuable preventive approaches to tackle psychiatric disorders. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Evaluating aggregate effects of rare and common variants in the 1000 Genomes Project exon sequencing data using latent variable structural equation modeling.

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Nock, Nl; Zhang, Lx

2011-11-29

Methods that can evaluate aggregate effects of rare and common variants are limited. Therefore, we applied a two-stage approach to evaluate aggregate gene effects in the 1000 Genomes Project data, which contain 24,487 single-nucleotide polymorphisms (SNPs) in 697 unrelated individuals from 7 populations. In stage 1, we identified potentially interesting genes (PIGs) as those having at least one SNP meeting Bonferroni correction using univariate, multiple regression models. In stage 2, we evaluate aggregate PIG effects on trait, Q1, by modeling each gene as a latent construct, which is defined by multiple common and rare variants, using the multivariate statistical framework of structural equation modeling (SEM). In stage 1, we found that PIGs varied markedly between a randomly selected replicate (replicate 137) and 100 other replicates, with the exception of FLT1. In stage 1, collapsing rare variants decreased false positives but increased false negatives. In stage 2, we developed a good-fitting SEM model that included all nine genes simulated to affect Q1 (FLT1, KDR, ARNT, ELAV4, FLT4, HIF1A, HIF3A, VEGFA, VEGFC) and found that FLT1 had the largest effect on Q1 (βstd = 0.33 ± 0.05). Using replicate 137 estimates as population values, we found that the mean relative bias in the parameters (loadings, paths, residuals) and their standard errors across 100 replicates was on average, less than 5%. Our latent variable SEM approach provides a viable framework for modeling aggregate effects of rare and common variants in multiple genes, but more elegant methods are needed in stage 1 to minimize type I and type II error.

Repeatability and reproducibility of decisions by latent fingerprint examiners.

Directory of Open Access Journals (Sweden)

Bradford T Ulery

Full Text Available The interpretation of forensic fingerprint evidence relies on the expertise of latent print examiners. We tested latent print examiners on the extent to which they reached consistent decisions. This study assessed intra-examiner repeatability by retesting 72 examiners on comparisons of latent and exemplar fingerprints, after an interval of approximately seven months; each examiner was reassigned 25 image pairs for comparison, out of total pool of 744 image pairs. We compare these repeatability results with reproducibility (inter-examiner results derived from our previous study. Examiners repeated 89.1% of their individualization decisions, and 90.1% of their exclusion decisions; most of the changed decisions resulted in inconclusive decisions. Repeatability of comparison decisions (individualization, exclusion, inconclusive was 90.0% for mated pairs, and 85.9% for nonmated pairs. Repeatability and reproducibility were notably lower for comparisons assessed by the examiners as "difficult" than for "easy" or "moderate" comparisons, indicating that examiners' assessments of difficulty may be useful for quality assurance. No false positive errors were repeated (n = 4; 30% of false negative errors were repeated. One percent of latent value decisions were completely reversed (no value even for exclusion vs. of value for individualization. Most of the inter- and intra-examiner variability concerned whether the examiners considered the information available to be sufficient to reach a conclusion; this variability was concentrated on specific image pairs such that repeatability and reproducibility were very high on some comparisons and very low on others. Much of the variability appears to be due to making categorical decisions in borderline cases.

STATUS SOSIAL EKONOMI DAN FERTILITAS: A Latent Variable Approach

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Suandi -

2012-11-01

Full Text Available The main problems faced by developing countries including Indonesia are not onlyeconomic problems that tend to harm, but still met the high fertility rate. The purpose ofwriting to find out the relationship between socioeconomic status to the level of fertilitythrough the "A Latent Variable Approach." The study adopts the approach of fertility oneconomic development. Economic development based on the theories of Malthus: anincrease in "income" is slower than the increase in births (fertility and is the root ofpeople falling into poverty. However, Becker made linkage model or the influence ofchildren income and price. According to Becker, viewed from the aspect of demand thatthe price of children is greater than the income effect.The study shows that (1 level of education correlates positively on income andnegatively affect fertility, (2 age structure of women (control contraceptives adverselyaffect fertility. That is, the older the age, the level of individual productivity and lowerfertility or declining, and (3 husband's employment status correlated positively to theearnings (income. Through a permanent factor income or household income referred toas a negative influence on fertility. There are differences in value orientation of childrenbetween advanced society (rich with a backward society (the poor. The poor, forexample, the value of children is more production of goods. That is, children born moreemphasis on aspects of the number or the number of children owned (quantity, numberof children born by the poor is expected to help their parents at the age of retirement orno longer productive so that the child is expected to assist them in economic, security,and social security (insurance, while the developed (rich children are moreconsumption value or quality of the child.

Uncovering state-dependent relationships in shallow lakes using Bayesian latent variable regression.

Science.gov (United States)

Vitense, Kelsey; Hanson, Mark A; Herwig, Brian R; Zimmer, Kyle D; Fieberg, John

2018-03-01

Ecosystems sometimes undergo dramatic shifts between contrasting regimes. Shallow lakes, for instance, can transition between two alternative stable states: a clear state dominated by submerged aquatic vegetation and a turbid state dominated by phytoplankton. Theoretical models suggest that critical nutrient thresholds differentiate three lake types: highly resilient clear lakes, lakes that may switch between clear and turbid states following perturbations, and highly resilient turbid lakes. For effective and efficient management of shallow lakes and other systems, managers need tools to identify critical thresholds and state-dependent relationships between driving variables and key system features. Using shallow lakes as a model system for which alternative stable states have been demonstrated, we developed an integrated framework using Bayesian latent variable regression (BLR) to classify lake states, identify critical total phosphorus (TP) thresholds, and estimate steady state relationships between TP and chlorophyll a (chl a) using cross-sectional data. We evaluated the method using data simulated from a stochastic differential equation model and compared its performance to k-means clustering with regression (KMR). We also applied the framework to data comprising 130 shallow lakes. For simulated data sets, BLR had high state classification rates (median/mean accuracy >97%) and accurately estimated TP thresholds and state-dependent TP-chl a relationships. Classification and estimation improved with increasing sample size and decreasing noise levels. Compared to KMR, BLR had higher classification rates and better approximated the TP-chl a steady state relationships and TP thresholds. We fit the BLR model to three different years of empirical shallow lake data, and managers can use the estimated bifurcation diagrams to prioritize lakes for management according to their proximity to thresholds and chance of successful rehabilitation. Our model improves upon

Building latent class trees, with an application to a study of social capital

NARCIS (Netherlands)

van den Bergh, M.; Schmittmann, V.D.; Vermunt, J.K.

2017-01-01

Researchers use latent class (LC) analysis to derive meaningful clusters from sets of categorical variables. However, especially when the number of classes required to obtain a good fit is large, interpretation of the latent classes may not be straightforward. To overcome this problem, we propose an

Latent Class Analysis of Criminal Social Identity in a Prison Sample

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Boduszek Daniel

2014-06-01

Full Text Available This study aimed to examine the number of latent classes of criminal social identity that exist among male recidivistic prisoners. Latent class analysis was used to identify homogeneous groups of criminal social identity. Multinomial logistic regression was used to interpret the nature of the latent classes, or groups, by estimating the associationsto number of police arrests, recidivism, and violent offending while controlling for current age. The best fitting latent class model was a five-class solution: ‘High criminal social identity’ (17%, ‘High Centrality, Moderate Affect, Low Ties’ (21.7%, ‘Low Centrality, Moderate Affect, High Ties’ (13.3%,‘Low Cognitive, High Affect, Low Ties’ (24.6%, and ‘Low criminal social identity’ (23.4%. Each of the latent classes was predicted by differing external variables. Criminal social identity is best explained by five homogenous classes that display qualitative and quantitative differences.

Association between latent toxoplasmosis and cognition in adults: a cross-sectional study.

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Gale, S D; Brown, B L; Erickson, L D; Berrett, A; Hedges, D W

2015-04-01

Latent infection from Toxoplasma gondii (T. gondii) is widespread worldwide and has been associated with cognitive deficits in some but not all animal models and in humans. We tested the hypothesis that latent toxoplasmosis is associated with decreased cognitive function in a large cross-sectional dataset, the National Health and Nutrition Examination Survey (NHANES). There were 4178 participants aged 20-59 years, of whom 19.1% had IgG antibodies against T. gondii. Two ordinary least squares (OLS) regression models adjusted for the NHANES complex sampling design and weighted to represent the US population were estimated for simple reaction time, processing speed and short-term memory or attention. The first model included only main effects of latent toxoplasmosis and demographic control variables, and the second added interaction terms between latent toxoplasmosis and the poverty-to-income ratio (PIR), educational attainment and race-ethnicity. We also used multivariate models to assess all three cognitive outcomes in the same model. Although the models evaluating main effects only demonstrated no association between latent toxoplasmosis and the cognitive outcomes, significant interactions between latent toxoplasmosis and the PIR, between latent toxoplasmosis and educational attainment, and between latent toxoplasmosis and race-ethnicity indicated that latent toxoplasmosis may adversely affect cognitive function in certain groups.

The Effects of Educational Diversity in a National Sample of Law Students: Fitting Multilevel Latent Variable Models in Data With Categorical Indicators.

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Gottfredson, Nisha C; Panter, A T; Daye, Charles E; Allen, Walter F; Wightman, Linda F

2009-01-01

Controversy surrounding the use of race-conscious admissions can be partially resolved with improved empirical knowledge of the effects of racial diversity in educational settings. We use a national sample of law students nested in 64 law schools to test the complex and largely untested theory regarding the effects of educational diversity on student outcomes. Social scientists who study these outcomes frequently encounter both latent variables and nested data within a single analysis. Yet, until recently, an appropriate modeling technique has been computationally infeasible, and consequently few applied researchers have estimated appropriate models to test their theories, sometimes limiting the scope of their research question. Our results, based on disaggregated multilevel structural equation models, show that racial diversity is related to a reduction in prejudiced attitudes and increased perceived exposure to diverse ideas and that these effects are mediated by more frequent interpersonal contact with diverse peers. These findings provide support for the idea that administrative manipulation of educational diversity may lead to improved student outcomes. Admitting a racially/ethnically diverse student body provides an educational experience that encourages increased exposure to diverse ideas and belief systems.

Single-Trial Inference on Visual Attention

DEFF Research Database (Denmark)

Dyrholm, Mads; Kyllingsbæk, Søren; Vangkilde, Signe Allerup

2011-01-01

In this paper we take a step towards single-trial behavioral modeling within a Theory of Visual Attention (TVA). In selective attention tasks, such as the Partial Report paradigm, the subject is asked to ignore distractors and only report stimuli that belong to the target class. Nothing about...... Report trial. This result retrodicts a latent attentional state of the subject using the observed response from that particular trial and thus differs from other predictions made with TVA which are based on expected values of observed variables. We show an example of the result in single-trial analysis...

Perturbative corrections for approximate inference in gaussian latent variable models

DEFF Research Database (Denmark)

Opper, Manfred; Paquet, Ulrich; Winther, Ole

2013-01-01

Expectation Propagation (EP) provides a framework for approximate inference. When the model under consideration is over a latent Gaussian field, with the approximation being Gaussian, we show how these approximations can systematically be corrected. A perturbative expansion is made of the exact b...... illustrate on tree-structured Ising model approximations. Furthermore, they provide a polynomial-time assessment of the approximation error. We also provide both theoretical and practical insights on the exactness of the EP solution. © 2013 Manfred Opper, Ulrich Paquet and Ole Winther....

Mode choice models' ability to express intention to change travel behaviour considering non-compensatory rules and latent variables

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Nobuhiro Sanko

2013-03-01

Full Text Available Disaggregate behaviour choice models have been improved in many aspects, but they are rarely evaluated from the viewpoint of their ability to express intention to change travel behaviour. This study compared various models, including objective and latent models and compensatory and non-compensatory decision-making models. Latent models contain latent factors calculated using the LISREL (linear structural relations model. Non-compensatory models are based on a lexicographic-semiorder heuristic. This paper proposes ‘probability increment’ and ‘joint probability increment’ as indicators for evaluating the ability of these models to express intention to change travel behaviour. The application to commuting travel data in the Chukyo metropolitan area in Japan showed that the appropriate non-compensatory and latent models outperform other models.

Latent heat coldness storage; Stockage du froid par chaleur latente

Energy Technology Data Exchange (ETDEWEB)

Dumas, J.P. [Pau Univ., Lab. de Thermodynamique et Energetique, LTE, 64 (France)

2002-07-01

This article presents the advantages of latent heat storage systems which use the solid-liquid phase transformation of a pure substance or of a solution. The three main methods of latent heat storage of coldness are presented: ice boxes, encapsulated nodules, and ice flows: 1 - definition of the thermal energy storage (sensible heat, latent heat, thermochemical storage); 2 - advantages and drawbacks of latent heat storage; 3 - choice criteria for a phase-change material; 4 - phenomenological aspect of liquid-solid transformations (phase equilibrium, crystallisation and surfusion); 5 - different latent heat storage processes (ice boxes, encapsulated nodules, two-phase refrigerating fluids); 6 - ice boxes (internal and external melting, loop, air injection, measurement of ice thickness); 7 - encapsulated nodules (nodules, tank, drainage, advantage and drawbacks, charge and discharge); 8 - two-phase refrigerating fluids (composition, ice fabrication, flow circulation, flow storage, exchangers). (J.S.)

Latent factors and route choice behaviour

DEFF Research Database (Denmark)

Prato, Carlo Giacomo

. A reliable dataset was prepared through measures of internal consistency and sampling adequacy, and data were analyzed with a proper application of factor analysis to the route choice context. For the dataset obtained from the survey, six latent constructs affecting driver behaviour were extracted and scores...... on each factor for each survey participant were calculated. Path generation algorithms were examined with respect to observed behaviour, through a measure of reproduction with deterministic techniques of the routes indicated in the answers to the survey. Results presented evidence that the majority...... and Link Nested Logit. Estimates were produced from model specifications that considered level-of-service, label and facility dummy variables. Moreover, a modelling framework was designed to represent drivers’ choices as affected by the latent constructs extracted with factor analysis. Previous experience...

Longitudinal mixed-effects models for latent cognitive function

NARCIS (Netherlands)

van den Hout, Ardo; Fox, Gerardus J.A.; Muniz-Terrera, Graciela

2015-01-01

A mixed-effects regression model with a bent-cable change-point predictor is formulated to describe potential decline of cognitive function over time in the older population. For the individual trajectories, cognitive function is considered to be a latent variable measured through an item response

Latent palmprint matching.

Science.gov (United States)

Jain, Anil K; Feng, Jianjiang

2009-06-01

The evidential value of palmprints in forensic applications is clear as about 30 percent of the latents recovered from crime scenes are from palms. While biometric systems for palmprint-based personal authentication in access control type of applications have been developed, they mostly deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution and uses minutiae as features to be compatible with the methodology used by latent experts. Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, and have a complex background. Other difficulties include a large number of minutiae in full prints (about 10 times as many as fingerprints), and the presence of many creases in latents and full prints. A robust algorithm to reliably estimate the local ridge direction and frequency in palmprints is developed. This facilitates the extraction of ridge and minutiae features even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based minutiae matching algorithm is used to match two palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latent palmprints) are matched to a background database of 10,200 full palmprints to test the proposed system. Despite the inherent difficulty of latent-to-full palmprint matching, rank-1 recognition rates of 78.7 and 69 percent, respectively, were achieved in searching live-scan partial palmprints and latent palmprints against the background database.

Discriminative latent models for recognizing contextual group activities.

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Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N; Mori, Greg

2012-08-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities.

Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

Science.gov (United States)

Molgaard Nielsen, Anne; Hestbaek, Lise; Vach, Werner; Kent, Peter; Kongsted, Alice

2017-08-09

Heterogeneity in patients with low back pain is well recognised and different approaches to subgrouping have been proposed. One statistical technique that is increasingly being used is Latent Class Analysis as it performs subgrouping based on pattern recognition with high accuracy. Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two-stage approach. However, their prognostic capacity was unexplored. This study (i) determined whether the subgrouping approaches were associated with the future outcomes of pain intensity, pain frequency and disability, (ii) assessed whether one of these two approaches was more strongly or more consistently associated with these outcomes, and (iii) assessed the performance of the novel subgroupings as compared to the following variables: two existing subgrouping tools (STarT Back Tool and Quebec Task Force classification), four baseline characteristics and a group of previously identified domain-specific patient categorisations (collectively, the 'comparator variables'). This was a longitudinal cohort study of 928 patients consulting for low back pain in primary care. The associations between each subgroup approach and outcomes at 2 weeks, 3 and 12 months, and with weekly SMS responses were tested in linear regression models, and their prognostic capacity (variance explained) was compared to that of the comparator variables listed above. The two previously identified subgroupings were similarly associated with all outcomes. The prognostic capacity of both subgroupings was better than that of the comparator variables, except for participants' recovery beliefs and the domain-specific categorisations, but was still limited. The explained variance ranged from 4.3%-6.9% for pain intensity and

Original article Latent classes of criminal intent associated with criminal behaviour

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Daniel Boduszek

2014-07-01

Full Text Available Background This study aimed to examine the number of latent classes of criminal intent that exist among prisoners and to look at the associations with recidivism, number of police arrests, type of offending (robbery, violent offences, murder, and multiple offences, and age. Participants and procedure Latent class analysis was used to identify homogeneous subgroups of prisoners based on their responses to the 10 questions reflecting criminal intent. Participants were 309 male recidivistic prisoners incarcerated in a maximum security prison. Multinomial logistic regression was used to interpret the nature of the latent classes, or groups, by estimating the association between recidivism and latent classes of criminal intent while controlling for offence type (robbery, violent offences, murder, and multiple offences, number of arrests, and age. Results The best fitting latent class model was a three-class solution: ‘High criminal intent’ (49.3%, ‘Intermediate criminal intent’ (41.3%, and ‘Low criminal intent’ (9.4%. The latent classes were differentially related to the external variables (recidivism, violent offences, and age. Conclusions Criminal intent is best explained by three homogeneous classes that appear to represent an underlying continuum. Future work is needed to identify whether these distinct classes of criminal intent may predict engagement in various types of criminal behaviour.

Incorporating Measurement Non-Equivalence in a Cross-Study Latent Growth Curve Analysis.

Science.gov (United States)

Flora, David B; Curran, Patrick J; Hussong, Andrea M; Edwards, Michael C

2008-10-01

A large literature emphasizes the importance of testing for measurement equivalence in scales that may be used as observed variables in structural equation modeling applications. When the same construct is measured across more than one developmental period, as in a longitudinal study, it can be especially critical to establish measurement equivalence, or invariance, across the developmental periods. Similarly, when data from more than one study are combined into a single analysis, it is again important to assess measurement equivalence across the data sources. Yet, how to incorporate non-equivalence when it is discovered is not well described for applied researchers. Here, we present an item response theory approach that can be used to create scale scores from measures while explicitly accounting for non-equivalence. We demonstrate these methods in the context of a latent curve analysis in which data from two separate studies are combined to create a single longitudinal model spanning several developmental periods.

Latent variables underlying the memory beliefs of Chartered Clinical Psychologists, Hypnotherapists and undergraduate students.

Science.gov (United States)

Ost, James; Easton, Simon; Hope, Lorraine; French, Christopher C; Wright, Daniel B

2017-01-01

In courts in the United Kingdom, understanding of memory phenomena is often assumed to be a matter of common sense. To test this assumption 337 UK respondents, consisting of 125 Chartered Clinical Psychologists, 88 individuals who advertised their services as Hypnotherapists (HTs) in a classified directory, the Yellow Pages TM , and 124 first year undergraduate psychology students, completed a questionnaire that assessed their knowledge of 10 memory phenomena about which there is a broad scientific consensus. HTs' responses were the most inconsistent with the scientific consensus, scoring lowest on six of these ten items. Principal Components Analysis indicated two latent variables - reflecting beliefs about memory quality and malleability - underlying respondents' responses. In addition, respondents were asked to rate their own knowledge of the academic memory literature in general. There was no significant relationship between participants' self reported knowledge and their actual knowledge (as measured by their responses to the 10-item questionnaire). There was evidence of beliefs among the HTs that could give rise to some concern (e.g., that early memories from the first year of life are accurately stored and are retrievable).

Behavior problems at ages 6 and 11 and high school academic achievement: longitudinal latent variable modeling.

Science.gov (United States)

Breslau, Naomi; Breslau, Joshua; Miller, Elizabeth; Raykov, Tenko

2011-02-28

Previous studies documented long-run effects of behavior problems at the start of school on academic achievement. However, these studies did not examine whether the observed effects of early behavior problems are explained by more proximate behavior problems, given the tendency of children's behavior problems to persist. Latent variable modeling was applied to estimate the effects of behavior problems at ages 6 and 11 on academic achievement at age 17, using data from a longitudinal study (n=823). Behavior problems at ages 6 and 11, each stage independently of the other, predicted lower math and reading test scores at age 17, controlling for intelligence quotient (IQ), birth weight, maternal characteristics, family and community environment, and taking into account behavior problems at age 17. Behavior problems at the start of school, independent of later behavior problems, exert lingering effects on achievement by impeding the acquisition of cognitive skills that are the foundation for later academic progress. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

A coarse to fine minutiae-based latent palmprint matching.

Science.gov (United States)

Liu, Eryun; Jain, Anil K; Tian, Jie

2013-10-01

With the availability of live-scan palmprint technology, high resolution palmprint recognition has started to receive significant attention in forensics and law enforcement. In forensic applications, latent palmprints provide critical evidence as it is estimated that about 30 percent of the latents recovered at crime scenes are those of palms. Most of the available high-resolution palmprint matching algorithms essentially follow the minutiae-based fingerprint matching strategy. Considering the large number of minutiae (about 1,000 minutiae in a full palmprint compared to about 100 minutiae in a rolled fingerprint) and large area of foreground region in full palmprints, novel strategies need to be developed for efficient and robust latent palmprint matching. In this paper, a coarse to fine matching strategy based on minutiae clustering and minutiae match propagation is designed specifically for palmprint matching. To deal with the large number of minutiae, a local feature-based minutiae clustering algorithm is designed to cluster minutiae into several groups such that minutiae belonging to the same group have similar local characteristics. The coarse matching is then performed within each cluster to establish initial minutiae correspondences between two palmprints. Starting with each initial correspondence, a minutiae match propagation algorithm searches for mated minutiae in the full palmprint. The proposed palmprint matching algorithm has been evaluated on a latent-to-full palmprint database consisting of 446 latents and 12,489 background full prints. The matching results show a rank-1 identification accuracy of 79.4 percent, which is significantly higher than the 60.8 percent identification accuracy of a state-of-the-art latent palmprint matching algorithm on the same latent database. The average computation time of our algorithm for a single latent-to-full match is about 141 ms for genuine match and 50 ms for impostor match, on a Windows XP desktop system with 2

Longitudinal Physical Activity Patterns Among Older Adults: A Latent Transition Analysis.

Science.gov (United States)

Mooney, Stephen J; Joshi, Spruha; Cerdá, Magdalena; Kennedy, Gary J; Beard, John R; Rundle, Andrew G

2018-05-14

Most epidemiologic studies of physical activity measure either total energy expenditure or engagement in a single activity type, such as walking. These approaches may gloss over important nuances in activity patterns. We performed a latent transition analysis to identify patterns of activity types as well as neighborhood and individual determinants of changes in those activity patterns over two years in a cohort of 2,023 older adult residents of New York City, NY, surveyed between 2011 and 2013. We identified seven latent classes: 1) Mostly Inactive, 2) Walking, 3) Exercise, 4) Household Activities and Walking, 5) Household Activities and Exercise, 6) Gardening and Household Activities, and 7) Gardening, Household Activities, and Exercise. The majority of subjects retained the same activity patterns between waves (54% unchanged between waves 1 and 2, 66% unchanged between waves 2 and 3).Most latent class transitions were between classes distinguished only by one form of activity, and only neighborhood unemployment was consistently associated with changing between activity latent classes. Future latent transition analyses of physical activity would benefit from larger cohorts and longer follow-up periods to assess predictors of and long-term impacts of changes in activity patterns.

Lanthanide mixed ligand chelates for DNA profiling and latent fingerprint detection

Science.gov (United States)

Menzel, E. R.; Allred, Clay

1997-02-01

It is our aim to develop a universally applicable latent fingerprint detection method using lanthanide (rare-earth) complexes as a source of luminescence. Use of these lanthanide complexes offers advantages on several fronts, including benefits from large Stokes shifts, long luminescence lifetimes, narrow emissions, ability of sequential assembly of complexes, and chemical variability of the ligands. Proper exploitation of these advantages would lead to a latent fingerprint detection method superior to any currently available. These same characteristics also lend themselves to many of the problems associated with DNA processing in the forensic science context.

PET CT Identifies Reactivation Risk in Cynomolgus Macaques with Latent M. tuberculosis.

Directory of Open Access Journals (Sweden)

Philana Ling Lin

2016-07-01

Full Text Available Mycobacterium tuberculosis infection presents across a spectrum in humans, from latent infection to active tuberculosis. Among those with latent tuberculosis, it is now recognized that there is also a spectrum of infection and this likely contributes to the variable risk of reactivation tuberculosis. Here, functional imaging with 18F-fluorodeoxygluose positron emission tomography and computed tomography (PET CT of cynomolgus macaques with latent M. tuberculosis infection was used to characterize the features of reactivation after tumor necrosis factor (TNF neutralization and determine which imaging characteristics before TNF neutralization distinguish reactivation risk. PET CT was performed on latently infected macaques (n = 26 before and during the course of TNF neutralization and a separate set of latently infected controls (n = 25. Reactivation occurred in 50% of the latently infected animals receiving TNF neutralizing antibody defined as development of at least one new granuloma in adjacent or distant locations including extrapulmonary sites. Increased lung inflammation measured by PET and the presence of extrapulmonary involvement before TNF neutralization predicted reactivation with 92% sensitivity and specificity. To define the biologic features associated with risk of reactivation, we used these PET CT parameters to identify latently infected animals at high risk for reactivation. High risk animals had higher cumulative lung bacterial burden and higher maximum lesional bacterial burdens, and more T cells producing IL-2, IL-10 and IL-17 in lung granulomas as compared to low risk macaques. In total, these data support that risk of reactivation is associated with lung inflammation and higher bacterial burden in macaques with latent Mtb infection.

Latent-trait latent-class analysis of selfdisclosure in the work environment

NARCIS (Netherlands)

Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.

2006-01-01

Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of

Latent-trait latent-class analysis of selfdisclosure in the work environment

NARCIS (Netherlands)

Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.

2005-01-01

Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of

Power and type I error of local fit statistics in multilevel latent class analysis

NARCIS (Netherlands)

Nagelkerke, E.; Oberski, D.L.; Vermunt, J.K.

2017-01-01

In the social and behavioral sciences, variables are often categorical and people are often nested in groups. Models for such data, such as multilevel logistic regression or the multilevel latent class model, should account for not only the categorical nature of the variables, but also the nested

Verification of High Resolution Soil Moisture and Latent Heat in Germany

Science.gov (United States)

Samaniego, L. E.; Warrach-Sagi, K.; Zink, M.; Wulfmeyer, V.

2012-12-01

Improving our understanding of soil-land-surface-atmosphere feedbacks is fundamental to make reliable predictions of water and energy fluxes on land systems influenced by anthropogenic activities. Estimating, for instance, which would be the likely consequences of changing climatic regimes on water availability and crop yield, requires of high resolution soil moisture. Modeling it at large-scales, however, is difficult and uncertain because of the interplay between state variables and fluxes and the significant parameter uncertainty of the predicting models. At larger scales, the sub-grid variability of the variables involved and the nonlinearity of the processes complicate the modeling exercise even further because parametrization schemes might be scale dependent. Two contrasting modeling paradigms (WRF/Noah-MP and mHM) were employed to quantify the effects of model and data complexity on soil moisture and latent heat over Germany. WRF/Noah-MP was forced ERA-interim on the boundaries of the rotated CORDEX-Grid (www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11o covering Europe during the period from 1989 to 2009. Land cover and soil texture were represented in WRF/Noah-MP with 1×1~km MODIS images and a single horizon, coarse resolution European-wide soil map with 16 soil texture classes, respectively. To ease comparison, the process-based hydrological model mHM was forced with daily precipitation and temperature fields generated by WRF during the same period. The spatial resolution of mHM was fixed at 4×4~km. The multiscale parameter regionalization technique (MPR, Samaniego et al. 2010) was embedded in mHM to be able to estimate effective model parameters using hyper-resolution input data (100×100~km) obtained from Corine land cover and detailed soil texture fields for various horizons comprising 72 soil texture classes for Germany, among other physiographical variables. mHM global parameters, in contrast with those of Noah-MP, were

Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.

Science.gov (United States)

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-03-12

Item response theory (IRT) plays an important role in psychological and educational measurement. Unlike the classical testing theory, IRT models aggregate the item level information, yielding more accurate measurements. Most IRT models assume local independence, an assumption not likely to be satisfied in practice, especially when the number of items is large. Results in the literature and simulation studies in this paper reveal that misspecifying the local independence assumption may result in inaccurate measurements and differential item functioning. To provide more robust measurements, we propose an integrated approach by adding a graphical component to a multidimensional IRT model that can offset the effect of unknown local dependence. The new model contains a confirmatory latent variable component, which measures the targeted latent traits, and a graphical component, which captures the local dependence. An efficient proximal algorithm is proposed for the parameter estimation and structure learning of the local dependence. This approach can substantially improve the measurement, given no prior information on the local dependence structure. The model can be applied to measure both a unidimensional latent trait and multidimensional latent traits.

Estimating Classification Errors Under Edit Restrictions in Composite Survey-Register Data Using Multiple Imputation Latent Class Modelling (MILC

Directory of Open Access Journals (Sweden)

Boeschoten Laura

2017-12-01

Full Text Available Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible combinations with scores on other variables. Furthermore, the latent class model, by multiply imputing a new variable, enhances the quality of statistics based on the composite data set. The performance of this method is investigated by a simulation study, which shows that whether or not the method can be applied depends on the entropy R2 of the latent class model and the type of analysis a researcher is planning to do. Finally, the method is applied to public data from Statistics Netherlands.

Bayesian Analysis for Dynamic Generalized Linear Latent Model with Application to Tree Survival Rate

Directory of Open Access Journals (Sweden)

Yu-sheng Cheng

2014-01-01

Full Text Available Logistic regression model is the most popular regression technique, available for modeling categorical data especially for dichotomous variables. Classic logistic regression model is typically used to interpret relationship between response variables and explanatory variables. However, in real applications, most data sets are collected in follow-up, which leads to the temporal correlation among the data. In order to characterize the different variables correlations, a new method about the latent variables is introduced in this study. At the same time, the latent variables about AR (1 model are used to depict time dependence. In the framework of Bayesian analysis, parameters estimates and statistical inferences are carried out via Gibbs sampler with Metropolis-Hastings (MH algorithm. Model comparison, based on the Bayes factor, and forecasting/smoothing of the survival rate of the tree are established. A simulation study is conducted to assess the performance of the proposed method and a pika data set is analyzed to illustrate the real application. Since Bayes factor approaches vary significantly, efficiency tests have been performed in order to decide which solution provides a better tool for the analysis of real relational data sets.

Do gamblers eat more salt? Testing a latent trait model of covariance in consumption.

Science.gov (United States)

Goodwin, Belinda C; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip

2015-09-01

A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as 'reward-oriented' in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural 'consumption' factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours.

Latent-Trait Latent-Class Analysis of Self-disclosure in the Work Environment

NARCIS (Netherlands)

Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.

2005-01-01

Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of

Production of a phage-displayed single chain variable fragment ...

African Journals Online (AJOL)

Abstract. Purpose: To develop specific single chain variable fragments (scFv) against ... libraries. The binding ability of the selected scFv antibody fragments against the IBDV particles was ..... Hermelink H, Koscielniak E. A human recombinant.

Latent classification models

DEFF Research Database (Denmark)

Langseth, Helge; Nielsen, Thomas Dyhre

2005-01-01

parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

Age is associated with latent tuberculosis in nurses

Directory of Open Access Journals (Sweden)

Naesinee Chaiear

2016-12-01

Full Text Available Objective: To evaluate risk factors for developing latent tuberculosis (LTB in Thai nurses. Methods: A comparison study was conducted at Srinagarind Hospital, Khon Kaen, Thailand. Clinical factors were compared between persons with tuberculin conversion and those without tuberculin conversion identified by tuberculin skin test. Results: There were 173 eligible persons with the LTB (34.7%. There were five workplaces where participants worked regularly including the general ward, surgical ward, pediatric ward, medical ward and critical care ward. In a multivariate model, two factors were significantly associated with LTB including age and history of tuberculosis in colleagues. The adjusted odds ratio (95% confidence interval of both variables were 1.056 (1.004–1.104 and 0.202 (0.044– 0.941. Conclusions: Older age is associated with latent tuberculosis in nurses. LTB should be screened routinely and treated if diagnosed for nurses.

A single variable shear deformable nonlocal theory for transversely ...

Indian Academy of Sciences (India)

Rameshchandra P Shimpi

2018-05-11

May 11, 2018 ... Abstract. In this paper, a simple single variable shear deformable nonlocal theory for bending of micro- and ... the models based upon continuum mechanics are widely .... of the body. ...... Elsevier Science Ltd, Oxford, UK. pp.

Sex Differences in Fluid Reasoning: Manifest and Latent Estimates from the Cognitive Abilities Test

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Joni M. Lakin

2014-06-01

Full Text Available The size and nature of sex differences in cognitive ability continues to be a source of controversy. Conflicting findings result from the selection of measures, samples, and methods used to estimate sex differences. Existing sex differences work on the Cognitive Abilities Test (CogAT has analyzed manifest variables, leaving open questions about sex differences in latent narrow cognitive abilities and the underlying broad ability of fluid reasoning (Gf. This study attempted to address these questions. A confirmatory bifactor model was used to estimate Gf and three residual narrow ability factors (verbal, quantitative, and figural. We found that latent mean differences were larger than manifest estimates for all three narrow abilities. However, mean differences in Gf were trivial, consistent with previous research. In estimating group variances, the Gf factor showed substantially greater male variability (around 20% greater. The narrow abilities varied: verbal reasoning showed small variability differences while quantitative and figural showed substantial differences in variance (up to 60% greater. These results add precision and nuance to the study of the variability and masking hypothesis.

Latent change models of adult cognition: are changes in processing speed and working memory associated with changes in episodic memory?

Science.gov (United States)

Hertzog, Christopher; Dixon, Roger A; Hultsch, David F; MacDonald, Stuart W S

2003-12-01

The authors used 6-year longitudinal data from the Victoria Longitudinal Study (VLS) to investigate individual differences in amount of episodic memory change. Latent change models revealed reliable individual differences in cognitive change. Changes in episodic memory were significantly correlated with changes in other cognitive variables, including speed and working memory. A structural equation model for the latent change scores showed that changes in speed and working memory predicted changes in episodic memory, as expected by processing resource theory. However, these effects were best modeled as being mediated by changes in induction and fact retrieval. Dissociations were detected between cross-sectional ability correlations and longitudinal changes. Shuffling the tasks used to define the Working Memory latent variable altered patterns of change correlations.

The Latent Structure of Autistic Traits: A Taxometric, Latent Class and Latent Profile Analysis of the Adult Autism Spectrum Quotient

Science.gov (United States)

James, Richard J.; Dubey, Indu; Smith, Danielle; Ropar, Danielle; Tunney, Richard J.

2016-01-01

Autistic traits are widely thought to operate along a continuum. A taxometric analysis of Adult Autism Spectrum Quotient data was conducted to test this assumption, finding little support but identifying a high severity taxon. To understand this further, latent class and latent profile models were estimated that indicated the presence of six…

A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

Science.gov (United States)

Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

2017-09-01

The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Randomization-Based Inference about Latent Variables from Complex Samples: The Case of Two-Stage Sampling

Science.gov (United States)

Li, Tiandong

2012-01-01

In large-scale assessments, such as the National Assessment of Educational Progress (NAEP), plausible values based on Multiple Imputations (MI) have been used to estimate population characteristics for latent constructs under complex sample designs. Mislevy (1991) derived a closed-form analytic solution for a fixed-effect model in creating…

Symptom Cluster Research With Biomarkers and Genetics Using Latent Class Analysis.

Science.gov (United States)

Conley, Samantha

2017-12-01

The purpose of this article is to provide an overview of latent class analysis (LCA) and examples from symptom cluster research that includes biomarkers and genetics. A review of LCA with genetics and biomarkers was conducted using Medline, Embase, PubMed, and Google Scholar. LCA is a robust latent variable model used to cluster categorical data and allows for the determination of empirically determined symptom clusters. Researchers should consider using LCA to link empirically determined symptom clusters to biomarkers and genetics to better understand the underlying etiology of symptom clusters. The full potential of LCA in symptom cluster research has not yet been realized because it has been used in limited populations, and researchers have explored limited biologic pathways.

A Bayesian approach to estimate sensible and latent heat over vegetated land surface

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C. van der Tol

2009-06-01

Full Text Available Sensible and latent heat fluxes are often calculated from bulk transfer equations combined with the energy balance. For spatial estimates of these fluxes, a combination of remotely sensed and standard meteorological data from weather stations is used. The success of this approach depends on the accuracy of the input data and on the accuracy of two variables in particular: aerodynamic and surface conductance. This paper presents a Bayesian approach to improve estimates of sensible and latent heat fluxes by using a priori estimates of aerodynamic and surface conductance alongside remote measurements of surface temperature. The method is validated for time series of half-hourly measurements in a fully grown maize field, a vineyard and a forest. It is shown that the Bayesian approach yields more accurate estimates of sensible and latent heat flux than traditional methods.

Latent-Trait Latent-Class Analysis of Self-Disclosure in the Work Environment

Science.gov (United States)

Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk

2005-01-01

Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of self-disclosure. The model was used to analyze the data…

Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto.

Science.gov (United States)

Yasmin, Shamsunnahar; Eluru, Naveen

2016-10-01

The study contributes to literature on bicycle safety by building on the traditional count regression models to investigate factors affecting bicycle crashes at the Traffic Analysis Zone (TAZ) level. TAZ is a traffic related geographic entity which is most frequently used as spatial unit for macroscopic crash risk analysis. In conventional count models, the impact of exogenous factors is restricted to be the same across the entire region. However, it is possible that the influence of exogenous factors might vary across different TAZs. To accommodate for the potential variation in the impact of exogenous factors we formulate latent segmentation based count models. Specifically, we formulate and estimate latent segmentation based Poisson (LP) and latent segmentation based Negative Binomial (LNB) models to study bicycle crash counts. In our latent segmentation approach, we allow for more than two segments and also consider a large set of variables in segmentation and segment specific models. The formulated models are estimated using bicycle-motor vehicle crash data from the Island of Montreal and City of Toronto for the years 2006 through 2010. The TAZ level variables considered in our analysis include accessibility measures, exposure measures, sociodemographic characteristics, socioeconomic characteristics, road network characteristics and built environment. A policy analysis is also conducted to illustrate the applicability of the proposed model for planning purposes. This macro-level research would assist decision makers, transportation officials and community planners to make informed decisions to proactively improve bicycle safety - a prerequisite to promoting a culture of active transportation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stereotype Threat and College Academic Performance: A Latent Variables Approach*

Science.gov (United States)

Owens, Jayanti; Massey, Douglas S.

2013-01-01

Stereotype threat theory has gained experimental and survey-based support in helping explain the academic underperformance of minority students at selective colleges and universities. Stereotype threat theory states that minority students underperform because of pressures created by negative stereotypes about their racial group. Past survey-based studies, however, are characterized by methodological inefficiencies and potential biases: key theoretical constructs have only been measured using summed indicators and predicted relationships modeled using ordinary least squares. Using the National Longitudinal Survey of Freshman, this study overcomes previous methodological shortcomings by developing a latent construct model of stereotype threat. Theoretical constructs and equations are estimated simultaneously from multiple indicators, yielding a more reliable, valid, and parsimonious test of key propositions. Findings additionally support the view that social stigma can indeed have strong negative effects on the academic performance of pejoratively stereotyped racial-minority group members, not only in laboratory settings, but also in the real world. PMID:23950616

Latent and actual entrepreneurship in Europe and the US: some recent developments

NARCIS (Netherlands)

I. Grilo (Isabel); A.R. Thurik (Roy)

2005-01-01

textabstractThis paper uses 2004 survey data from the 15 old EU member states and the US to explain country differences in latent and actual entrepreneurship. Other than demographic variables such as gender, age and education, the set of covariates includes the perception by respondents of

Latent log-linear models for handwritten digit classification.

Science.gov (United States)

Deselaers, Thomas; Gass, Tobias; Heigold, Georg; Ney, Hermann

2012-06-01

We present latent log-linear models, an extension of log-linear models incorporating latent variables, and we propose two applications thereof: log-linear mixture models and image deformation-aware log-linear models. The resulting models are fully discriminative, can be trained efficiently, and the model complexity can be controlled. Log-linear mixture models offer additional flexibility within the log-linear modeling framework. Unlike previous approaches, the image deformation-aware model directly considers image deformations and allows for a discriminative training of the deformation parameters. Both are trained using alternating optimization. For certain variants, convergence to a stationary point is guaranteed and, in practice, even variants without this guarantee converge and find models that perform well. We tune the methods on the USPS data set and evaluate on the MNIST data set, demonstrating the generalization capabilities of our proposed models. Our models, although using significantly fewer parameters, are able to obtain competitive results with models proposed in the literature.

Variable dose rate single-arc IMAT delivered with a constant dose rate and variable angular spacing

International Nuclear Information System (INIS)

Tang, Grace; Earl, Matthew A; Yu, Cedric X

2009-01-01

Single-arc intensity-modulated arc therapy (IMAT) has gained worldwide interest in both research and clinical implementation due to its superior plan quality and delivery efficiency. Single-arc IMAT techniques such as the Varian RapidArc(TM) deliver conformal dose distributions to the target in one single gantry rotation, resulting in a delivery time in the order of 2 min. The segments in these techniques are evenly distributed within an arc and are allowed to have different monitor unit (MU) weightings. Therefore, a variable dose-rate (VDR) is required for delivery. Because the VDR requirement complicates the control hardware and software of the linear accelerators (linacs) and prevents most existing linacs from delivering IMAT, we propose an alternative planning approach for IMAT using constant dose-rate (CDR) delivery with variable angular spacing. We prove the equivalence by converting VDR-optimized RapidArc plans to CDR plans, where the evenly spaced beams in the VDR plan are redistributed to uneven spacing such that the segments with larger MU weighting occupy a greater angular interval. To minimize perturbation in the optimized dose distribution, the angular deviation of the segments was restricted to ≤± 5 deg. This restriction requires the treatment arc to be broken into multiple sectors such that the local MU fluctuation within each sector is reduced, thereby lowering the angular deviation of the segments during redistribution. The converted CDR plans were delivered with a single gantry sweep as in the VDR plans but each sector was delivered with a different value of CDR. For four patient cases, including two head-and-neck, one brain and one prostate, all CDR plans developed with the variable spacing scheme produced similar dose distributions to the original VDR plans. For plans with complex angular MU distributions, the number of sectors increased up to four in the CDR plans in order to maintain the original plan quality. Since each sector was

Modeling Nonlinear Change via Latent Change and Latent Acceleration Frameworks: Examining Velocity and Acceleration of Growth Trajectories

Science.gov (United States)

Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele

2013-01-01

We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…

A hybrid choice model with nonlinear utility functions and bounded distributions for latent variables : application to purchase intention decisions of electric cars

NARCIS (Netherlands)

Kim, J.; Rasouli, S.; Timmermans, H.J.P.

2014-01-01

The hybrid choice model (HCM) provides a powerful framework to account for heterogeneity across decision-makers in terms of different underlying latent attitudes. Typically, effects of the latent attitudes have been represented assuming linear utility functions. In contributing to the further

Variability in proactive and reactive cognitive control processes across the adult lifespan

Directory of Open Access Journals (Sweden)

Frini eKarayanidis

2011-11-01

Full Text Available Task-switching paradigms produce a highly consistent age-related increase in mixing cost (longer RT on repeat trials in mixed-task than single task blocks but a less consistent age effect on switch cost (longer RT on switch than repeat trials in mixed-task blocks. We use two approaches to examine the adult lifespan trajectory of control processes contributing to mixing cost and switch cost: latent variables derived from an evidence accumulation model of choice, and event-related potentials (ERP that temporally differentiate proactive (cue-driven and reactive (target-driven control processes. Under highly practiced and prepared task conditions, ageing was associated with increasing RT mixing cost but reducing RT switch cost. Both effects were largely due to the same cause: an age effect for mixed-repeat trials. In terms of latent variables, increasing age was associated with slower non-decision processes, slower rate of evidence accumulation about the target, and higher response criterion. Age effects on mixing costs were evident only on response criterion, the amount of evidence required to trigger a decision, whereas age effects on switch cost were present for all three latent variables. ERPs showed age-related increases in preparation for mixed-repeat trials, anticipatory attention, and post-target interference. Cue-locked ERPs that are linked to proactive control were associated with early emergence of age differences in response criterion. These results are consistent with age effects on strategic processes controlling decision caution. Consistent with an age-related decline in cognitive flexibility, younger adults flexibly adjusted response criterion from trial-to-trial on mixed-task blocks, whereas older adults maintained a high criterion for all trials.

Production of a phage-displayed single chain variable fragment ...

African Journals Online (AJOL)

Purpose: To develop specific single chain variable fragments (scFv) against infectious bursal disease virus (IBDV) via phage display technology. Methods: Purified viruses were initially applied for iterative panning rounds of scFv phage display libraries. The binding ability of the selected scFv antibody fragments against the ...

Effect of Progesterone on Latent Phase Prolongation in Patients With Preterm Premature Rupture of Membranes

Directory of Open Access Journals (Sweden)

Fatemeh Abdali

2018-01-01

Full Text Available Preterm premature rupture of membranes (PPROM is a condition leading to an increased risk of maternal and neonatal morbidity and mortality in pregnant women. To prevent this complication, some studies have proposed using prophylactic progesterone. However, due to lack of sufficient relevant data, there is still need for further studies in this regard. This study was performed to determine the effect of rectal progesterone on the latent phase and maternal and neonatal outcome variables in females with PPROM. During the present randomized clinical trial study (IRCT201512077676N4, a total of 120 patients with PPROM at pregnancy ages between 26 and 32 weeks were randomly assigned to 2 equal intervention and control groups. In the intervention group, progesterone suppositories (400 mg per night were administered until delivery or completion of the 34th gestational week and was compared with placebo effect in control group. The latent phase and maternal and neonatal outcome variables were compared between the two groups. The mean age of patients was 29.56±5.66 (19-42 and 29.88±5.57 (17-40 years in the intervention and control group, respectively. The two groups were almost identical in the confounding factors. The median latent phase was 8.5 days in the intervention group vs. 5 days in the control group in the 28th-30th weeks of gestation, which was significantly higher in the intervention group (P=0.001. Among maternal and neonatal outcome variables, only the mean birth-weight was significantly higher in the intervention group than that in the controls (1609.92±417.28 gr vs. 1452.03±342.35 gr, P=0.03. Administration of progesterone suppository in patients with PPROM at gestational ages of 28 to 30 weeks is effective in elongating the latent phase and increasing birth-weight with no significant complications.

Scan-rate and vacuum pressure dependence of the nucleation and growth dynamics in a spin-crossover single crystal: the role of latent heat.

Science.gov (United States)

Ridier, Karl; Rat, Sylvain; Salmon, Lionel; Nicolazzi, William; Molnár, Gábor; Bousseksou, Azzedine

2018-04-04

Using optical microscopy we studied the vacuum pressure dependence (0.1-1000 mbar) of the nucleation and growth dynamics of the thermally induced first-order spin transition in a single crystal of the spin-crossover compound [Fe(HB(tz)3)2] (tz = 1,2,4-triazol-1-yl). A crossover between a quasi-static hysteresis regime and a temperature-scan-rate-dependent kinetic regime is evidenced around 5 mbar due to the change of the heat exchange coupling between the crystal and its external environment. Remarkably, the absorption/dissipation rate of latent heat was identified as the key factor limiting the switching speed of the crystal.

Using existing questionnaires in latent class analysis

DEFF Research Database (Denmark)

Nielsen, Anne Molgaard; Vach, Werner; Kent, Peter

2016-01-01

BACKGROUND: Latent class analysis (LCA) is increasingly being used in health research, but optimal approaches to handling complex clinical data are unclear. One issue is that commonly used questionnaires are multidimensional, but expressed as summary scores. Using the example of low back pain (LBP......), the aim of this study was to explore and descriptively compare the application of LCA when using questionnaire summary scores and when using single items to subgrouping of patients based on multidimensional data. MATERIALS AND METHODS: Baseline data from 928 LBP patients in an observational study were...

Shallow and Deep Latent Heating Modes Over Tropical Oceans Observed with TRMM PR Spectral Latent Heating Data

Science.gov (United States)

Takayabu, Yukari N.; Shige, Shoichi; Tao, Wei-Kuo; Hirota, Nagio

2010-01-01

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. Three-dimensional distributions of latent heating estimated from Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR)utilizing the Spectral Latent Heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated latent heating averaged over the tropical oceans is estimated as approx.72.6 J/s (approx.2.51 mm/day), and that over tropical land is approx.73.7 J/s (approx.2.55 mm/day), for 30degN-30degS. It is shown that non-drizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems, deep systems and congestus. A rough estimate of shallow mode contribution against the total heating is about 46.7 % for the average tropical oceans, which is substantially larger than 23.7 % over tropical land. While cumulus congestus heating linearly correlates with the SST, deep mode is dynamically bounded by large-scale subsidence. It is notable that substantial amount of rain, as large as 2.38 mm day-1 in average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that even in the region with SST warmer than 28 oC, large-scale subsidence effectively suppresses the deep convection, remaining the heating by congestus clouds. Our results support that the entrainment of mid-to-lower-tropospheric dry air, which accompanies the large

A hybrid choice model with a nonlinear utility function and bounded distribution for latent variables : application to purchase intention decisions of electric cars

NARCIS (Netherlands)

Kim, J.; Rasouli, S.; Timmermans, H.J.P.

2016-01-01

The hybrid choice model (HCM) provides a powerful framework to account for heterogeneity across decision-makers in terms of different underlying latent attitudes. Typically, effects of the latent attitudes have been represented assuming linear utility functions. In contributing to the further

Accounting for standard errors of vision-specific latent trait in regression models.

Science.gov (United States)

Wong, Wan Ling; Li, Xiang; Li, Jialiang; Wong, Tien Yin; Cheng, Ching-Yu; Lamoureux, Ecosse L

2014-07-11

To demonstrate the effectiveness of Hierarchical Bayesian (HB) approach in a modeling framework for association effects that accounts for SEs of vision-specific latent traits assessed using Rasch analysis. A systematic literature review was conducted in four major ophthalmic journals to evaluate Rasch analysis performed on vision-specific instruments. The HB approach was used to synthesize the Rasch model and multiple linear regression model for the assessment of the association effects related to vision-specific latent traits. The effectiveness of this novel HB one-stage "joint-analysis" approach allows all model parameters to be estimated simultaneously and was compared with the frequently used two-stage "separate-analysis" approach in our simulation study (Rasch analysis followed by traditional statistical analyses without adjustment for SE of latent trait). Sixty-six reviewed articles performed evaluation and validation of vision-specific instruments using Rasch analysis, and 86.4% (n = 57) performed further statistical analyses on the Rasch-scaled data using traditional statistical methods; none took into consideration SEs of the estimated Rasch-scaled scores. The two models on real data differed for effect size estimations and the identification of "independent risk factors." Simulation results showed that our proposed HB one-stage "joint-analysis" approach produces greater accuracy (average of 5-fold decrease in bias) with comparable power and precision in estimation of associations when compared with the frequently used two-stage "separate-analysis" procedure despite accounting for greater uncertainty due to the latent trait. Patient-reported data, using Rasch analysis techniques, do not take into account the SE of latent trait in association analyses. The HB one-stage "joint-analysis" is a better approach, producing accurate effect size estimations and information about the independent association of exposure variables with vision-specific latent traits

Adolescent substance use behavior and suicidal behavior for boys and girls: a cross-sectional study by latent analysis approach.

Science.gov (United States)

Wang, Peng-Wei; Yen, Cheng-Fang

2017-12-08

Adolescent suicidal behavior may consist of different symptoms, including suicidal ideation, suicidal planning and suicidal attempts. Adolescent substance use behavior may contribute to adolescent suicidal behavior. However, research on the relationships between specific substance use and individual suicidal behavior is insufficient, as adolescents may not use only one substance or develop only one facet of suicidal behavior. Latent variables permit us to describe the relationships between clusters of related behaviors more accurately than studying the relationships between specific behaviors. Thus, the aim of this study was to explore how adolescent substance use behavior contributes to suicidal behavior using latent variables representing adolescent suicidal and substance use behaviors. A total of 13,985 adolescents were recruited using a stratified random sampling strategy. The participants indicated whether they had experienced suicidal ideation, planning and attempts and reported their cigarette, alcohol, ketamine and MDMA use during the past year. Latent analysis was used to examine the relationship between substance use and suicidal behavior. Adolescents who used any one of the above substances exhibited more suicidal behavior. The results of latent variables analysis revealed that adolescent substance use contributed to suicidal behavior and that boys exhibited more severe substance use behavior than girls. However, there was no gender difference in the association between substance use and suicidal behavior. Substance use behavior in adolescents is related to more suicidal behavior. In addition, the contribution of substance use to suicidal behavior does not differ between genders.

Latent constructs of the autobiographical memory questionnaire: a recollection-belief model of autobiographical experience.

Science.gov (United States)

Fitzgerald, Joseph M; Broadbridge, Carissa L

2013-01-01

Many researchers employ single-item scales of subjective experiences such as imagery and confidence to assess autobiographical memory. We tested the hypothesis that four latent constructs, recollection, belief, impact, and rehearsal, account for the variance in commonly used scales across four different types of autobiographical memory: earliest childhood memory, cue word memory of personal experience, highly vivid memory, and most stressful memory. Participants rated each memory on scales hypothesised to be indicators of one of four latent constructs. Multi-group confirmatory factor analyses and structural analyses confirmed the similarity of the latent constructs of recollection, belief, impact, and rehearsal, as well as the similarity of the structural relationships among those constructs across memory type. The observed pattern of mean differences between the varieties of autobiographical experiences was consistent with prior research and theory in the study of autobiographical memory.

Analysis on the public acceptance of nuclear energy using structural equation model with latent variables

International Nuclear Information System (INIS)

Lee, Young Eal

1996-02-01

Comparison of the effect of education and public information on the public acceptance of nuclear energy is carried out. For the increase of public acceptance, the correct understanding on the nuclear energy via proper regular school education would be the first basis and the appropriate public information services by utility and unbiased mass media would be the second basis. Subjects that which is more effect in education or information and how much effective quantitatively to improve the public acceptance are derived. Structural Equation Model (SEM) with Latent Variables (LVs) in social science to public attitudes towards nuclear energy is developed. Questionnaire is conducted to respondents who took part in the program of visiting the nuclear power plant opened by OKAEA in 1995. As a result of the analysis, effect of education for correct awareness of nuclear energy is more sensitive to public acceptance than that of information. It is shown that the susceptibility in education factor in influence of radiation on human body and that in information factor persons consider nuclear power plant as an environmental polluter. It is concluded that radiation treatment should be a 'Hand on Experience' and general principle of nuclear power generation should be contained in the educational text book. Education and information should not been independently performed but been carried out simultaneously and mutually aided. It is shown that this modeling approach is useful to make the decision for the long-term nuclear energy policy transparent and successful

Bayesian modeling of measurement error in predictor variables

NARCIS (Netherlands)

Fox, Gerardus J.A.; Glas, Cornelis A.W.

2003-01-01

It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between

Fatal and serious road crashes involving young New Zealand drivers: a latent class clustering approach

DEFF Research Database (Denmark)

Weiss, Harold B.; Kaplan, Sigal; Prato, Carlo Giacomo

2016-01-01

, infrastructure characteristics, environmental conditions, demographic characteristics, driving behaviour, and pre-crash manoeuvres. The analysis yielded 15 and 8 latent classes of, respectively, single-vehicle and multi-vehicle crashes, and average posterior probabilities measured the odds of correct...

Are Anxiety and Depression Just as Stable as Personality During Late Adolescence? Results From a Three-Year Longitudinal Latent Variable Study

Science.gov (United States)

Prenoveau, Jason M.; Craske, Michelle G.; Zinbarg, Richard E.; Mineka, Susan; Rose, Raphael D.; Griffith, James W.

2012-01-01

Although considerable evidence shows that affective symptoms and personality traits demonstrate moderate to high relative stabilities during adolescence and early adulthood, there has been little work done to examine differential stability among these constructs or to study the manner in which the stability of these constructs is expressed. The present study used a three-year longitudinal design in an adolescent/young adult sample to examine the stability of depression symptoms, social phobia symptoms, specific phobia symptoms, neuroticism, and extraversion. When considering one-, two-, and three-year durations, anxiety and personality stabilities were generally similar and typically greater than the stability of depression. Comparison of various representations of a latent variable trait-state-occasion (TSO) model revealed that whereas the full TSO model was the best representation for depression, a trait stability model was the most parsimonious of the best-fitting models for the anxiety and personality constructs. Over three years, the percentages of variance explained by the trait component for the anxiety and personality constructs (73– 84%) were significantly greater than that explained by the trait component for depression (46%). These findings indicate that symptoms of depression are more episodic in nature, whereas symptoms of anxiety are more similar to personality variables in their expression of stability. PMID:21604827

Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling

Science.gov (United States)

Cheong, JeeWon; MacKinnon, David P.; Khoo, Siek Toon

2010-01-01

This study investigated a method to evaluate mediational processes using latent growth curve modeling. The mediator and the outcome measured across multiple time points were viewed as 2 separate parallel processes. The mediational process was defined as the independent variable influencing the growth of the mediator, which, in turn, affected the growth of the outcome. To illustrate modeling procedures, empirical data from a longitudinal drug prevention program, Adolescents Training and Learning to Avoid Steroids, were used. The program effects on the growth of the mediator and the growth of the outcome were examined first in a 2-group structural equation model. The mediational process was then modeled and tested in a parallel process latent growth curve model by relating the prevention program condition, the growth rate factor of the mediator, and the growth rate factor of the outcome. PMID:20157639

Application of a latent class analysis to empirically define eating disorder phenotypes.

Science.gov (United States)

Keel, Pamela K; Fichter, Manfred; Quadflieg, Norbert; Bulik, Cynthia M; Baxter, Mark G; Thornton, Laura; Halmi, Katherine A; Kaplan, Allan S; Strober, Michael; Woodside, D Blake; Crow, Scott J; Mitchell, James E; Rotondo, Alessandro; Mauri, Mauro; Cassano, Giovanni; Treasure, Janet; Goldman, David; Berrettini, Wade H; Kaye, Walter H

2004-02-01

Diagnostic criteria for eating disorders influence how we recognize, research, and treat eating disorders, and empirically valid phenotypes are required for revealing their genetic bases. To empirically define eating disorder phenotypes. Data regarding eating disorder symptoms and features from 1179 individuals with clinically significant eating disorders were submitted to a latent class analysis. The resulting latent classes were compared on non-eating disorder variables in a series of validation analyses. Multinational, collaborative study with cases ascertained through diverse clinical settings (inpatient, outpatient, and community). Members of affected relative pairs recruited for participation in genetic studies of eating disorders in which probands met DSM-IV-TR criteria for anorexia nervosa (AN) or bulimia nervosa and had at least 1 biological relative with a clinically significant eating disorder. Main Outcome Measure Number and clinical characterization of latent classes. A 4-class solution provided the best fit. Latent class 1 (LC1) resembled restricting AN; LC2, AN and bulimia nervosa with the use of multiple methods of purging; LC3, restricting AN without obsessive-compulsive features; and LC4, bulimia nervosa with self-induced vomiting as the sole form of purging. Biological relatives were significantly likely to belong to the same latent class. Across validation analyses, LC2 demonstrated the highest levels of psychological disturbance, and LC3 demonstrated the lowest. The presence of obsessive-compulsive features differentiates among individuals with restricting AN. Similarly, the combination of low weight and multiple methods of purging distinguishes among individuals with binge eating and purging behaviors. These results support some of the distinctions drawn within the DSM-IV-TR among eating disorder subtypes, while introducing new features to define phenotypes.

Stability of latent class segments over time

DEFF Research Database (Denmark)

Mueller, Simone

2011-01-01

Dynamic stability, as the degree to which identified segments at a given time remain unchanged over time in terms of number, size and profile, is a desirable segment property which has received limited attention so far. This study addresses the question to what degree latent classes identified from...... logit model suggests significant changes in the price sensitivity and the utility from environmental claims between both experimental waves. A pooled scale adjusted latent class model is estimated jointly over both waves and the relative size of latent classes is compared across waves, resulting...... in significant differences in the size of two out of seven classes. These differences can largely be accounted for by the changes on the aggregated level. The relative size of latent classes is correlated at 0.52, suggesting a fair robustness. An ex-post characterisation of latent classes by behavioural...

Refreshing the Aged Latent Fingerprints with Ionizing Radiation Prior to the Cyanoacrylate Fuming Procedure: A Preliminary Study.

Science.gov (United States)

Ristova, Mimoza M; Radiceska, Pavlina; Bozinov, Igorco; Barandovski, Lambe

2016-05-01

One of the crucial factors determining the cyanoacrylate deposit quality over latent fingerprints appeared to be the extent of the humidity. This work focuses on the enhancement/refreshment of age-degraded latent fingerprints by irradiating the samples with UV, X-ray, or thermal neutrons prior to the cyanoacrylate (CA) fuming. Age degradation of latent fingerprints deposited on glass surfaces was examined through the decrease in the number of characteristic minutiae counts over time. A term "critical day" was introduced for the time at which the average number of identifiable minutiae definitions drops to one-half. Fingerprints older than their "critical day" were exposed to either UV, X-ray, or thermal neutrons. Identical reference samples were kept unexposed. All samples, both reference and irradiated, were developed during a single CA fuming procedure. Comparative latent fingerprint analysis showed that exposure to ionizing radiation enhances the CA fuming, yielding a 20-30% increase in average minutiae count. © 2015 American Academy of Forensic Sciences.

What is significant about a single nursing session? An exploratory study.

Science.gov (United States)

Miller, Elizabeth M

2017-09-10

Researchers and clinicians specializing in breastfeeding often rely on measuring one nursing session to characterize the breastfeeding relationship. However, less is known about the descriptive or statistically predictive characteristics of one nursing session. The purposes of this study are twofold: (1) to explore the relationships between variables in a single nursing session; and (2) to study the association between variables in a single nursing session and infant length-for-age (LAZ) and weight-for-age (WAZ). In 63 nursing mother-infant pairs in the United States, anthropometric measurement and observation of a single nursing session revealed six nursing session variables: fore milk fat percent, hind milk fat percent, infant milk intake, duration of session, time since last session, and time of day of session. A principle factor analysis, undertaken to explore latent variables underlying the six session variables, revealed two factors: (1) loaded highly on fore and hind milk fat percentage, reflecting the overall fat percent in a feed; and (2) loaded highly on milk intake and hind milk fat percentage, indicating the process of breast emptying. In multivariate analyses of all session variables on infant LAZ and WAZ, only hind milk fat percentage was significantly negatively associated with LAZ (β = -0.14, P = .01 (two-tailed), R 2  = 0.070), confirmed by a significant negative association between LAZ and factor one (β = -0.32, P = .05 (two-tailed), R 2  = 0.090). This research describes the dynamics of a single nursing session, and has the potential to help explain variation in infant growth and nutrition. © 2017 Wiley Periodicals, Inc.

Executive functions cannot be distinguished from general intelligence: Two variations on a single theme within a symphony of latent variance

Directory of Open Access Journals (Sweden)

Donald R Royall

2014-10-01

Full Text Available The empirical foundation of executive control function (ECF remains controversial. We have employed structural equation models (SEM to explicitly distinguish domain-specific variance in ECF performance from memory (MEM and shared cognitive performance variance, i.e., Spearman’s g. ECF does not survive adjustment for both MEM and g in a well fitting model of data obtained from non-demented older persons (N = 193. Instead, the variance in putative ECF measures is attributable only to g, and related to functional status only through a fraction of that construct (i.e., dECF. dECF is a homolog of the latent variable δ, which we have previously associated specifically with the Default Mode Network (DMN. These findings undermine the validity of ECF and its putative association with the frontal lobe. ECF may have no existence independent of general intelligence, and no functionally salient association with the frontal lobe outside of that structure’s contribution to the DMN.

Using a latent variable model with non-constant factor loadings to examine PM2.5 constituents related to secondary inorganic aerosols.

Science.gov (United States)

Zhang, Zhenzhen; O'Neill, Marie S; Sánchez, Brisa N

2016-04-01

Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM 2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions.

Detecting New Words from Chinese Text Using Latent Semi-CRF Models

Science.gov (United States)

Sun, Xiao; Huang, Degen; Ren, Fuji

Chinese new words and their part-of-speech (POS) are particularly problematic in Chinese natural language processing. With the fast development of internet and information technology, it is impossible to get a complete system dictionary for Chinese natural language processing, as new words out of the basic system dictionary are always being created. A latent semi-CRF model, which combines the strengths of LDCRF (Latent-Dynamic Conditional Random Field) and semi-CRF, is proposed to detect the new words together with their POS synchronously regardless of the types of the new words from the Chinese text without being pre-segmented. Unlike the original semi-CRF, the LDCRF is applied to generate the candidate entities for training and testing the latent semi-CRF, which accelerates the training speed and decreases the computation cost. The complexity of the latent semi-CRF could be further adjusted by tuning the number of hidden variables in LDCRF and the number of the candidate entities from the Nbest outputs of the LDCRF. A new-words-generating framework is proposed for model training and testing, under which the definitions and distributions of the new words conform to the ones existing in real text. Specific features called “Global Fragment Information” for new word detection and POS tagging are adopted in the model training and testing. The experimental results show that the proposed method is capable of detecting even low frequency new words together with their POS tags. The proposed model is found to be performing competitively with the state-of-the-art models presented.

Biomarkers of latent TB infection

DEFF Research Database (Denmark)

Ruhwald, Morten; Ravn, Pernille

2009-01-01

For the last 100 years, the tuberculin skin test (TST) has been the only diagnostic tool available for latent TB infection (LTBI) and no biomarker per se is available to diagnose the presence of LTBI. With the introduction of M. tuberculosis-specific IFN-gamma release assays (IGRAs), a new area...... of in vitro immunodiagnostic tests for LTBI based on biomarker readout has become a reality. In this review, we discuss existing evidence on the clinical usefulness of IGRAs and the indefinite number of potential new biomarkers that can be used to improve diagnosis of latent TB infection. We also present...... early data suggesting that the monocyte-derived chemokine inducible protein-10 may be useful as a novel biomarker for the immunodiagnosis of latent TB infection....

UNSOLVED AND LATENT CRIME: DIFFERENCES AND SIMILARITIES

Directory of Open Access Journals (Sweden)

Mikhail Kleymenov

2017-01-01

Full Text Available УДК 343Purpose of the article is to study the specific legal and informational nature of the unsolved crime in comparison with the phenomenon of delinquency, special study and analysis to improve the efficiency of law enforcement.Methods of research are abstract-logical, systematic, statistical, study of documents. The main results of research. Unsolved crime has specific legal, statistical and informational na-ture as the crime phenomenon, which is expressed in cumulative statistical population of unsolved crimes. An array of unsolved crimes is the sum of the number of acts, things of which is suspended and not terminated. The fault of the perpetrator in these cases is not proven, they are not considered by the court, it is not a conviction. Unsolved crime must be registered. Latent crime has a different informational nature. The main symptom of latent crimes is the uncertainty for the subjects of law enforcement, which delegated functions of identification, registration and accounting. Latent crime is not recorded. At the same time, there is a "border" area between the latent and unsolved crimes, which includes covered from the account of the crime. In modern Russia the majority of crimes covered from accounting by passing the decision about refusal in excitation of criminal case. Unsolved crime on their criminogenic consequences represents a significant danger to the public is higher compared to latent crime.It is conducted in the article a special analysis of the differences and similarities in the unsolved latent crime for the first time in criminological literature.The analysis proves the need for radical changes in the current Russian assessment of the state of crime and law enforcement to solve crimes. The article argues that an unsolved crime is a separate and, in contrast to latent crime, poorly understood phenomenon. However unsolved latent crime and have common features and areas of interaction.

Latent geometry of bipartite networks

Science.gov (United States)

Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

2017-03-01

Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

Pathways of early fatherhood, marriage, and employment: a latent class growth analysis.

Science.gov (United States)

Dariotis, Jacinda K; Pleck, Joseph H; Astone, Nan M; Sonenstein, Freya L

2011-05-01

In the National Longitudinal Survey of Youth 1979 (NLSY79), young fathers include heterogeneous subgroups with varying early life pathways in terms of fatherhood timing, the timing of first marriage, and holding full-time employment. Using latent class growth analysis with 10 observations between ages 18 and 37, we derived five latent classes with median ages of first fatherhood below the cohort median (26.4), constituting distinct early fatherhood pathways representing 32.4% of NLSY men: (A) Young Married Fathers, (B) Teen Married Fathers, (C) Young Underemployed Married Fathers, (D) Young Underemployed Single Fathers, and (E) Young Later-Marrying Fathers. A sixth latent class of men who become fathers around the cohort median, following full-time employment and marriage (On-Time On-Sequence Fathers), is the comparison group. With sociodemographic background controlled, all early fatherhood pathways show disadvantage in at least some later-life circumstances (earnings, educational attainment, marital status, and incarceration). The extent of disadvantage is greater when early fatherhood occurs at relatively younger ages (before age 20), occurs outside marriage, or occurs outside full-time employment. The relative disadvantage associated with early fatherhood, unlike early motherhood, increases over the life course.

Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

DEFF Research Database (Denmark)

Mølgaard Nielsen, Anne; Hestbaek, Lise; Vach, Werner

2017-01-01

. Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two...

Latent hardening size effect in small-scale plasticity

Science.gov (United States)

Bardella, Lorenzo; Segurado, Javier; Panteghini, Andrea; Llorca, Javier

2013-07-01

We aim at understanding the multislip behaviour of metals subject to irreversible deformations at small-scales. By focusing on the simple shear of a constrained single-crystal strip, we show that discrete Dislocation Dynamics (DD) simulations predict a strong latent hardening size effect, with smaller being stronger in the range [1.5 µm, 6 µm] for the strip height. We attempt to represent the DD pseudo-experimental results by developing a flow theory of Strain Gradient Crystal Plasticity (SGCP), involving both energetic and dissipative higher-order terms and, as a main novelty, a strain gradient extension of the conventional latent hardening. In order to discuss the capability of the SGCP theory proposed, we implement it into a Finite Element (FE) code and set its material parameters on the basis of the DD results. The SGCP FE code is specifically developed for the boundary value problem under study so that we can implement a fully implicit (Backward Euler) consistent algorithm. Special emphasis is placed on the discussion of the role of the material length scales involved in the SGCP model, from both the mechanical and numerical points of view.

Latent hardening size effect in small-scale plasticity

International Nuclear Information System (INIS)

Bardella, Lorenzo; Panteghini, Andrea; Segurado, Javier; Llorca, Javier

2013-01-01

We aim at understanding the multislip behaviour of metals subject to irreversible deformations at small-scales. By focusing on the simple shear of a constrained single-crystal strip, we show that discrete Dislocation Dynamics (DD) simulations predict a strong latent hardening size effect, with smaller being stronger in the range [1.5 µm, 6 µm] for the strip height. We attempt to represent the DD pseudo-experimental results by developing a flow theory of Strain Gradient Crystal Plasticity (SGCP), involving both energetic and dissipative higher-order terms and, as a main novelty, a strain gradient extension of the conventional latent hardening. In order to discuss the capability of the SGCP theory proposed, we implement it into a Finite Element (FE) code and set its material parameters on the basis of the DD results. The SGCP FE code is specifically developed for the boundary value problem under study so that we can implement a fully implicit (Backward Euler) consistent algorithm. Special emphasis is placed on the discussion of the role of the material length scales involved in the SGCP model, from both the mechanical and numerical points of view. (paper)

A flexible latent class approach to estimating test-score reliability

NARCIS (Netherlands)

van der Palm, D.W.; van der Ark, L.A.; Sijtsma, K.

2014-01-01

The latent class reliability coefficient (LCRC) is improved by using the divisive latent class model instead of the unrestricted latent class model. This results in the divisive latent class reliability coefficient (DLCRC), which unlike LCRC avoids making subjective decisions about the best solution

Extraction of latent images from printed media

Science.gov (United States)

Sergeyev, Vladislav; Fedoseev, Victor

2015-12-01

In this paper we propose an automatic technology for extraction of latent images from printed media such as documents, banknotes, financial securities, etc. This technology includes image processing by adaptively constructed Gabor filter bank for obtaining feature images, as well as subsequent stages of feature selection, grouping and multicomponent segmentation. The main advantage of the proposed technique is versatility: it allows to extract latent images made by different texture variations. Experimental results showing performance of the method over another known system for latent image extraction are given.

Enumeration of Combinatorial Classes of Single Variable Complex Polynomial Vector Fields

DEFF Research Database (Denmark)

Dias, Kealey

A vector field in the space of degree d monic, centered single variable complex polynomial vector fields has a combinatorial structure which can be fully described by a combinatorial data set consisting of an equivalence relation and a marked subset on the integers mod 2d-2, satisfying certain...

Latent transition analysis of pre-service teachers' efficacy in mathematics and science

Science.gov (United States)

Ward, Elizabeth Kennedy

This study modeled changes in pre-service teacher efficacy in mathematics and science over the course of the final year of teacher preparation using latent transition analysis (LTA), a longitudinal form of analysis that builds on two modeling traditions (latent class analysis (LCA) and auto-regressive modeling). Data were collected using the STEBI-B, MTEBI-r, and the ABNTMS instruments. The findings suggest that LTA is a viable technique for use in teacher efficacy research. Teacher efficacy is modeled as a construct with two dimensions: personal teaching efficacy (PTE) and outcome expectancy (OE). Findings suggest that the mathematics and science teaching efficacy (PTE) of pre-service teachers is a multi-class phenomena. The analyses revealed a four-class model of PTE at the beginning and end of the final year of teacher training. Results indicate that when pre-service teachers transition between classes, they tend to move from a lower efficacy class into a higher efficacy class. In addition, the findings suggest that time-varying variables (attitudes and beliefs) and time-invariant variables (previous coursework, previous experiences, and teacher perceptions) are statistically significant predictors of efficacy class membership. Further, analyses suggest that the measures used to assess outcome expectancy are not suitable for LCA and LTA procedures.

Fitting Latent Cluster Models for Networks with latentnet

Directory of Open Access Journals (Sweden)

Pavel N. Krivitsky

2007-12-01

Full Text Available latentnet is a package to fit and evaluate statistical latent position and cluster models for networks. Hoff, Raftery, and Handcock (2002 suggested an approach to modeling networks based on positing the existence of an latent space of characteristics of the actors. Relationships form as a function of distances between these characteristics as well as functions of observed dyadic level covariates. In latentnet social distances are represented in a Euclidean space. It also includes a variant of the extension of the latent position model to allow for clustering of the positions developed in Handcock, Raftery, and Tantrum (2007.The package implements Bayesian inference for the models based on an Markov chain Monte Carlo algorithm. It can also compute maximum likelihood estimates for the latent position model and a two-stage maximum likelihood method for the latent position cluster model. For latent position cluster models, the package provides a Bayesian way of assessing how many groups there are, and thus whether or not there is any clustering (since if the preferred number of groups is 1, there is little evidence for clustering. It also estimates which cluster each actor belongs to. These estimates are probabilistic, and provide the probability of each actor belonging to each cluster. It computes four types of point estimates for the coefficients and positions: maximum likelihood estimate, posterior mean, posterior mode and the estimator which minimizes Kullback-Leibler divergence from the posterior. You can assess the goodness-of-fit of the model via posterior predictive checks. It has a function to simulate networks from a latent position or latent position cluster model.

Multi-region and single-cell sequencing reveal variable genomic heterogeneity in rectal cancer.

Science.gov (United States)

Liu, Mingshan; Liu, Yang; Di, Jiabo; Su, Zhe; Yang, Hong; Jiang, Beihai; Wang, Zaozao; Zhuang, Meng; Bai, Fan; Su, Xiangqian

2017-11-23

Colorectal cancer is a heterogeneous group of malignancies with complex molecular subtypes. While colon cancer has been widely investigated, studies on rectal cancer are very limited. Here, we performed multi-region whole-exome sequencing and single-cell whole-genome sequencing to examine the genomic intratumor heterogeneity (ITH) of rectal tumors. We sequenced nine tumor regions and 88 single cells from two rectal cancer patients with tumors of the same molecular classification and characterized their mutation profiles and somatic copy number alterations (SCNAs) at the multi-region and the single-cell levels. A variable extent of genomic heterogeneity was observed between the two patients, and the degree of ITH increased when analyzed on the single-cell level. We found that major SCNAs were early events in cancer development and inherited steadily. Single-cell sequencing revealed mutations and SCNAs which were hidden in bulk sequencing. In summary, we studied the ITH of rectal cancer at regional and single-cell resolution and demonstrated that variable heterogeneity existed in two patients. The mutational scenarios and SCNA profiles of two patients with treatment naïve from the same molecular subtype are quite different. Our results suggest each tumor possesses its own architecture, which may result in different diagnosis, prognosis, and drug responses. Remarkable ITH exists in the two patients we have studied, providing a preliminary impression of ITH in rectal cancer.

Advanced calculus of a single variable

CERN Document Server

Geveci, Tunc

2016-01-01

This advanced undergraduate textbook is based on a one-semester course on single variable calculus that the author has been teaching at San Diego State University for many years. The aim of this classroom-tested book is to deliver a rigorous discussion of the concepts and theorems that are dealt with informally in the first two semesters of a beginning calculus course. As such, students are expected to gain a deeper understanding of the fundamental concepts of calculus, such as limits (with an emphasis on ε-δ definitions), continuity (including an appreciation of the difference between mere pointwise and uniform continuity), the derivative (with rigorous proofs of various versions of L’Hôpital’s rule) and the Riemann integral (discussing improper integrals in-depth, including the comparison and Dirichlet tests). Success in this course is expected to prepare students for more advanced courses in real and complex analysis and this book will help to accomplish this. The first semester of advanced calculus...

Cognitive psychology meets psychometric theory: on the relation between process models for decision making and latent variable models for individual differences.

Science.gov (United States)

van der Maas, Han L J; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A; Borsboom, Denny

2011-04-01

This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line of reasoning, we discuss the appropriateness of IRT for measuring abilities and bipolar traits, such as pro versus contra attitudes. Surprisingly, if a diffusion model underlies the response processes, IRT models are appropriate for bipolar traits but not for ability tests. A reconsideration of the concept of ability that is appropriate for such situations leads to a new item response model for accuracy and speed based on the idea that ability has a natural zero point. The model implies fundamentally new ways to think about guessing, response speed, and person fit in IRT. We discuss the relation between this model and existing models as well as implications for psychology and psychometrics. 2011 APA, all rights reserved

Rapid isolation of IgNAR variable single-domain antibody fragments from a shark synthetic library.

Science.gov (United States)

Shao, Cui-Ying; Secombes, Chris J; Porter, Andrew J

2007-01-01

The immunoglobulin isotype IgNAR (Novel Antigen Receptor) was discovered in the serum of the nurse shark (Ginglymostoma cirratum) and wobbegong shark (Orectolobus maculates) as a homodimer of two protein chains, each composed of a single variable domain (V) domain and five constant domains. The IgNAR variable domain contains an intact antigen-binding site and functions as an independent domain able to react to antigen with both high specificity and affinity. Here we describe the successful construction of a synthetic phage-displayed library based upon a single anti-lysozyme clone HEL-5A7 scaffold, which was previously selected from an immune IgNAR variable domain library. The complementarity-determining region 3 (CDR3) loop of this clone was varied in both length and composition and the derived library was used to pan against two model proteins, lysozyme and leptin. A single anti-lysozyme clone (Ly-X20) and anti-leptin clone (Lep-12E1) were selected for further study. Both clones were shown to be functionally expressed in Escherichia coli, extremely thermostable and bind to corresponding antigens specifically. The results here demonstrate that a synthetic IgNAR variable domain library based on a single framework scaffold can be used as a route to generate antigen binders quickly, easily and without the need of immunization.

Use of a Latent Topic Model for Characteristic Extraction from Health Checkup Questionnaire Data.

Science.gov (United States)

Hatakeyama, Y; Miyano, I; Kataoka, H; Nakajima, N; Watabe, T; Yasuda, N; Okuhara, Y

2015-01-01

When patients complete questionnaires during health checkups, many of their responses are subjective, making topic extraction difficult. Therefore, the purpose of this study was to develop a model capable of extracting appropriate topics from subjective data in questionnaires conducted during health checkups. We employed a latent topic model to group the lifestyle habits of the study participants and represented their responses to items on health checkup questionnaires as a probability model. For the probability model, we used latent Dirichlet allocation to extract 30 topics from the questionnaires. According to the model parameters, a total of 4381 study participants were then divided into groups based on these topics. Results from laboratory tests, including blood glucose level, triglycerides, and estimated glomerular filtration rate, were compared between each group, and these results were then compared with those obtained by hierarchical clustering. If a significant (p topic model and hierarchical clustering grouping revealed that, in the latent topic model method, a small group of participants who reported having subjective signs of urinary disorder were allocated to a single group. The latent topic model is useful for extracting characteristics from a small number of groups from questionnaires with a large number of items. These results show that, in addition to chief complaints and history of past illness, questionnaire data obtained during medical checkups can serve as useful judgment criteria for assessing the conditions of patients.

Dissociative Experiences are Associated with Obsessive-Compulsive Symptoms in a Non-clinical Sample: A Latent Profile Analysis

Science.gov (United States)

BOYSAN, Murat

2014-01-01

Introduction There has been a burgeoning literature considering the significant associations between obsessive-compulsive symptoms and dissociative experiences. In this study, the relationsips between dissociative symtomotology and dimensions of obsessive-compulsive symptoms were examined in homogeneous sub-groups obtained with latent class algorithm in an undergraduate Turkish sample. Method Latent profile analysis, a recently developed classification method based on latent class analysis, was applied to the Dissociative Experiences Scale (DES) item-response data from 2976 undergraduates. Differences in severity of obsessive-compulsive symptoms, anxiety and depression across groups were evaluated by running multinomial logistic regression analyses. Associations between latent class probabilities and psychological variables in terms of obsessive-compulsive sub-types, anxiety, and depression were assessed by computing Pearson’s product-moment correlation coefficients. Results The findings of the latent profile analysis supported further evidence for discontinuity model of dissociative experiences. The analysis empirically justified the distinction among three sub-groups based on the DES items. A marked proportion of the sample (42%) was assigned to the high dissociative class. In the further analyses, all sub-types of obsessive-compulsive symptoms significantly differed across latent classes. Regarding the relationships between obsessive-compulsive symptoms and dissociative symptomatology, low dissociation appeared to be a buffering factor dealing with obsessive-compulsive symptoms; whereas high dissociation appeared to be significantly associated with high levels of obsessive-compulsive symptoms. Conclusion It is concluded that the concept of dissociation can be best understood in a typological approach that dissociative symptomatology not only exacerbates obsessive-compulsive symptoms but also serves as an adaptive coping mechanism. PMID:28360635

cn.FARMS: a latent variable model to detect copy number variations in microarray data with a low false discovery rate.

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Clevert, Djork-Arné; Mitterecker, Andreas; Mayr, Andreas; Klambauer, Günter; Tuefferd, Marianne; De Bondt, An; Talloen, Willem; Göhlmann, Hinrich; Hochreiter, Sepp

2011-07-01

Cost-effective oligonucleotide genotyping arrays like the Affymetrix SNP 6.0 are still the predominant technique to measure DNA copy number variations (CNVs). However, CNV detection methods for microarrays overestimate both the number and the size of CNV regions and, consequently, suffer from a high false discovery rate (FDR). A high FDR means that many CNVs are wrongly detected and therefore not associated with a disease in a clinical study, though correction for multiple testing takes them into account and thereby decreases the study's discovery power. For controlling the FDR, we propose a probabilistic latent variable model, 'cn.FARMS', which is optimized by a Bayesian maximum a posteriori approach. cn.FARMS controls the FDR through the information gain of the posterior over the prior. The prior represents the null hypothesis of copy number 2 for all samples from which the posterior can only deviate by strong and consistent signals in the data. On HapMap data, cn.FARMS clearly outperformed the two most prevalent methods with respect to sensitivity and FDR. The software cn.FARMS is publicly available as a R package at http://www.bioinf.jku.at/software/cnfarms/cnfarms.html.

A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model.

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Feeney, Daniel F; Meyer, François G; Noone, Nicholas; Enoka, Roger M

2017-10-01

Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal

Bayesian inference for an illness-death model for stroke with cognition as a latent time-dependent risk factor

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Hout A. van den; Fox J.P.; Klein Entink R.H.

2015-01-01

Longitudinal data can be used to estimate the transition intensities between healthy and unhealthy states prior to death. An illness-death model for history of stroke is presented, where time-dependent transition intensities are regressed on a latent variable representing cognitive function. The

Tropical Gravity Wave Momentum Fluxes and Latent Heating Distributions

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Geller, Marvin A.; Zhou, Tiehan; Love, Peter T.

2015-01-01

Recent satellite determinations of global distributions of absolute gravity wave (GW) momentum fluxes in the lower stratosphere show maxima over the summer subtropical continents and little evidence of GW momentum fluxes associated with the intertropical convergence zone (ITCZ). This seems to be at odds with parameterizations forGWmomentum fluxes, where the source is a function of latent heating rates, which are largest in the region of the ITCZ in terms of monthly averages. The authors have examined global distributions of atmospheric latent heating, cloud-top-pressure altitudes, and lower-stratosphere absolute GW momentum fluxes and have found that monthly averages of the lower-stratosphere GW momentum fluxes more closely resemble the monthly mean cloud-top altitudes rather than the monthly mean rates of latent heating. These regions of highest cloud-top altitudes occur when rates of latent heating are largest on the time scale of cloud growth. This, plus previously published studies, suggests that convective sources for stratospheric GW momentum fluxes, being a function of the rate of latent heating, will require either a climate model to correctly model this rate of latent heating or some ad hoc adjustments to account for shortcomings in a climate model's land-sea differences in convective latent heating.

Learning Latent Vector Spaces for Product Search

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Van Gysel, C.; de Rijke, M.; Kanoulas, E.

2016-01-01

We introduce a novel latent vector space model that jointly learns the latent representations of words, e-commerce products and a mapping between the two without the need for explicit annotations. The power of the model lies in its ability to directly model the discriminative relation between

High-fidelity teleportation of continuous-variable quantum States using delocalized single photons

DEFF Research Database (Denmark)

Andersen, Ulrik L; Ralph, Timothy C

2013-01-01

Traditional continuous-variable teleportation can only approach unit fidelity in the limit of an infinite (and unphysical) amount of squeezing. We describe a new method for continuous-variable teleportation that approaches unit fidelity with finite resources. The protocol is not based on squeezed...... states as in traditional teleportation but on an ensemble of single photon entangled states. We characterize the teleportation scheme with coherent states, mesoscopic superposition states, and two-mode squeezed states and we find several situations in which near-unity teleportation fidelity can...

Cytokine profile in patients with early latent syphilis

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Zakharov S.V.

2018-03-01

Full Text Available The purpose of this study was to study the change in the content of the most active cytokines (interleukins 6 and 10 during the formation of the immune response in patients with latent early syphilis, as well as to study the possible relationship between the concentrations of these cytokines and the duration of the disease. In 50 patients with early latent syphilis, the concentration of interleukins 6 and 10 in serum was studied. The serum level of interleukins was studied by the enzyme immunoassay. A statistically significant increase in the concentration of interleukin 6 in the blood of patients with latent syphilis and decrease in the interleukin 10 concentration in comparison with healthy people was established. At the same time, in patients with latent syphilis with term of infection for more than 1 year, interleukin 10 has been expressed, as compared with healthy people and, especially, with patients with syphilis with a duration of infection of up to 1 year. Along with this, a lower degree of increase in the concentration of interleukin 6 in patients with latent syphilis with a duration of infection over 1 year has been established, as compared with patients with latent syphilis with a term of infection up to 1 year, against the background of its increased concentration as compared with a group of healthy individuals.

[sup 31]P-magnetic resonance spectroscopy: Impaired energy metabolism in latent hyperthyroidism. [sup 31]Phosphor-Kernspinspektroskopie: Gestoerter Energiestoffwechsel bei latenter Hyperthyreose

Energy Technology Data Exchange (ETDEWEB)

Theissen, P. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany)); Kaldewey, S. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany)); Moka, D. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany)); Bunke, J. (Philips Medizin Systeme, Hamburg (Germany)); Voth, E. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany)); Schicha, H. (Klinik und Poliklinik fuer Nuklearmedizin, Univ. Koeln (Germany))

1993-06-01

[sup 31]Phosphorous magnetic resonance spectroscopy allows an in vivo examination of energy metabolism. The present study was designed to evaluate whether in patients with latent hyperthyroidism alterations of muscle energy metabolism could be found similar to those observed in patients with overt hyperthyroidism. In 10 patients with overt hyperthyroidism before therapy and 20 with latent hyperthyroidism (also without therapy) and in 24 healthy volunteers magnetic resonance spectroscopy of the calf muscle was performed within a 1.5-Tesla magnet. Muscle concentrations of phosphocreatine, inorganic phosphate, and ATP were quantified compared to an external standard solution of K[sub 2]HPO[sub 4]. In the patients with overt hyperthyroidism and with latent hyperthyroidism a significant decrease of phosphocreatine was found. Further, the ATP concentration in patients with latent and manifest hyperthyroidism tended towards lower values. There were no significant differences in the decrease of phosphocreatine and ATP between both patient groups. Therefore, this study for the first time shows that alterations of energy metabolism in latent hyperthyroidism can be measured and that they are similar to those observed in overt hyperthyroidism. (orig.)

Closing the gap between behavior and models in route choice: The role of spatiotemporal constraints and latent traits in choice set formation

DEFF Research Database (Denmark)

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

not account for individual-related spatiotemporal constraints. This paper reduces the gap by proposing a route choice model incorporating spatiotemporal constraints and latent traits. The proposed approach combines stochastic route generation with a latent variable semi-compensatory model representing......A considerable gap exists between the behavioral paradigm of choice set formation in route choice and its representation in route choice modeling. While travelers form their viable choice set by retaining routes that satisfy spatiotemporal constraints, existing route generation techniques do...

Generalized Network Psychometrics : Combining Network and Latent Variable Models

NARCIS (Netherlands)

Epskamp, S.; Rhemtulla, M.; Borsboom, D.

2017-01-01

We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

Latent trait cortisol (LTC) during pregnancy: Composition, continuity, change, and concomitants.

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Giesbrecht, Gerald F; Bryce, Crystal I; Letourneau, Nicole; Granger, Douglas A

2015-12-01

Individual differences in the activity of the hypothalamic pituitary adrenal (HPA) axis are often operationalized using summary measures of cortisol that are taken to represent stable individual differences. Here we extend our understanding of a novel latent variable approach to latent trait cortisol (LTC) as a measure of trait-like HPA axis function during pregnancy. Pregnant women (n=380) prospectively collected 8 diurnal saliva samples (4 samples/day, 2 days) within each trimester. Saliva was assayed for cortisol. Confirmatory factor analyses were used to fit LTC models to early morning and daytime cortisol. For individual trimester data, only the daytime LTC models had adequate fit. These daytime LTC models were strongly correlated between trimesters and stable over pregnancy. Daytime LTC was unrelated to the cortisol awakening response and the daytime slope but strongly correlated with the area under the curve from ground. The findings support the validity of LTC as a measure of cortisol during pregnancy and suggest that it is not affected by pregnancy-related changes in HPA axis function. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of UV and X-Ray radiation for refreshing of old latent fingerprints in the cyanoacrylate fuming technique - preliminary study

International Nuclear Information System (INIS)

Radiceska, Pavlina; Ristova, Mimoza

2013-01-01

The work described below focuses on enhancement/refreshment of older latent fingerprints onto a non porous (glass) surface. The aging of the fingerprints is a major problem of the forensic science, because of the compound’s degradation under the influence of a variety of atmospheric parameters, in addition to the time factor. The humidification extent on the latent fingerprints appeared to be one of the critical factors for the deposition of the cyanoacrylate on the finger-marks, since the unsaturated bonds from lipid content from the latent fingerprints serve as active water condensation centers. In the present work we show results from the enhancement of aged latent fingerprint details by activation of the humidity condensation centers with exposition to UV or X-ray radiation prior to their developing into the cyanoacrylate fuming chamber. The aging of the latent fingerprints on glass surfaces with the time for given conditions was established. A term “critical day” was introduced as the day when the detectable details from the latent fingerprints dropped to one half of the initial number of details, recovered from identical fresh latent fingerprint. As the fingerprints were aged to the “critical day”, one third of the samples were exposed to a UV for 15 minutes, another third to 15 minutes of X-ray radiation and the last third was kept unexposed. All the samples were developed into a single cyanoacrylate fuming process. The results showed that in both UV and X-ray cases, a considerable enhancement/refreshment, in approximately 50% of the aged latent fingerprints, has been achieved with only a short term irradiation (15 minutes). (Author)

Do recognizable lifetime eating disorder phenotypes naturally occur in a culturally asian population? A combined latent profile and taxometric approach.

Science.gov (United States)

Thomas, Jennifer J; Eddy, Kamryn T; Ruscio, John; Ng, King Lam; Casale, Kristen E; Becker, Anne E; Lee, Sing

2015-05-01

We examined whether empirically derived eating disorder (ED) categories in Hong Kong Chinese patients (N = 454) would be consistent with recognizable lifetime ED phenotypes derived from latent structure models of European and American samples. We performed latent profile analysis (LPA) using indicator variables from data collected during routine assessment, and then applied taxometric analysis to determine whether latent classes were qualitatively versus quantitatively distinct. Latent profile analysis identified four classes: (i) binge/purge (47%); (ii) non-fat-phobic low-weight (34%); (iii) fat-phobic low-weight (12%); and (iv) overweight disordered eating (6%). Taxometric analysis identified qualitative (categorical) distinctions between the binge/purge and non-fat-phobic low-weight classes, and also between the fat-phobic and non-fat-phobic low-weight classes. Distinctions between the fat-phobic low-weight and binge/purge classes were indeterminate. Empirically derived categories in Hong Kong showed recognizable correspondence with recognizable lifetime ED phenotypes. Although taxometric findings support two distinct classes of low weight EDs, LPA findings also support heterogeneity among non-fat-phobic individuals. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

Visualization of pairwise and multilocus linkage disequilibrium structure using latent forests.

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Raphaël Mourad

Full Text Available Linkage disequilibrium study represents a major issue in statistical genetics as it plays a fundamental role in gene mapping and helps us to learn more about human history. The linkage disequilibrium complex structure makes its exploratory data analysis essential yet challenging. Visualization methods, such as the triangular heat map implemented in Haploview, provide simple and useful tools to help understand complex genetic patterns, but remain insufficient to fully describe them. Probabilistic graphical models have been widely recognized as a powerful formalism allowing a concise and accurate modeling of dependences between variables. In this paper, we propose a method for short-range, long-range and chromosome-wide linkage disequilibrium visualization using forests of hierarchical latent class models. Thanks to its hierarchical nature, our method is shown to provide a compact view of both pairwise and multilocus linkage disequilibrium spatial structures for the geneticist. Besides, a multilocus linkage disequilibrium measure has been designed to evaluate linkage disequilibrium in hierarchy clusters. To learn the proposed model, a new scalable algorithm is presented. It constrains the dependence scope, relying on physical positions, and is able to deal with more than one hundred thousand single nucleotide polymorphisms. The proposed algorithm is fast and does not require phase genotypic data.

A Probability Distribution over Latent Causes, in the Orbitofrontal Cortex.

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Chan, Stephanie C Y; Niv, Yael; Norman, Kenneth A

2016-07-27

The orbitofrontal cortex (OFC) has been implicated in both the representation of "state," in studies of reinforcement learning and decision making, and also in the representation of "schemas," in studies of episodic memory. Both of these cognitive constructs require a similar inference about the underlying situation or "latent cause" that generates our observations at any given time. The statistically optimal solution to this inference problem is to use Bayes' rule to compute a posterior probability distribution over latent causes. To test whether such a posterior probability distribution is represented in the OFC, we tasked human participants with inferring a probability distribution over four possible latent causes, based on their observations. Using fMRI pattern similarity analyses, we found that BOLD activity in the OFC is best explained as representing the (log-transformed) posterior distribution over latent causes. Furthermore, this pattern explained OFC activity better than other task-relevant alternatives, such as the most probable latent cause, the most recent observation, or the uncertainty over latent causes. Our world is governed by hidden (latent) causes that we cannot observe, but which generate the observations we see. A range of high-level cognitive processes require inference of a probability distribution (or "belief distribution") over the possible latent causes that might be generating our current observations. This is true for reinforcement learning and decision making (where the latent cause comprises the true "state" of the task), and for episodic memory (where memories are believed to be organized by the inferred situation or "schema"). Using fMRI, we show that this belief distribution over latent causes is encoded in patterns of brain activity in the orbitofrontal cortex, an area that has been separately implicated in the representations of both states and schemas. Copyright © 2016 the authors 0270-6474/16/367817-12$15.00/0.

Learning Latent Structure in Complex Networks

DEFF Research Database (Denmark)

Mørup, Morten; Hansen, Lars Kai

such as the Modularity, it has recently been shown that latent structure in complex networks is learnable by Bayesian generative link distribution models (Airoldi et al., 2008, Hofman and Wiggins, 2008). In this paper we propose a new generative model that allows representation of latent community structure......Latent structure in complex networks, e.g., in the form of community structure, can help understand network dynamics, identify heterogeneities in network properties, and predict ‘missing’ links. While most community detection algorithms are based on optimizing heuristic clustering objectives...... as in the previous Bayesian approaches and in addition allows learning of node specific link properties similar to that in the modularity objective. We employ a new relaxation method for efficient inference in these generative models that allows us to learn the behavior of very large networks. We compare the link...

Students' Views on Mathematics in Single-Sex and Coed Classrooms in Ghana

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Bofah, Emmanuel Adu-tutu; Hannula, Markku S.

2016-01-01

In this study, we investigated students' views on themselves as learners of mathematics as a function of school-by-sex (N = 2034, MAge = 18.49, SDAge = 1.25; 12th-grade; 58.2% girls). Using latent variable Structural Equation Modeling (SEM), the measurement and structural equivalence as well as the equality of latent means of scores across…

Morphometry of latent palmprints as a function of time.

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Barros, Rodrigo M; Faria, Bruna E F; Kuckelhaus, Selma A S

2013-12-01

In many crimes, the elapsed time between production and collecting fingermark traces is crucial. and a method able to detect the aging of latent prints would represent an improvement in forensic procedures. Considering that as the latent print gets older, substantial changes in the relative proportion of individual components secreted by skin glands could affect the morphology of ridges, morphometry could be a potential tool to assess the aging of latent fingermarks. Then, considering the very limited research in the field, the present work aims to evaluate the morphometry of latent palmprint ridges, as a function of time, in order to identify an aging pattern. The latent marks were deposited by 20 donors on glass microscope slides considering pressure and contact angle, and then were maintained under controlled environmental conditions. The morphometric study was conducted on marks developed with magnetic powder in 7 different time intervals after deposition (0, 5, 10, 15, 20, 25 or 30 days); 60 ridges were evaluated for each developed mark. The results showed that: 1) the method for the replacement and mixing of skin secretions on the palm was appropriate to ensure reproducibility of latent prints, and 2) considering the studied group, there was a time-dependent reduction in the width of ridges and on the percentage of visible ridges over 30 days. Results suggest the possibility of using the morphometric method to determine an aging profile of latent palmprints on glass surface, aiming for forensic purposes. © 2013.

Classification criteria of syndromes by latent variable models

DEFF Research Database (Denmark)

Petersen, Janne

2010-01-01

, although this is often desired. I have proposed a new method for predicting class membership that, in contrast to methods based on posterior probabilities of class membership, yields consistent estimates when regressed on explanatory variables in a subsequent analysis. There are four different basic models...... analyses. Part 1: HALS engages different phenotypic changes of peripheral lipoatrophy and central lipohypertrophy.  There are several different definitions of HALS and no consensus on the number of phenotypes. Many of the definitions consist of counting fulfilled criteria on markers and do not include...

Incorporating direct marketing activity into latent attrition models

NARCIS (Netherlands)

Schweidel, David A.; Knox, George

2013-01-01

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

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

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

2016-08-01

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

A Latent-Variable Causal Model of Faculty Reputational Ratings.

Science.gov (United States)

King, Suzanne; Wolfle, Lee M.

A reanalysis was conducted of Saunier's research (1985) on sources of variation in the National Research Council (NRC) reputational ratings of university faculty. Saunier conducted a stepwise regression analysis using 12 predictor variables. Due to problems with multicollinearity and because of the atheoretical nature of stepwise regression,…

Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

Science.gov (United States)

Kim, Eun Sook; Cao, Chunhua

2015-01-01

Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

Contribution of LFP dynamics to single-neuron spiking variability in motor cortex during movement execution

Science.gov (United States)

Rule, Michael E.; Vargas-Irwin, Carlos; Donoghue, John P.; Truccolo, Wilson

2015-01-01

Understanding the sources of variability in single-neuron spiking responses is an important open problem for the theory of neural coding. This variability is thought to result primarily from spontaneous collective dynamics in neuronal networks. Here, we investigate how well collective dynamics reflected in motor cortex local field potentials (LFPs) can account for spiking variability during motor behavior. Neural activity was recorded via microelectrode arrays implanted in ventral and dorsal premotor and primary motor cortices of non-human primates performing naturalistic 3-D reaching and grasping actions. Point process models were used to quantify how well LFP features accounted for spiking variability not explained by the measured 3-D reach and grasp kinematics. LFP features included the instantaneous magnitude, phase and analytic-signal components of narrow band-pass filtered (δ,θ,α,β) LFPs, and analytic signal and amplitude envelope features in higher-frequency bands. Multiband LFP features predicted single-neuron spiking (1ms resolution) with substantial accuracy as assessed via ROC analysis. Notably, however, models including both LFP and kinematics features displayed marginal improvement over kinematics-only models. Furthermore, the small predictive information added by LFP features to kinematic models was redundant to information available in fast-timescale (spiking history. Overall, information in multiband LFP features, although predictive of single-neuron spiking during movement execution, was redundant to information available in movement parameters and spiking history. Our findings suggest that, during movement execution, collective dynamics reflected in motor cortex LFPs primarily relate to sensorimotor processes directly controlling movement output, adding little explanatory power to variability not accounted by movement parameters. PMID:26157365

Latent fingerprints on different type of screen protective films

Directory of Open Access Journals (Sweden)

Yuttana Sudjaroen

2016-07-01

Full Text Available The purpose of this research was to study the quality of latent fingerprint on different types of screen protective films including screen protector, matte screen protector, anti-fingerprint clear screen protector and anti-fingerprint matte screen protector by using black powder method in developing latent fingerprints. The fingerprints were performed by 10 volunteers whose fingers (right index, right thumb, left index and left thumb were stubbing at different types of screen protective films and subsequently latent fingerprints were developed by brushing with black powder. Automated Fingerprint Identification System (AFIS counted the numbers of minutiae points from 320 latent fingerprints. Anti-fingerprint matte screen protective film produced the best quality of latent fingerprint with an average minutiae point 72.65, followed by matte screen protective film, clear screen protective film and anti-fingerprint clear screen protective film with an average minutiae point of 155.2, 135.0 and 72.65 respectively. The quality of latent fingerprints developed between a clear and a matte surface of screen protective films showed a significant difference (sig>0.05, whereas the coat and the non-coat with anti-fingerprint chemical revealed a non-significant difference (sig<0.05 in their number of minutiae points.

Ground Motion Uncertainty and Variability (single-station sigma): Insights from Euroseistest, Greece

Science.gov (United States)

Ktenidou, O. J.; Roumelioti, Z.; Abrahamson, N. A.; Cotton, F.; Pitilakis, K.

2014-12-01

Despite recent improvements in networks and data, the global aleatory uncertainty (sigma) in GMPEs is still large. One reason is the ergodic approach, where we combine data in space to make up for lack of data in time. By estimating the systematic site response, we can make site-specific GMPEs and use a lower, site-specific uncertainty: single-station sigma. In this study we use the EUROSEISTEST database (http://euroseisdb.civil.auth.gr), which has two distinct advantages: good existing knowledge of site conditions at all stations, and careful relocation of the recorded events. Constraining the site and source parameters as best we can, we minimise the within- and between-events components of the global, ergodic sigma. Following that, knowledge of the site response from empirical and theoretical approaches permits us to move on to single-station sigma. The variability per site is not clearly correlated to the site class. We show that in some cases knowledge of Vs30 is not sufficient, and that site-specific data are needed to capture the response, possibly due to 2D/3D effects from complex geometry. Our values of single-station sigma are low compared to the literature. This may be due to the good ray coverage we have in all directions for small, nearby records. Indeed, our single-station sigma values are similar to published single-path values, which means that they may correspond to a fully -rather than partially- non-ergodic approach. We find larger ground motion variability for short distances and small magnitudes. This may be related to the uncertainty in the depth affecting nearby records more, or to stress drop and causing trade-offs between the source and site terms for small magnitudes.

Measuring what latent fingerprint examiners consider sufficient information for individualization determinations.

Directory of Open Access Journals (Sweden)

Bradford T Ulery

Full Text Available Latent print examiners use their expertise to determine whether the information present in a comparison of two fingerprints (or palmprints is sufficient to conclude that the prints were from the same source (individualization. When fingerprint evidence is presented in court, it is the examiner's determination--not an objective metric--that is presented. This study was designed to ascertain the factors that explain examiners' determinations of sufficiency for individualization. Volunteer latent print examiners (n = 170 were each assigned 22 pairs of latent and exemplar prints for examination, and annotated features, correspondence of features, and clarity. The 320 image pairs were selected specifically to control clarity and quantity of features. The predominant factor differentiating annotations associated with individualization and inconclusive determinations is the count of corresponding minutiae; other factors such as clarity provided minimal additional discriminative value. Examiners' counts of corresponding minutiae were strongly associated with their own determinations; however, due to substantial variation of both annotations and determinations among examiners, one examiner's annotation and determination on a given comparison is a relatively weak predictor of whether another examiner would individualize. The extensive variability in annotations also means that we must treat any individual examiner's minutia counts as interpretations of the (unknowable information content of the prints: saying "the prints had N corresponding minutiae marked" is not the same as "the prints had N corresponding minutiae." More consistency in annotations, which could be achieved through standardization and training, should lead to process improvements and provide greater transparency in casework.

Induction of latent memory for conditioned food aversion and its transformation into "active" state depend on translation and transcription processes.

Science.gov (United States)

Solntseva, S V; Nikitin, V P

2014-05-01

Mechanisms of induction and retrieval of latent (hidden) memory for conditioned food aversion were investigated in snails. After initial training (single combination of a food stimulus with electric shock), aversive reactions to presentation of the conditioned food stimulus were not revealed. Repeated presentation of the stimuli in 12 days after the first combination was followed by the appearance of aversive food reactions that persisted for at least 14 days. Injections of inhibitors of protein (cycloheximide) or RNA (α-amanitin) synthesis immediately after the first or second combined presentation of the stimuli disturbed skill performance. We hypothesized that single combination of food and reinforcing stimuli led to translation- and transcription-dependent induction of latent conditioned food aversion memory. Transformation of this memory into an active state after repeated presentation of the stimulus combination also depends on the synthesis of new proteins and RNA.

A quantitative analysis on latent heat of an aqueous binary mixture.

Science.gov (United States)

Han, Bumsoo; Choi, Jeung Hwan; Dantzig, Jonathan A; Bischof, John C

2006-02-01

The latent heat during phase change of water-NaCl binary mixture was measured using a differential scanning calorimeter, and the magnitude for two distinct phase change events, water/ice and eutectic phase change, were analyzed considering the phase change characteristics of a binary mixture. During the analysis, the latent heat associated with each event was calculated by normalizing the amount of each endothermic peak with only the amount of sample participating in each event estimated from the lever rule for the phase diagram. The resulting latent heat of each phase change measured is 303.7 +/- 2.5 J/g for water/ice phase change, and 233.0 +/- 1.6 J/g for eutectic phase change, respectively regardless of the initial concentration of mixture. Although the latent heats of water/ice phase change in water-NaCl mixtures are closely correlated, further study is warranted to investigate the reason for smaller latent heat of water/ice phase change than that in pure water (335 J/g). The analysis using the lever rule was extended to estimate the latent heat of dihydrate as 115 J/g with the measured eutectic and water/ice latent heat values. This new analysis based on the lever rule will be useful to estimate the latent heat of water-NaCl mixtures at various concentrations, and may become a framework for more general analysis of latent heat of various biological solutions.

Prevalence and risk factors of latent Tuberculosis among ...

African Journals Online (AJOL)

Background: Latent Tuberculosis treatment is a key tuberculosis control intervention. Adolescents are a high risk group that is not routinely treated in low income countries. Knowledge of latent Tuberculosis (TB) burden among adolescents may influence policy. Objectives: We determined the prevalence and risk factors of ...

Assessing Trust and Effectiveness in Virtual Teams: Latent Growth Curve and Latent Change Score Models

Directory of Open Access Journals (Sweden)

Michael D. Coovert

2017-08-01

Full Text Available Trust plays a central role in the effectiveness of work groups and teams. This is the case for both face-to-face and virtual teams. Yet little is known about the development of trust in virtual teams. We examined cognitive and affective trust and their relationship to team effectiveness as reflected through satisfaction with one’s team and task performance. Latent growth curve analysis reveals both trust types start at a significant level with individual differences in that initial level. Cognitive trust follows a linear growth pattern while affective trust is overall non-linear, but becomes linear once established. Latent change score models are utilized to examine change in trust and also its relationship with satisfaction with the team and team performance. In examining only change in trust and its relationship to satisfaction there appears to be a straightforward influence of trust on satisfaction and satisfaction on trust. However, when incorporated into a bivariate coupling latent change model the dynamics of the relationship are revealed. A similar pattern holds for trust and task performance; however, in the bivariate coupling change model a more parsimonious representation is preferred.

Thermally activated, single component epoxy systems

KAUST Repository

Unruh, David A.; Pastine, Stefan J.; Moreton, Jessica C.; Frechet, Jean

2011-01-01

A single component epoxy system in which the resin and hardener components found in many two-component epoxies are combined onto the same molecule is described. The single molecule precursor to the epoxy resin contains both multiple epoxide moieties and a diamine held latent by thermally degradable carbamate linkages. These bis-carbamate "single molecule epoxies" have an essentially infinite shelf life and access a significant range in curing temperatures related to the structure of the carbamate linkages used. © 2011 American Chemical Society.

Thermally activated, single component epoxy systems

KAUST Repository

Unruh, David A.

2011-08-23

A single component epoxy system in which the resin and hardener components found in many two-component epoxies are combined onto the same molecule is described. The single molecule precursor to the epoxy resin contains both multiple epoxide moieties and a diamine held latent by thermally degradable carbamate linkages. These bis-carbamate "single molecule epoxies" have an essentially infinite shelf life and access a significant range in curing temperatures related to the structure of the carbamate linkages used. © 2011 American Chemical Society.

The Blind Men and the Elephant: Identification of a Latent Maltreatment Construct for Youth in Foster Care

Science.gov (United States)

Gabrielli, Joy; Jackson, Yo; Tunno, Angela M.; Hambrick, Erin P.

2017-01-01

Child maltreatment is a major public health concern due to its impact on developmental trajectories and consequences across mental and physical health outcomes. Operationalization of child maltreatment has been complicated, as research has used simple dichotomous counts to identification of latent class profiles. This study examines a latent measurement model assessed within foster youth inclusive of indicators of maltreatment chronicity and severity across four maltreatment types: physical, sexual, and psychological abuse, and neglect. Participants were 500 foster youth with a mean age of 12.99 years (SD = 2.95 years). Youth completed survey questions through a confidential audio computer-assisted self-interview program. A two-factor model with latent constructs of chronicity and severity of maltreatment revealed excellent fit across fit indices; however, the latent constructs were correlated .972. A one-factor model also demonstrated excellent model fit to the data (χ2 (16, n = 500) =28.087, p =.031, RMSEA (0.012 – 0.062) =.039, TLI =.990, CFI =.994, SRMR =.025) with a nonsignificant chi-square difference test comparing the one- and two-factor models. Invariance tests across age, gender, and placement type also were conducted with recommendations provided. Results suggest a single-factor latent model of maltreatment severity and chronicity can be attained. Thus, the maltreatment experiences reported by foster youth, though varied and complex, were captured in a model that may prove useful in later predictions of outcome behaviors. Appropriate identification of both the chronicity and severity of maltreatment inclusive of the range of maltreatment types remains a high priority for future research. PMID:28254690

Effects of categorization method, regression type, and variable distribution on the inflation of Type-I error rate when categorizing a confounding variable.

Science.gov (United States)

Barnwell-Ménard, Jean-Louis; Li, Qing; Cohen, Alan A

2015-03-15

The loss of signal associated with categorizing a continuous variable is well known, and previous studies have demonstrated that this can lead to an inflation of Type-I error when the categorized variable is a confounder in a regression analysis estimating the effect of an exposure on an outcome. However, it is not known how the Type-I error may vary under different circumstances, including logistic versus linear regression, different distributions of the confounder, and different categorization methods. Here, we analytically quantified the effect of categorization and then performed a series of 9600 Monte Carlo simulations to estimate the Type-I error inflation associated with categorization of a confounder under different regression scenarios. We show that Type-I error is unacceptably high (>10% in most scenarios and often 100%). The only exception was when the variable categorized was a continuous mixture proxy for a genuinely dichotomous latent variable, where both the continuous proxy and the categorized variable are error-ridden proxies for the dichotomous latent variable. As expected, error inflation was also higher with larger sample size, fewer categories, and stronger associations between the confounder and the exposure or outcome. We provide online tools that can help researchers estimate the potential error inflation and understand how serious a problem this is. Copyright © 2014 John Wiley & Sons, Ltd.

Latent semantic analysis.

Science.gov (United States)

Evangelopoulos, Nicholas E

2013-11-01

This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individual words are represented as vectors. LSA as a computational technique uses linear algebra to extract dimensions that represent that space. This representation enables the computation of similarity among terms and documents, categorization of terms and documents, and summarization of large collections of documents using automated procedures that mimic the way humans perform similar cognitive tasks. We present some technical details, various illustrative examples, and discuss a number of applications from linguistics, psychology, cognitive science, education, information science, and analysis of textual data in general. WIREs Cogn Sci 2013, 4:683-692. doi: 10.1002/wcs.1254 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. © 2013 John Wiley & Sons, Ltd.

Latent-failure risk estimates for computer control

Science.gov (United States)

Dunn, William R.; Folsom, Rolfe A.; Green, Owen R.

1991-01-01

It is shown that critical computer controls employing unmonitored safety circuits are unsafe. Analysis supporting this result leads to two additional, important conclusions: (1) annual maintenance checks of safety circuit function do not, as widely believed, eliminate latent failure risk; (2) safety risk remains even if multiple, series-connected protection circuits are employed. Finally, it is shown analytically that latent failure risk is eliminated when continuous monitoring is employed.

Exposing Latent Information in Folksonomies for Reasoning

Science.gov (United States)

2010-01-14

1.73 $.") http://www.w3.org/2006/07/SWD/ SKOS /reference/20081001/ Spiteri, L.F. (2007) "The structure and form of folksonomy tags: The road to the...Exposing Latent Information in Folksonomies for Reasoning January 14, 2010 Sponsored by Defense Advanced Research Projects Agency (DOD...DATES COVERED (From - To! 4/14/2009-12/23/2009 4. TITLE AND SUBTITLE Exposing Latent Information in Folksonomies for Reasoning Sa. CONTRACT

Polytomous latent scales for the investigation of the ordering of items

NARCIS (Netherlands)

Ligtvoet, R.; van der Ark, L.A.; Bergsma, W. P.; Sijtsma, K.

2011-01-01

We propose three latent scales within the framework of nonparametric item response theory for polytomously scored items. Latent scales are models that imply an invariant item ordering, meaning that the order of the items is the same for each measurement value on the latent scale. This ordering

Bayesian latent feature modeling for modeling bipartite networks with overlapping groups

DEFF Research Database (Denmark)

Jørgensen, Philip H.; Mørup, Morten; Schmidt, Mikkel Nørgaard

2016-01-01

Bi-partite networks are commonly modelled using latent class or latent feature models. Whereas the existing latent class models admit marginalization of parameters specifying the strength of interaction between groups, existing latent feature models do not admit analytical marginalization...... by the notion of community structure such that the edge density within groups is higher than between groups. Our model further assumes that entities can have different propensities of generating links in one of the modes. The proposed framework is contrasted on both synthetic and real bi-partite networks...... feature representations in bipartite networks provides a new framework for accounting for structure in bi-partite networks using binary latent feature representations providing interpretable representations that well characterize structure as quantified by link prediction....

Latent Growth and Dynamic Structural Equation Models.

Science.gov (United States)

Grimm, Kevin J; Ram, Nilam

2018-05-07

Latent growth models make up a class of methods to study within-person change-how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.

Illustration of Step-Wise Latent Class Modeling With Covariates and Taxometric Analysis in Research Probing Children's Mental Models in Learning Sciences

Directory of Open Access Journals (Sweden)

Dimitrios Stamovlasis

2018-04-01

Full Text Available This paper illustrates two psychometric methods, latent class analysis (LCA and taxometric analysis (TA using empirical data from research probing children's mental representation in science learning. LCA is used to obtain a typology based on observed variables and to further investigate how the encountered classes might be related to external variables, where the effectiveness of classification process and the unbiased estimations of parameters become the main concern. In the step-wise LCA, the class membership is assigned and subsequently its relationship with covariates is established. This leading-edge modeling approach suffers from severe downward-biased estimations. The illustration of LCA is focused on alternative bias correction approaches and demonstrates the effect of modal and proportional class-membership assignment along with BCH and ML correction procedures. The illustration of LCA is presented with three covariates, which are psychometric variables operationalizing formal reasoning, divergent thinking and field dependence-independence, respectively. Moreover, taxometric analysis, a method designed to detect the type of the latent structural model, categorical or dimensional, is introduced, along with the relevant basic concepts and tools. TA was applied complementarily in the same data sets to answer the fundamental hypothesis about children's naïve knowledge on the matters under study and it comprises an additional asset in building theory which is fundamental for educational practices. Taxometric analysis provided results that were ambiguous as far as the type of the latent structure. This finding initiates further discussion and sets a problematization within this framework rethinking fundamental assumptions and epistemological issues.

Illustration of Step-Wise Latent Class Modeling With Covariates and Taxometric Analysis in Research Probing Children's Mental Models in Learning Sciences.

Science.gov (United States)

Stamovlasis, Dimitrios; Papageorgiou, George; Tsitsipis, Georgios; Tsikalas, Themistoklis; Vaiopoulou, Julie

2018-01-01

This paper illustrates two psychometric methods, latent class analysis (LCA) and taxometric analysis (TA) using empirical data from research probing children's mental representation in science learning. LCA is used to obtain a typology based on observed variables and to further investigate how the encountered classes might be related to external variables, where the effectiveness of classification process and the unbiased estimations of parameters become the main concern. In the step-wise LCA, the class membership is assigned and subsequently its relationship with covariates is established. This leading-edge modeling approach suffers from severe downward-biased estimations. The illustration of LCA is focused on alternative bias correction approaches and demonstrates the effect of modal and proportional class-membership assignment along with BCH and ML correction procedures. The illustration of LCA is presented with three covariates, which are psychometric variables operationalizing formal reasoning, divergent thinking and field dependence-independence, respectively. Moreover, taxometric analysis, a method designed to detect the type of the latent structural model, categorical or dimensional, is introduced, along with the relevant basic concepts and tools. TA was applied complementarily in the same data sets to answer the fundamental hypothesis about children's naïve knowledge on the matters under study and it comprises an additional asset in building theory which is fundamental for educational practices. Taxometric analysis provided results that were ambiguous as far as the type of the latent structure. This finding initiates further discussion and sets a problematization within this framework rethinking fundamental assumptions and epistemological issues.

A single dose of dark chocolate increases parasympathetic modulation and heart rate variability in healthy subjects

Directory of Open Access Journals (Sweden)

Ana Amélia Machado DUARTE

Full Text Available ABSTRACT Objective: The aim of this study was to investigate the acute effect of a single dose of dark chocolate (70% cocoa on blood pressure and heart rate variability. Methods: Thirty-one healthy subjects (aged 18-25 years; both sexes were divided into two groups: 10 subjects in the white chocolate (7.4 g group and 21 in the dark chocolate (10 g group; measurements were performed at the university's physiology lab. An electrocardiogram measured the sympathovagal balance by spectral and symbolic analysis. Results: A single dose of dark chocolate significantly reduced systolic blood pressure and heart rate. After consuming 10 g of dark chocolate, significant increases were observed for heart rate variability, standard deviation of RR intervals standard deviation of all NN intervals, square root of the mean squared differences between adjacent normal RR intervals root mean square of successive differences, and an increase in the high frequency component in absolute values, representing the parasympathetic modulation. Conclusion: In conclusion the importance of our results lies in the magnitude of the response provoked by a single dose of cocoa. Just 10 g of cocoa triggered a significant increase in parasympathetic modulation and heart rate variability. These combined effects can potentially increase life expectancy because a reduction in heart rate variability is associated with several cardiovascular diseases and higher mortality.

Aspects of physicochemical methods for the detection of latent fingerprints

International Nuclear Information System (INIS)

Knowles, A.M.

1978-01-01

This paper reviews physicochemical methods of detecting latent finger-prints on a wide range of materials commonly found at the scene of a crime, with particular emphasis placed on the newer autoradiographic techniques. This is set against a description of studies on the fundamental nature of the latent fingerprint and its host substrate, with a brief review of the history of reagents used in latent fingerprint examination. (author)

Coupling of latent heat flux and the greenhouse effect by large-scale tropical/subtropical dynamics diagnosed in a set of observations and model simulations

Energy Technology Data Exchange (ETDEWEB)

Gershunov, A. [Climate Research Division, Scripps Institution of Oceanography, La Jolla, CA 92093-0224 (United States); Roca, R. [Laboratoire de Meteorologie Dynamique, Ecole Polytechnique, 91128 Palaiseau (France)

2004-03-01

Coupled variability of the greenhouse effect (GH) and latent heat flux (LHF) over the tropical - subtropical oceans is described, summarized and compared in observations and a coupled ocean-atmosphere general circulation model (CGCM). Coupled seasonal and interannual modes account for much of the total variability in both GH and LHF. In both observations and model, seasonal coupled variability is locally 180 out-of-phase throughout the tropics. Moisture is brought into convergent/convective regions from remote source areas located partly in the opposite, non-convective hemisphere. On interannual time scales, the tropical Pacific GH in the ENSO region of largest interannual variance is 180 out of phase with local LHF in observations but in phase in the model. A local source of moisture is thus present in the model on interannual time scales while in observations, moisture is mostly advected from remote source regions. The latent cooling and radiative heating of the surface as manifested in the interplay of LHF and GH is an important determinant of the current climate. Moreover, the hydrodynamic processes involved in the GH-LHF interplay determine in large part the climate response to external perturbations mainly through influencing the water vapor feedback but also through their intimate connection to the hydrological cycle. The diagnostic process proposed here can be performed on other CGCMs. Similarly, it should be repeated using a number of observational latent heat flux datasets to account for the variability in the different satellite retrievals. A realistic CGCM could be used to further study these coupled dynamics in natural and anthropogenically altered climate conditions. (orig.)

Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining.

Directory of Open Access Journals (Sweden)

Gabriele Prati

Full Text Available The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types. The present study focused on bicycle crashes that occurred in Italy during the period between 2011 and 2013. We analyzed categorical indicators corresponding to the characteristics of infrastructure (road type, road signage, and location type, road user (i.e., opponent vehicle and cyclist's maneuver, type of collision, age and gender of the cyclist, vehicle (type of opponent vehicle, and the environmental and time period variables (time of the day, day of the week, season, pavement condition, and weather. To identify homogenous subgroups of bicycle crashes, we used latent class analysis. Using latent class analysis, the bicycle crash data set was segmented into 19 classes, which represents 19 different bicycle crash types. Logistic regression analysis was used to identify the association between class membership and severity of the bicycle crashes. Finally, association rules were conducted for each of the latent classes to uncover the factors associated with an increased likelihood of severity. Association rules highlighted different crash characteristics associated with an increased likelihood of severity for each of the 19 bicycle crash types.

Latent M. tuberculosis infection--pathogenesis, diagnosis, treatment and prevention strategies.

Science.gov (United States)

Druszczyńska, Magdalena; Kowalewicz-Kulbat, Magdalena; Fol, Marek; Włodarczyk, Marcin; Rudnicka, Wiesława

2012-01-01

One third of the earths population is infected with Mycobacterium tuberculosis (Mtb), but only 5-10% of the infected individuals develop active tuberculosis (TB) over their lifetime. The remaining 90-95% stay healthy and are called latently infected individuals. They are the biggest reservoir of the tubercle bacilli and identifying the cases of latent TB is a part of the global plan of TB control. From the clinical point of view detection of latent TB infections (LTBI) in individuals with the highest active TB risk including cases of HIV infection, autoimmune inflammatory diseases or cancer, is a priority. This review summarizes the recent findings in the pathogenesis of latent TB, its diagnosis, treatment and prevention.

Modeling and impacts of the latent heat of phase change and specific heat for phase change materials

Science.gov (United States)

Scoggin, J.; Khan, R. S.; Silva, H.; Gokirmak, A.

2018-05-01

We model the latent heats of crystallization and fusion in phase change materials with a unified latent heat of phase change, ensuring energy conservation by coupling the heat of phase change with amorphous and crystalline specific heats. We demonstrate the model with 2-D finite element simulations of Ge2Sb2Te5 and find that the heat of phase change increases local temperature up to 180 K in 300 nm × 300 nm structures during crystallization, significantly impacting grain distributions. We also show in electrothermal simulations of 45 nm confined and 10 nm mushroom cells that the higher amorphous specific heat predicted by this model increases nucleation probability at the end of reset operations. These nuclei can decrease set time, leading to variability, as demonstrated for the mushroom cell.

The Depression Anxiety Stress Scales (DASS): normative data and latent structure in a large non-clinical sample.

Science.gov (United States)

Crawford, John R; Henry, Julie D

2003-06-01

To provide UK normative data for the Depression Anxiety and Stress Scale (DASS) and test its convergent, discriminant and construct validity. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,771) in terms of demographic variables. Competing models of the latent structure of the DASS were derived from theoretical and empirical sources and evaluated using confirmatory factor analysis. Correlational analysis was used to determine the influence of demographic variables on DASS scores. The convergent and discriminant validity of the measure was examined through correlating the measure with two other measures of depression and anxiety (the HADS and the sAD), and a measure of positive and negative affectivity (the PANAS). The best fitting model (CFI =.93) of the latent structure of the DASS consisted of three correlated factors corresponding to the depression, anxiety and stress scales with correlated error permitted between items comprising the DASS subscales. Demographic variables had only very modest influences on DASS scores. The reliability of the DASS was excellent, and the measure possessed adequate convergent and discriminant validity Conclusions: The DASS is a reliable and valid measure of the constructs it was intended to assess. The utility of this measure for UK clinicians is enhanced by the provision of large sample normative data.

Single cell Hi-C reveals cell-to-cell variability in chromosome structure

Science.gov (United States)

Schoenfelder, Stefan; Yaffe, Eitan; Dean, Wendy; Laue, Ernest D.; Tanay, Amos; Fraser, Peter

2013-01-01

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. PMID:24067610

Identifying subgroups of patients using latent class analysis

DEFF Research Database (Denmark)

Nielsen, Anne Mølgaard; Kent, Peter; Hestbæk, Lise

2017-01-01

BACKGROUND: Heterogeneity in patients with low back pain (LBP) is well recognised and different approaches to subgrouping have been proposed. Latent Class Analysis (LCA) is a statistical technique that is increasingly being used to identify subgroups based on patient characteristics. However......, as LBP is a complex multi-domain condition, the optimal approach when using LCA is unknown. Therefore, this paper describes the exploration of two approaches to LCA that may help improve the identification of clinically relevant and interpretable LBP subgroups. METHODS: From 928 LBP patients consulting...... of statistical performance measures, qualitative evaluation of clinical interpretability (face validity) and a subgroup membership comparison. RESULTS: For the single-stage LCA, a model solution with seven patient subgroups was preferred, and for the two-stage LCA, a nine patient subgroup model. Both approaches...

Environmental, morphological, and productive characterization of Sardinian goats and use of latent explanatory factors for population analysis.

Science.gov (United States)

Vacca, G M; Paschino, P; Dettori, M L; Bergamaschi, M; Cipolat-Gotet, C; Bittante, G; Pazzola, M

2016-09-01

Dairy goat farming is practiced worldwide, within a range of different farming systems. Here we investigated the effects of environmental factors and morphology on milk traits of the Sardinian goat population. Sardinian goats are currently reared in Sardinia (Italy) in a low-input context, similar to many goat farming systems, especially in developing countries. Milk and morphological traits from 1,050 Sardinian goats from 42 farms were recorded. We observed a high variability regarding morphological traits, such as coat color, ear length and direction, horn presence, and udder shape. Such variability derived partly from the unplanned repeated crossbreeding of the native Sardinian goats with exotic breeds, especially Maltese goats. The farms located in the mountains were characterized by the traditional farming system and the lowest percentage of crossbred goats. Explanatory factors analysis was used to summarize the interrelated measured milk variables. The explanatory factor related to fat, protein, and energy content of milk (the "Quality" latent variable) explained about 30% of the variance of the whole data set of measured milk traits followed by the "Hygiene" (19%), "Production" (19%), and "Acidity" (11%) factors. The "Quality" and "Hygiene" factors were not affected by any of the farm classification items, whereas "Production" and "Acidity" were affected only by altitude and size of herds, respectively, indicating the adaptation of the local goat population to different environmental conditions. The use of latent explanatory factor analysis allowed us to clearly explain the large variability of milk traits, revealing that the Sardinian goat population cannot be divided into subpopulations based on milk attitude The factors, properly integrated with genetic data, may be useful tools in future selection programs.

Using latent class analysis to estimate the test characteristics of the γ-interferon test, the single intradermal comparative tuberculin test and a multiplex immunoassay under Irish conditions

DEFF Research Database (Denmark)

Clegg, Tracy A.; Duignan, Anthony; Whelan, Clare

2011-01-01

Considerable effort has been devoted to improving the existing diagnostic tests for bovine tuberculosis (single intradermal comparative tuberculin test [SICTT] and ¿-interferon assay [¿-IFN]) and to develop new tests. Previously, the diagnostic characteristics (sensitivity, specificity) have been...... estimated in populations with defined infection status. However, these approaches can be problematic as there may be few herds in Ireland where freedom from infection is guaranteed. We used latent class models to estimate the diagnostic characteristics of existing (SICTT and ¿-IFN) and new (multiplex...... immunoassay [Enferplex-TB]) diagnostic tests under Irish field conditions where true disease status was unknown. The study population consisted of herds recruited in areas with no known TB problems (2197 animals) and herds experiencing a confirmed TB breakdown (2740 animals). A Bayesian model was developed...

Development of a scale to measure adherence to self-monitoring of blood glucose with latent variable measurement.

Science.gov (United States)

Wagner, J A; Schnoll, R A; Gipson, M T

1998-07-01

Adherence to self-monitoring of blood glucose (SMBG) is problematic for many people with diabetes. Self-reports of adherence have been found to be unreliable, and existing paper-and-pencil measures have limitations. This study developed a brief measure of SMBG adherence with good psychometric properties and a useful factor structure that can be used in research and in practice. A total of 216 adults with diabetes responded to 30 items rated on a 9-point Likert scale that asked about blood monitoring habits. In part I of the study, items were evaluated and retained based on their psychometric properties. The sample was divided into exploratory and confirmatory halves. Using the exploratory half, items with acceptable psychometric properties were subjected to a principal components analysis. In part II of the study, structural equation modeling was used to confirm the component solution with the entire sample. Structural modeling was also used to test the relationship between these components. It was hypothesized that the scale would produce four correlated factors. Principal components analysis suggested a two-component solution, and confirmatory factor analysis confirmed this solution. The first factor measures the degree to which patients rely on others to help them test and thus was named "social influence." The second component measures the degree to which patients use physical symptoms of blood glucose levels to help them test and thus was named "physical influence." Results of the structural model show that the components are correlated and make up the higher-order latent variable adherence. The resulting 15-item scale provides a short, reliable way to assess patient adherence to SMBG. Despite the existence of several aspects of adherence, this study indicates that the construct consists of only two components. This scale is an improvement on previous measures of adherence because of its good psychometric properties, its interpretable factor structure, and its

Religiousness and Levels of Hazardous Alcohol Use: A Latent Profile Analysis.

Science.gov (United States)

Jankowski, Peter J; Hardy, Sam A; Zamboanga, Byron L; Ham, Lindsay S; Schwartz, Seth J; Kim, Su Yeong; Forthun, Larry F; Bersamin, Melina M; Donovan, Roxanne A; Whitbourne, Susan Krauss; Hurley, Eric A; Cano, Miguel Ángel

2015-10-01

Prior person-centered research has consistently identified a subgroup of highly religious participants that uses significantly less alcohol when compared to the other subgroups. The construct of religious motivation is absent from existing examinations of the nuanced combinations of religiousness dimensions within persons, and alcohol expectancy valuations have yet to be included as outcome variables. Variable-centered approaches have found religious motivation and alcohol expectancy valuations to play a protective role against individuals' hazardous alcohol use. The current study examined latent religiousness profiles and hazardous alcohol use in a large, multisite sample of ethnically diverse college students. The sample consisted of 7412 college students aged 18-25 (M age = 19.77, SD age = 1.61; 75% female; 61% European American). Three latent profiles were derived from measures of religious involvement, salience, and religious motivations: Quest-Intrinsic Religiousness (highest levels of salience, involvement, and quest and intrinsic motivations; lowest level of extrinsic motivation), Moderate Religiousness (intermediate levels of salience, involvement, and motivations) and Extrinsic Religiousness (lowest levels of salience, involvement, and quest and intrinsic motivations; highest level of extrinsic motivation). The Quest-Intrinsic Religiousness profile scored significantly lower on hazardous alcohol use, positive expectancy outcomes, positive expectancy valuations, and negative expectancy valuations, and significantly higher on negative expectancy outcomes, compared to the other two profiles. The Extrinsic and Moderate Religiousness profiles did not differ significantly on positive expectancy outcomes, negative expectancy outcomes, negative expectancy valuations, or hazardous alcohol use. The results advance existing research by demonstrating that the protective influence of religiousness on college students' hazardous alcohol use may involve high levels on

Towards an HIV-1 cure: measuring the latent reservoir

Science.gov (United States)

Bruner, Katherine M.; Hosmane, Nina N.; Siliciano, Robert F.

2015-01-01

The latent reservoir of HIV-1 in resting memory CD4+ T cells serves as a major barrier to curing HIV-1 infection. While many PCR- and culture-based assays have been used to measure the size of the latent reservoir, correlation between results of different assays is poor and recent studies indicate that no available assay provides an accurate measurement of reservoir size. The discrepancies between assays are a hurdle to clinical trials that aim to measure the efficacy of HIV-1 eradication strategies. Here we describe the advantages and disadvantages of various approaches to measure the latent reservoir. PMID:25747663

Multilevel Latent Class Analysis for Large-Scale Educational Assessment Data: Exploring the Relation between the Curriculum and Students' Mathematical Strategies

Science.gov (United States)

Fagginger Auer, Marije F.; Hickendorff, Marian; Van Putten, Cornelis M.; Béguin, Anton A.; Heiser, Willem J.

2016-01-01

A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

Cardiac strain findings in children with latent rheumatic heart disease detected by echocardiographic screening.

Science.gov (United States)

Beaton, Andrea; Richards, Hedda; Ploutz, Michelle; Gaur, Lasya; Aliku, Twalib; Lwabi, Peter; Ensing, Greg; Sable, Craig

2017-08-01

Identification of patients with latent rheumatic heart disease by echocardiography presents a unique opportunity to prevent disease progression. Myocardial strain is a more sensitive indicator of cardiac performance than traditional measures of systolic function. The objective of this study was to test the hypothesis that abnormalities in myocardial strain may be present in children with latent rheumatic heart disease. Standard echocardiography images with electrocardiogram gating were obtained from Ugandan children found to have latent rheumatic heart disease as well as control subjects. Traditional echocardiography measures of systolic function were obtained, and offline global longitudinal strain analysis was performed. Comparison between groups was performed using strain as a continuous (Mann-Whitney U-test) and categorical (cut-off 5th percentile for age) variable. Our study included 14 subjects with definite rheumatic heart disease, 13 with borderline rheumatic heart disease, and 112 control subjects. None of the subjects had abnormal left ventricular size or ejection fraction. Global longitudinal strain was lower than the 5th percentile in 44% of the subjects with any rheumatic heart disease (p=0.002 versus controls) and 57% of the subjects with definite rheumatic heart disease (p=0.03). The mean absolute strain values were significantly lower when comparing subjects with any rheumatic heart disease with controls (20.4±3.95 versus 22.4±4.35, p=0.025) and subjects with definite rheumatic heart disease with controls (19.9±4.25 versus 22.4±4.35, p=0.033). Global longitudinal strain is decreased in subjects with rheumatic heart disease in the absence of abnormal systolic function. Larger studies with longer-term follow-up are required to determine whether there is a role for strain to help better understand the pathophysiology of latent rheumatic heart disease.

Ridge Width Correlations between Inked Prints and Powdered Latent Fingerprints.

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De Alcaraz-Fossoul, Josep; Barrot-Feixat, Carme; Zapico, Sara C; Mancenido, Michelle; Broatch, Jennifer; Roberts, Katherine A; Carreras-Marin, Clara; Tasker, Jack

2017-10-03

A methodology to estimate the time of latent fingerprint deposition would be of great value to law enforcement and courts. It has been observed that ridge topography changes as latent prints age, including the widths of ridges that could be measured as a function of time. Crime suspects are commonly identified using fingerprint databases that contain reference inked tenprints (flat and rolled impressions). These can be of interest in aging studies as they provide baseline information relating to the original (nonaged) ridges' widths. In practice, the age of latent fingerprints could be estimated following a comparison process between the evidentiary aged print and the corresponding reference inked print. The present article explores possible correlations between inked and fresh latent fingerprints deposited on different substrates and visualized with TiO 2 . The results indicate that the ridge width of flat inked prints is most similar to fresh latent fingerprints , and these should be used as the comparison standard for future aging studies. © 2017 American Academy of Forensic Sciences.

Study of noninvasive detection of latent fingerprints using UV laser

Science.gov (United States)

Li, Hong-xia; Cao, Jing; Niu, Jie-qing; Huang, Yun-gang; Mao, Lin-jie; Chen, Jing-rong

2011-06-01

Latent fingerprints present a considerable challenge in forensics, and noninvasive procedure that captures a digital image of the latent fingerprints is significant in the field of criminal investigation. The capability of photography technologies using 266nm UV Nd:YAG solid state laser as excitation light source to provide detailed images of unprocessed latent fingerprints is demonstrated. Unprocessed latent fingerprints were developed on various non-absorbent and absorbing substrates. According to the special absorption, reflection, scattering and fluorescence characterization of the various residues in fingerprints (fatty acid ester, protein, and carbosylic acid salts etc) to the UV light to weaken or eliminate the background disturbance and increase the brightness contrast of fingerprints with the background, and using 266nm UV laser as excitation light source, fresh and old latent fingerprints on the surface of four types of non-absorbent objects as magazine cover, glass, back of cellphone, wood desktop paintwork and two types of absorbing objects as manila envelope, notebook paper were noninvasive detected and appeared through reflection photography and fluorescence photography technologies, and the results meet the fingerprint identification requirements in forensic science.

Insights into the latent multinomial model through mark-resight data on female grizzly bears with cubs-of-the-year

Science.gov (United States)

Higgs, Megan D.; Link, William; White, Gary C.; Haroldson, Mark A.; Bjornlie, Daniel D.

2013-01-01

Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.

Ativação da proteína TGFbetaI latente em pulmão irradiado in vivo Latent TGFbeta1 activation in the lung irradiated in vivo

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MARCOS DUARTE MATTOS

2002-12-01

Full Text Available OBJETIVO: Investigar no pulmão, por imunohistoquímica, a localização das proteínas TGFbeta1 latente e TGFbeta1 ativa, se ocorre ativação radioinduzida da proteína TGFbeta1 latente e a distribuição das fibras colágenas em diversos períodos de tempo após irradiação. MÉTODOS: 32 camundongos isogênicos (C57BL foram divididos em dois grupos: GI (não irradiado com 12 animais e GII (irradiado com 20 animais. Os animais do GII receberam radiação gama (telecobaltoterapia, 60Co, com rendimento de 0,97Gy/min, dose única de 7Gy em corpo inteiro. Os camundongos dos grupos I e II foram sacrificados por estiramento cervical nos períodos de 1, 14, 30 e 90 dias após irradiação. RESULTADOS: Os pulmões irradiados apresentaram: 1 congestão vascular e espessamento dos septos alveolares aos 30 dias e mais intensamente aos 90 dias depois da irradiação; 2 aumento significante da deposição de colágeno em todos os períodos de tempo após irradiação; 3 fraca ativação da proteína TGFbeta1 latente em um dia e intensa aos 14 dias depois da irradiação em brônquios e alvéolos. Nossos resultados sugerem que células dos brônquios e alvéolos podem participar do complexo mecanismo de fibrose pulmonar radioinduzida atuando como fontes da proteína TGFbeta1 ativa.PURPOSE: assess the latent and active TGFb1 localization in the lung, whether or not radiation induces latent TGFbeta1 activation, and the distribution of collagen fibers in the irradiated lung. METHODS: Thirty two C57BL mice were randomly assigned in two groups: GI (non irradiated animals and GII (irradiated animals. The mice from GII received a single whole ¾ body radiation dose of 7Gy, using a 60Co source at a dose rate of 0.97 Gy/min. They were sacrificed by cervical dislocation at 1, 14, 30 and 90 days after radiation. RESULTS: The irradiated lungs showed: 1 vascular congestion and thickness of the alveolar septa 30 days and more intense 90 days after irradiation; 2

Latent tuberculosis in nursing professionals of a Brazilian hospital

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Valim Andréia

2011-05-01

Full Text Available Abstract Tuberculosis (TB is considered an occupational disease among health-care workers (HCWs. Direct contact with TB patients leads to an increased risk to become latently infected by Mycobacterium tuberculosis. The objective of this study is to estimate the prevalence of latent M. tuberculosis minfection among nursing professionals of a hospital in Rio Grande do Sul, Brazil, assessed by tuberculin skin test (TST. From November 2009 to May 2010, latent M. tuberculosis infection was assessed by TST in 55 nursing professionals. Epidemiological information was collected using a standardized questionnaire. A positive TST result (> or = 10 mm was observed in 47.3% of the HCWs tested. There was no significant difference in TST positivity when duration of employment or professional category (technician or nurse was evaluated. The results of this work reinforce the need for control measures to prevent latent M. tuberculosis infection among nursing professionals at the hospital where the study was conducted.

Men and women are from Earth: examining the latent structure of gender.

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Carothers, Bobbi J; Reis, Harry T

2013-02-01

Taxometric methods enable determination of whether the latent structure of a construct is dimensional or taxonic (nonarbitrary categories). Although sex as a biological category is taxonic, psychological gender differences have not been examined in this way. The taxometric methods of mean above minus below a cut, maximum eigenvalue, and latent mode were used to investigate whether gender is taxonic or dimensional. Behavioral measures of stereotyped hobbies and physiological characteristics (physical strength, anthropometric measurements) were examined for validation purposes, and were taxonic by sex. Psychological indicators included sexuality and mating (sexual attitudes and behaviors, mate selectivity, sociosexual orientation), interpersonal orientation (empathy, relational-interdependent self-construal), gender-related dispositions (masculinity, femininity, care orientation, unmitigated communion, fear of success, science inclination, Big Five personality), and intimacy (intimacy prototypes and stages, social provisions, intimacy with best friend). Constructs were with few exceptions dimensional, speaking to Spence's (1993) gender identity theory. Average differences between men and women are not under dispute, but the dimensionality of gender indicates that these differences are inappropriate for diagnosing gender-typical psychological variables on the basis of sex. (c) 2013 APA, all rights reserved.

Primiparous women's preferences for care during a prolonged latent phase of labour.

Science.gov (United States)

Ängeby, Karin; Wilde-Larsson, Bodil; Hildingsson, Ingegerd; Sandin-Bojö, Ann-Kristin

2015-10-01

To investigate primiparous women's preferences for care during a prolonged latent phase of labour. A qualitative study based on focus groups and individual interviews and analysed with inductive content analysis. Sixteen primiparous women with a prolonged latent phase of labour >18 hours were interviewed in five focus groups (n = 11) or individually (n = 5). One main category emerged "Beyond normality - a need of individual adapted guidance in order to understand and manage an extended latent phase of labour" which covers the women's preferences during the prolonged latent phase. Five categories were generated from the data: "A welcoming manner and not being rejected", "Individually adapted care", "Important information which prepares for reality and coping", "Participation and need for feedback" and "Staying nearby the labour ward or being admitted for midwifery support". Women with a prolonged latent phase of labour sought to use their own resources, but their needs for professional support increased as time passed. A welcoming attitude from an available midwife during the latent phase created a feeling of security, and personally adapted care was perceived positively. Women with a prolonged latent phase of labour preferred woman-centred care. Midwives play an important role in supporting these women. Women's need for midwifery-support increases as the time spent in latent phase increases. Copyright © 2015 Elsevier B.V. All rights reserved.

Tratamento da tuberculose de infecção latente: As recomendações actuais Latent tuberculosis infection treatment: Current recommendations

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R Duarte

2010-09-01

Full Text Available O diagnóstico e tratamento da infecção latente por Mycobacterium tuberculosis reduz significativamente o risco de desenvolvimento de tuberculose activa e a transmissão da doença na comunidade. O rastreio da tuberculose infecção latente deve passar pela exclusão de doença activa (inquérito de sintomas e radiografia pulmonar e avaliação da resposta imunológica ao M. tuberculosis através dos testes actualmente ao dispor, como o teste tuberculínico e os testes IGRA (interferon-gamma release assay. A escolha do esquema de tratamento deve ter em linha de conta a eficácia, a adesão e os efeitos colaterais associados ao mesmo Este documento actualiza as recomendações sobre tratamento da tuberculose infecção latente. São apresentadas indicações sobre quem deve ser rastreado e revistos os esquemas de tratamento.Diagnosis and treatment of latent infection with Mycobacterium tuberculosis (LTBI, significantly reduces the risk of developing active tuberculosis and the transmission of the disease in the community. LTBI screening must pass by the exclusion of active disease (symptoms enquiry and chest radiography and assessment of immune response to Mycobacterium tuberculosis testing with the tests currently available - tuberculin skin test and interferon-gamma release assay (IGRA. The choice of treatment must take into account the efficacy and side effects associated with the same. This document provides updated recommendations on latent tuberculosis infection treatment. Topics covered include whom to test for TB and reviewed LTBI treatment regimens.

Calculating latent frequencies of systems with local damping

International Nuclear Information System (INIS)

Kolonits, Ferenc

2005-01-01

Modal analysis of damped systems often cannot proceed with common real-eigenvalue techniques. The system of equilibrium equations leads to a matrix with elements being quadratic functions of a parameter λ. The values of that which make the matrix singular are the latent roots, while the solutions of the associated homogenous equation are the latent vectors. They are the (generally complex) characteristic frequencies and the mode shapes of the system, respectively. Although the theory is well developed, the numerical application is open to refinements yet. A reduction to better-known real-domain subtasks deserves attention. With a theorem of Popper and Gaspar, a n x n λ-matrix problem can be cut in two: into n-size asymmetric real matrices having as eigenvalues the n lower and n upper latent roots, ranked by absolute value. This approach may be of use for systems with high number of degrees of freedom while damped by a relatively few concentrated devices. It might fit also an earthquake analysis, where the lower portion of eigenvalues is customarily what counts. The dampers appear in the splitting algorithm as restricted-size modifications, ready for use by the Sherman-Morrison-Woodbury identity. The task is re-traced this way to a more usual real-asymmetric eigenproblem. A requirement of convergence is that the lower and upper n-set of latent values must be distinct. With odd-number degrees of freedom and neither over-damped, i.e. all latent roots being complex, this condition is surely violated. For such cases, a supplemental algorithm is proposed

Behaviorism, latent learning, and cognitive maps: needed revisions in introductory psychology textbooks.

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Jensen, Robert

2006-01-01

This paper critically assesses the scholarship in introductory psychology textbooks in relation to the topic of latent learning. A review of the treatment of latent learning in 48 introductory psychology textbooks published between 1948 and 2004, with 21 of these texts published since 1999, reveals that the scholarship on the topic of latent learning demonstrated in introductory textbooks warrants improvement. Errors that persist in textbooks include the assertion that the latent learning experiments demonstrate unequivocally that reinforcement was not necessary for learning to occur, that behavioral theories could not account for the results of the latent learning experiments, that B. F. Skinner was an S-R association behaviorist who argued that reinforcement is necessary for learning to occur, and that because behavioral theories (including that of B. F. Skinner) were unable explain the results of the latent learning experiments the cognitive map invoked by Edward Tolman is the only explanation for latent learning. Finally, the validity of the cognitive map is typically accepted without question. Implications of the presence of these errors for students and the discipline are considered. Lastly, remedies are offered to improve the scholarship found in introductory psychology textbooks.

Sociodemographic predictors of latent class membership of problematic and disordered gamblers

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Richard J.E. James

2016-06-01

Full Text Available This paper reports a series of analyses examining the predictors of gambling subtypes identified from a latent class analysis of problem gambling assessment data, pooled from four health and gambling surveys conducted in Britain between 2007 and 2012. Previous analyses have indicated that gambling assessments have a consistent three class structure showing quantitative and potentially qualitative differences. Bringing this data together is useful for studying more severe problem gamblers, where the small number of respondents has been a chronic limitation of gambling prevalence research. Predictors were drawn from sociodemographic indicators and engagement with other legal addictive behaviours, namely smoking and alcohol consumption. The pooled data was entered into a multinomial logistic regression model in which class membership was regressed along a series of demographic variables and survey year, based on previous analyses of gambling prevalence data. The results identified multiple demographic differences (age, general health, SES, being single, membership of ethnic minority groups between the non-problem and two classes endorsing some problem gambling indicators. Although these two groups tended to share a sociodemographic profile, the odds of being male, British Asian and a smoker increased between the three groups in line with problem gambling severity. Being widowed was also found to be associated with the most severe gambling class. A number of associations were also observed with other addictive behaviours. However these should be taken as indicative as these were limited subsamples of a single dataset. These findings identify specific groups in which gambling problems are more prevalent, and highlight the importance of the interaction between acute and determinant aspects of impulsivity, suggesting that a more complex account of impulsivity should be considered than is currently present in the gambling literature.

[Hypothesis on the equilibrium point and variability of amplitude, speed and time of single-joint movement].

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Latash, M; Gottleib, G

1990-01-01

Problems of single-joint movement variability are analysed in the framework of the equilibrium-point hypothesis (the lambda-model). Control of the movements is described with three parameters related to movement amplitude speed, and time. Three strategies emerge from this description. Only one of them is likely to lead to a Fitts' type speed-accuracy trade-off. Experiments were performed to test one of the predictions of the model. Subjects performed identical sets of single-joint fast movements with open or closed eyes and some-what different instructions. Movements performed with closed eyes were characterized with higher peak speeds and unchanged variability in seeming violation of the Fitt's law and in a good correspondence to the model.

Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification

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Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.

2010-01-01

Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f = A???x of a latent multinomial variable x with cell probability vector ?? = ??(??). Given that full conditional distributions [?? | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, ??], which is made possible by knowledge of the null space of A???. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks. ?? 2009, The International Biometric Society.

A competitive enzyme immunoassay for the quantitative detection of cocaine from banknotes and latent fingermarks.

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van der Heide, Susan; Garcia Calavia, Paula; Hardwick, Sheila; Hudson, Simon; Wolff, Kim; Russell, David A

2015-05-01

A sensitive and versatile competitive enzyme immunoassay (cEIA) has been developed for the quantitative detection of cocaine in complex forensic samples. Polyclonal anti-cocaine antibody was purified from serum and deposited onto microtiter plates. The concentration of the cocaine antibody adsorbed onto the plates, and the dilution of the cocaine-HRP hapten were both studied to achieve an optimised immunoassay. The method was successfully used to quantify cocaine in extracts taken from both paper currency and latent fingermarks. The limit of detection (LOD) of 0.162ngmL(-1) achieved with the assay compares favourably to that of conventional chromatography-mass spectroscopy techniques, with an appropriate sensitivity for the quantification of cocaine at the low concentrations present in some forensic samples. The cEIA was directly compared to LC-MS for the analysis of ten UK banknote samples. The results obtained from both techniques were statistically similar, suggesting that the immunoassay was unaffected by cross-reactivity with potentially interfering compounds. The cEIA was used also for the detection of cocaine in extracts from latent fingermarks. The results obtained were compared to the cocaine concentrations detected in oral fluid sampled from the same individual. Using the cEIA, we have shown, for the first time, that endogeneously excreted cocaine can be detected and quantified from a single latent fingermark. Additionally, it has been shown that the presence of cocaine, at similar concentrations, in more than one latent fingermark from the same individual can be linked with those concentrations found in oral fluid. These results show that detection of drugs in latent fingermarks could directly indicate whether an individual has consumed the drug. The specificity and feasibility of measuring low concentrations of cocaine in complex forensic samples demonstrate the effectiveness and robustness of the assay. The immunoassay presents a simple and cost

Current management options for latent tuberculosis: a review

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Norton BL

2012-11-01

Full Text Available Brianna L Norton, David P HollandDepartment of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USAAbstract: Tuberculosis remains the world’s second leading infectious cause of death, with nearly one-third of the global population latently infected. Treatment of latent tuberculosis infection is a mainstay of tuberculosis-control efforts in low-to medium-incidence countries. Isoniazid monotherapy has been the standard of care for decades, but its utility is impaired by poor completion rates. However, new, shorter-course regimens using rifamycins improve completion rates and are cost-saving compared with standard isoniazid monotherapy. We review the currently available therapies for latent tuberculosis infection and their toxicities and include a brief economic comparison of the different regimens.Keywords: isoniazid, rifampin, rifapentine, tuberculin skin test, interferon-gamma release assay

Harry Potter and the sorcerer's scope: latent scope biases in explanatory reasoning.

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Khemlani, Sangeet S; Sussman, Abigail B; Oppenheimer, Daniel M

2011-04-01

What makes a good explanation? We examine the function of latent scope, i.e., the number of unobserved phenomena that an explanation can account for. We show that individuals prefer narrow latent scope explanations-those that account for fewer unobserved effects-to broader explanations. In Experiments 1a-d, participants found narrow latent scope explanations to be both more satisfying and more likely. In Experiment 2 we directly manipulated base rate information and again found a preference for narrow latent scope explanations. Participants in Experiment 3 evaluated more natural explanations of unexpected observations, and again displayed a bias for narrow latent scope explanations. We conclude by considering what this novel bias tells us about how humans evaluate explanations and engage in causal reasoning.

Latent Cognitive Phenotypes in De Novo Parkinson's Disease: A Person-Centered Approach.

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LaBelle, Denise R; Walsh, Ryan R; Banks, Sarah J

2017-08-01

Cognitive impairment is an important aspect of Parkinson's disease (PD), but there is considerable heterogeneity in its presentation. This investigation aims to identify and characterize latent cognitive phenotypes in early PD. Latent class analysis, a data-driven, person-centered, cluster analysis was performed on cognitive data from the Parkinson's Progressive Markers Initiative baseline visit. This analytic method facilitates identification of naturally occurring endophenotypes. Resulting classes were compared across biomarker, symptom, and demographic data. Six cognitive phenotypes were identified. Three demonstrated consistent performance across indicators, representing poor ("Weak-Overall"), average ("Typical-Overall"), and strong ("Strong-Overall") cognition. The remaining classes demonstrated unique patterns of cognition, characterized by "Strong-Memory," "Weak-Visuospatial," and "Amnestic" profiles. The Amnestic class evidenced greater tremor severity and anosmia, but was unassociated with biomarkers linked with Alzheimer's disease. The Weak-Overall class was older and reported more non-motor features associated with cognitive decline, including anxiety, depression, autonomic dysfunction, anosmia, and REM sleep behaviors. The Strong-Overall class was younger, more female, and reported less dysautonomia and anosmia. Classes were unrelated to disease duration, functional independence, or available biomarkers. Latent cognitive phenotypes with focal patterns of impairment were observed in recently diagnosed individuals with PD. Cognitive profiles were found to be independent of traditional biomarkers and motoric indices of disease progression. Only globally impaired class was associated with previously reported indicators of cognitive decline, suggesting this group may drive the effects reported in studies using variable-based analysis. Longitudinal and neuroanatomical characterization of classes will yield further insight into the evolution of cognitive

Tuberculosis and latent tuberculosis infection among healthcare workers in Kisumu, Kenya.

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Agaya, Janet; Nnadi, Chimeremma D; Odhiambo, Joseph; Obonyo, Charles; Obiero, Vincent; Lipke, Virginia; Okeyo, Elisha; Cain, Kevin; Oeltmann, John E

2015-12-01

To assess prevalence and occupational risk factors of latent TB infection and history of TB disease ascribed to work in a healthcare setting in western Kenya. We conducted a cross-sectional survey among healthcare workers in western Kenya in 2013. They were recruited from dispensaries, health centres and hospitals that offer both TB and HIV services. School workers from the health facilities' catchment communities were randomly selected to serve as the community comparison group. Latent TB infection was diagnosed by tuberculin skin testing. HIV status of participants was assessed. Using a logistic regression model, we determined the adjusted odds of latent TB infection among healthcare workers compared to school workers; and among healthcare workers only, we assessed work-related risk factors for latent TB infection. We enrolled 1005 healthcare workers and 411 school workers. Approximately 60% of both groups were female. A total of 22% of 958 healthcare workers and 12% of 392 school workers tested HIV positive. Prevalence of self-reported history of TB disease was 7.4% among healthcare workers and 3.6% among school workers. Prevalence of latent TB infection was 60% among healthcare workers and 48% among school workers. Adjusted odds of latent TB infection were 1.5 times higher among healthcare workers than school workers (95% confidence interval 1.2-2.0). Healthcare workers at all three facility types had similar prevalence of latent TB infection (P = 0.72), but increasing years of employment was associated with increased odds of LTBI (P Kenya which offer TB and HIV services are at increased risk of latent TB infection, and the risk is similar across facility types. Implementation of WHO-recommended TB infection control measures are urgently needed in health facilities to protect healthcare workers. © 2015 John Wiley & Sons Ltd.

A Multinomial Probit Model with Latent Factors

DEFF Research Database (Denmark)

Piatek, Rémi; Gensowski, Miriam

2017-01-01

be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler......We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can...

Child involvement, alliance, and therapist flexibility: process variables in cognitive-behavioural therapy for anxiety disorders in childhood.

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Hudson, Jennifer L; Kendall, Philip C; Chu, Brian C; Gosch, Elizabeth; Martin, Erin; Taylor, Alan; Knight, Ashleigh

2014-01-01

This study examined the relations between treatment process variables and child anxiety outcomes. Independent raters watched/listened to taped therapy sessions of 151 anxiety-disordered (6-14 yr-old; M = 10.71) children (43% boys) and assessed process variables (child alliance, therapist alliance, child involvement, therapist flexibility and therapist functionality) within a manual-based cognitive-behavioural treatment. Latent growth modelling examined three latent variables (intercept, slope, and quadratic) for each process variable. Child age, gender, family income and ethnicity were examined as potential antecedents. Outcome was analyzed using factorially derived clinician, mother, father, child and teacher scores from questionnaire and structured diagnostic interviews at pretreatment, posttreatment and 12-month follow-up. Latent growth models demonstrated a concave quadratic curve for child involvement and therapist flexibility over time. A predominantly linear, downward slope was observed for alliance, and functional flexibility remained consistent over time. Increased alliance, child involvement and therapist flexibility showed some albeit inconsistent, associations with positive treatment outcome. Findings support the notion that maintaining the initial high level of alliance or involvement is important for clinical improvement. There is some support that progressively increasing alliance/involvement also positively impacts on treatment outcome. These findings were not consistent across outcome measurement points or reporters. Copyright © 2013 Elsevier Ltd. All rights reserved.

DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity

Science.gov (United States)

Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2013-12-01

Objective. Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than 3, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach. To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results. To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance. DataHigh was developed to fulfil a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity.

DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity.

Science.gov (United States)

Cowley, Benjamin R; Kaufman, Matthew T; Butler, Zachary S; Churchland, Mark M; Ryu, Stephen I; Shenoy, Krishna V; Yu, Byron M

2013-12-01

Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than 3, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. DataHigh was developed to fulfil a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity.

DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

Science.gov (United States)

Cowley, Benjamin R.; Kaufman, Matthew T.; Butler, Zachary S.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2014-01-01

Objective Analyzing and interpreting the activity of a heterogeneous population of neurons can be challenging, especially as the number of neurons, experimental trials, and experimental conditions increases. One approach is to extract a set of latent variables that succinctly captures the prominent co-fluctuation patterns across the neural population. A key problem is that the number of latent variables needed to adequately describe the population activity is often greater than three, thereby preventing direct visualization of the latent space. By visualizing a small number of 2-d projections of the latent space or each latent variable individually, it is easy to miss salient features of the population activity. Approach To address this limitation, we developed a Matlab graphical user interface (called DataHigh) that allows the user to quickly and smoothly navigate through a continuum of different 2-d projections of the latent space. We also implemented a suite of additional visualization tools (including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses) and an optional tool for performing dimensionality reduction. Main results To demonstrate the utility and versatility of DataHigh, we used it to analyze single-trial spike count and single-trial timecourse population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded using single electrodes. Significance DataHigh was developed to fulfill a need for visualization in exploratory neural data analysis, which can provide intuition that is critical for building scientific hypotheses and models of population activity. PMID:24216250

Competing risk model for reduction in life expectancy from radiogenic latent cancer

International Nuclear Information System (INIS)

Davis, H.T.

1978-01-01

Because of the large number of persons who could potentially receive low doses of radiation as a result of a nuclear reactor accident, the number of fatalities from latent cancers is generally larger than the early, or prompt, fatalities. For this reason the latent cancer fatality risk of reactor accidents is perceived as being more important than the early fatality risk. In addition, there exists the temptation to add the latent cancer fatality risk to the early fatality risk for the purpose of comparing reactor accident risks to other risks that society is exposed to, such as automobile accidents, airplane accidents, hurricanes, etc. However, the impact on the individual, and society as a whole, due to latent cancer fatalities is significantly different from the impact produced by early fatalities. Early fatalities generally result in appreciable life shortening for the affected individual while latent cancer fatalities generally result in very limited life shortening. A mathematical model was developed to express the reduction in life expectancy due to latent radiogenic cancer as a function of dose received

Measure Guideline: Replacing Single-Speed Pool Pumps with Variable Speed Pumps for Energy Savings

Energy Technology Data Exchange (ETDEWEB)

Hunt, A.; Easley, S.

2012-05-01

The report evaluates potential energy savings by replacing traditional single-speed pool pumps with variable speed pool pumps, and provide a basic cost comparison between continued uses of traditional pumps verses new pumps. A simple step-by-step process for inspecting the pool area and installing a new pool pump follows.

The selection of a mode of urban transportation: Integrating psychological variables to discrete choice models

International Nuclear Information System (INIS)

Cordoba Maquilon, Jorge E; Gonzalez Calderon, Carlos A; Posada Henao, John J

2011-01-01

A study using revealed preference surveys and psychological tests was conducted. Key psychological variables of behavior involved in the choice of transportation mode in a population sample of the Metropolitan Area of the Valle de Aburra were detected. The experiment used the random utility theory for discrete choice models and reasoned action in order to assess beliefs. This was used as a tool for analysis of the psychological variables using the sixteen personality factor questionnaire (16PF test). In addition to the revealed preference surveys, two other surveys were carried out: one with socio-economic characteristics and the other with latent indicators. This methodology allows for an integration of discrete choice models and latent variables. The integration makes the model operational and quantifies the unobservable psychological variables. The most relevant result obtained was that anxiety affects the choice of urban transportation mode and shows that physiological alterations, as well as problems in perception and beliefs, can affect the decision-making process.

Skin Resistivity Value of Upper Trapezius Latent Trigger Points

Directory of Open Access Journals (Sweden)

Elżbieta Skorupska

2015-01-01

Full Text Available Introduction. The skin resistivity (SkR measurement is commonly recommended for acupoints measurement, but for trigger points (TrPs only one study is available. The purpose of the study was to evaluate SkR for latent TrPs compared to non-TrPs and the surrounding tissue. Material and Methods. Forty-two healthy volunteers with unilateral latent upper trapezius TrPs (12 men, 30 women aged 21–23 (mean age: 22.1 ± 0.6 y participated in the study. Keithley electrometer 610B was used for measuring SkR (Ag/AgCl self-adhesive, disposable ground electrode: 30 mm diameter. SkR was measured for latent TrPs and compared to opposite non-TrPs sites and the surrounding tissue. Results. The SkR decrease of TrPs-positive sites as compared to TrPs-negative sites and the surrounding tissue was confirmed. However, no statistically significant difference in the SkR value occurred when all data were analyzed. The same was confirmed after gender division and for TrPs-positive subjects examined for referred pain and twitch response presence. Conclusion. SkR reactive changes at latent TrPs are possible but the results were not consistent with the previous study. Thus, caution in applying SkR to latent TrPs isolation is recommended and its clinical use should not be encouraged yet. Further studies, especially on active TrPs, are yet required.

Natural Language Search Interfaces: Health Data Needs Single-Field Variable Search.

Science.gov (United States)

Jay, Caroline; Harper, Simon; Dunlop, Ian; Smith, Sam; Sufi, Shoaib; Goble, Carole; Buchan, Iain

2016-01-14

Data discovery, particularly the discovery of key variables and their inter-relationships, is key to secondary data analysis, and in-turn, the evolving field of data science. Interface designers have presumed that their users are domain experts, and so they have provided complex interfaces to support these "experts." Such interfaces hark back to a time when searches needed to be accurate first time as there was a high computational cost associated with each search. Our work is part of a governmental research initiative between the medical and social research funding bodies to improve the use of social data in medical research. The cross-disciplinary nature of data science can make no assumptions regarding the domain expertise of a particular scientist, whose interests may intersect multiple domains. Here we consider the common requirement for scientists to seek archived data for secondary analysis. This has more in common with search needs of the "Google generation" than with their single-domain, single-tool forebears. Our study compares a Google-like interface with traditional ways of searching for noncomplex health data in a data archive. Two user interfaces are evaluated for the same set of tasks in extracting data from surveys stored in the UK Data Archive (UKDA). One interface, Web search, is "Google-like," enabling users to browse, search for, and view metadata about study variables, whereas the other, traditional search, has standard multioption user interface. Using a comprehensive set of tasks with 20 volunteers, we found that the Web search interface met data discovery needs and expectations better than the traditional search. A task × interface repeated measures analysis showed a main effect indicating that answers found through the Web search interface were more likely to be correct (F1,19=37.3, Pnatural language search interfaces for variable search supporting in particular: query reformulation; data browsing; faceted search; surrogates; relevance

Measure Guideline. Replacing Single-Speed Pool Pumps with Variable Speed Pumps for Energy Savings

Energy Technology Data Exchange (ETDEWEB)

Hunt, A. [Building Media and the Building America Retrofit Alliance (BARA), Wilmington, DE (United States); Easley, S. [Building Media and the Building America Retrofit Alliance (BARA), Wilmington, DE (United States)

2012-05-01

This measure guideline evaluates potential energy savings by replacing traditional single-speed pool pumps with variable speed pool pumps, and provides a basic cost comparison between continued uses of traditional pumps verses new pumps. A simple step-by-step process for inspecting the pool area and installing a new pool pump follows.

31P-magnetic resonance spectroscopy: Impaired energy metabolism in latent hyperthyroidism

International Nuclear Information System (INIS)

Theissen, P.; Kaldewey, S.; Moka, D.; Bunke, J.; Voth, E.; Schicha, H.

1993-01-01

31 Phosphorous magnetic resonance spectroscopy allows an in vivo examination of energy metabolism. The present study was designed to evaluate whether in patients with latent hyperthyroidism alterations of muscle energy metabolism could be found similar to those observed in patients with overt hyperthyroidism. In 10 patients with overt hyperthyroidism before therapy and 20 with latent hyperthyroidism (also without therapy) and in 24 healthy volunteers magnetic resonance spectroscopy of the calf muscle was performed within a 1.5-Tesla magnet. Muscle concentrations of phosphocreatine, inorganic phosphate, and ATP were quantified compared to an external standard solution of K 2 HPO 4 . In the patients with overt hyperthyroidism and with latent hyperthyroidism a significant decrease of phosphocreatine was found. Further, the ATP concentration in patients with latent and manifest hyperthyroidism tended towards lower values. There were no significant differences in the decrease of phosphocreatine and ATP between both patient groups. Therefore, this study for the first time shows that alterations of energy metabolism in latent hyperthyroidism can be measured and that they are similar to those observed in overt hyperthyroidism. (orig.) [de

Generalized correlation of latent heats of vaporization of coal liquid model compounds between their freezing points and critical points

Energy Technology Data Exchange (ETDEWEB)

Sivaraman, A.; Kobuyashi, R.; Mayee, J.W.

1984-02-01

Based on Pitzer's three-parameter corresponding states principle, the authors have developed a correlation of the latent heat of vaporization of aromatic coal liquid model compounds for a temperature range from the freezing point to the critical point. An expansion of the form L = L/sub 0/ + ..omega..L /sub 1/ is used for the dimensionless latent heat of vaporization. This model utilizes a nonanalytic functional form based on results derived from renormalization group theory of fluids in the vicinity of the critical point. A simple expression for the latent heat of vaporization L = D/sub 1/epsilon /SUP 0.3333/ + D/sub 2/epsilon /SUP 0.8333/ + D/sub 4/epsilon /SUP 1.2083/ + E/sub 1/epsilon + E/sub 2/epsilon/sup 2/ + E/sub 3/epsilon/sup 3/ is cast in a corresponding states principle correlation for coal liquid compounds. Benzene, the basic constituent of the functional groups of the multi-ring coal liquid compounds, is used as the reference compound in the present correlation. This model works very well at both low and high reduced temperatures approaching the critical point (0.02 < epsilon = (T /SUB c/ - T)/(T /SUB c/- 0.69)). About 16 compounds, including single, two, and three-ring compounds, have been tested and the percent root-mean-square deviations in latent heat of vaporization reported and estimated through the model are 0.42 to 5.27%. Tables of the coefficients of L/sub 0/ and L/sub 1/ are presented. The contributing terms of the latent heat of vaporization function are also presented in a table for small increments of epsilon.

Photodynamic inactivation of rubella virus enhances recombination with a latent virus of a baby hamster kidney cell line BHK21

International Nuclear Information System (INIS)

Yamamoto, Nobuto; Urade, Masahiro

1989-01-01

Rubella virus is very sensitive to photodynamic action. When tested with 1.2 x 10 -5 M toluidine blue and 8 W fluorescent lamp at a fluence of 11 W/m 2 , inactivation kinetics showed a linear single hit curve with a k value of 1.48 min -1 . Photodynamic inactivation of rubella virus greatly enhanced recombination with a latent virus (R-virus) of baby hamster kidney BHK21 cells. In contrast, no hybrids were detected in lysates of the cells infected with either UV-treated or untreated rubella virus. Therefore, hybrid viruses were readily detected only in lysates of BHK21 cells infected with photodynamically treated rubella virus. Photodynamic damage of rubella virus genomes generated a new hybrid type (hybrid type 3) in addition to a previously described type 2 hybrid (formerly designated as HPV-RV variant). Although both of these hybrid types carry the CF antigens of rubella virus, plaque forming ability of type 3 hybrid is neutralized neither by anti-rubella serum nor by anti-latent virus serum while type 2 hybrid is neutralized by anti-latent virus serum. (author)

Graphical user interface for input output characterization of single variable and multivariable highly nonlinear systems

Directory of Open Access Journals (Sweden)

Shahrukh Adnan Khan M. D.

2017-01-01

Full Text Available This paper presents a Graphical User Interface (GUI software utility for the input/output characterization of single variable and multivariable nonlinear systems by obtaining the sinusoidal input describing function (SIDF of the plant. The software utility is developed on MATLAB R2011a environment. The developed GUI holds no restriction on the nonlinearity type, arrangement and system order; provided that output(s of the system is obtainable either though simulation or experiments. An insight to the GUI and its features are presented in this paper and example problems from both single variable and multivariable cases are demonstrated. The formulation of input/output behavior of the system is discussed and the nucleus of the MATLAB command underlying the user interface has been outlined. Some of the industries that would benefit from this software utility includes but not limited to aerospace, defense technology, robotics and automotive.

Latent class factor and cluster models, bi-plots and tri-plots and related graphical displays

NARCIS (Netherlands)

Magidson, J.; Vermunt, J.K.

2001-01-01

We propose an alternative method of conducting exploratory latent class analysis that utilizes latent class factor models, and compare it to the more traditional approach based on latent class cluster models. We show that when formulated in terms of R mutually independent, dichotomous latent

Latent uncertainties of the precalculated track Monte Carlo method

Energy Technology Data Exchange (ETDEWEB)

Renaud, Marc-André; Seuntjens, Jan [Medical Physics Unit, McGill University, Montreal, Quebec H3G 1A4 (Canada); Roberge, David [Département de radio-oncologie, Centre Hospitalier de l’Université de Montréal, Montreal, Quebec H2L 4M1 (Canada)

2015-01-15

Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D{sub max}. Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of

Latent uncertainties of the precalculated track Monte Carlo method

International Nuclear Information System (INIS)

Renaud, Marc-André; Seuntjens, Jan; Roberge, David

2015-01-01

Purpose: While significant progress has been made in speeding up Monte Carlo (MC) dose calculation methods, they remain too time-consuming for the purpose of inverse planning. To achieve clinically usable calculation speeds, a precalculated Monte Carlo (PMC) algorithm for proton and electron transport was developed to run on graphics processing units (GPUs). The algorithm utilizes pregenerated particle track data from conventional MC codes for different materials such as water, bone, and lung to produce dose distributions in voxelized phantoms. While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from the limited number of unique tracks in the pregenerated track bank is missing from the paper. With a proper uncertainty analysis, an optimal number of tracks in the pregenerated track bank can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pregenerated for electrons and protons using EGSnrc and GEANT4 and saved in a database. The PMC algorithm for track selection, rotation, and transport was implemented on the Compute Unified Device Architecture (CUDA) 4.0 programming framework. PMC dose distributions were calculated in a variety of media and compared to benchmark dose distributions simulated from the corresponding general-purpose MC codes in the same conditions. A latent uncertainty metric was defined and analysis was performed by varying the pregenerated track bank size and the number of simulated primary particle histories and comparing dose values to a “ground truth” benchmark dose distribution calculated to 0.04% average uncertainty in voxels with dose greater than 20% of D max . Efficiency metrics were calculated against benchmark MC codes on a single CPU core with no variance reduction. Results: Dose distributions generated using PMC and benchmark MC codes were compared and found to be within 2% of each other in voxels with dose values greater than 20% of the

A solar air collector with integrated latent heat thermal storage

Directory of Open Access Journals (Sweden)

Klimes Lubomir

2012-04-01

Full Text Available Simulations of the behaviour of a solar air collector with integrated latent heat thermal storage were performed. The model of the collector was created with the use of coupling between TRNSYS 17 and MATLAB. Latent heat storage (Phase Change Material - PCM was integrated with the solar absorber. The model of the latent heat storage absorber was created in MATLAB and the model of the solar air collector itself was created in TRNSYS with the use of TYPE 56. The model of the latent heat storage absorber allows specification of the PCM properties as well as other parameters. The simulated air collector was the front and back pass collector with the absorber in the middle of the air cavity. Two variants were considered for comparison; the light-weight absorber made of sheet metal and the heat-storage absorber with the PCM. Simulations were performed for the climatic conditions of the Czech Republic (using TMY weather data.

Genetic analysis of glucosinolate variability in broccoli florets using genome-anchored single nucleotide polymorphisms.

Science.gov (United States)

Brown, Allan F; Yousef, Gad G; Reid, Robert W; Chebrolu, Kranthi K; Thomas, Aswathy; Krueger, Christopher; Jeffery, Elizabeth; Jackson, Eric; Juvik, John A

2015-07-01

The identification of genetic factors influencing the accumulation of individual glucosinolates in broccoli florets provides novel insight into the regulation of glucosinolate levels in Brassica vegetables and will accelerate the development of vegetables with glucosinolate profiles tailored to promote human health. Quantitative trait loci analysis of glucosinolate (GSL) variability was conducted with a B. oleracea (broccoli) mapping population, saturated with single nucleotide polymorphism markers from a high-density array designed for rapeseed (Brassica napus). In 4 years of analysis, 14 QTLs were associated with the accumulation of aliphatic, indolic, or aromatic GSLs in floret tissue. The accumulation of 3-carbon aliphatic GSLs (2-propenyl and 3-methylsulfinylpropyl) was primarily associated with a single QTL on C05, but common regulation of 4-carbon aliphatic GSLs was not observed. A single locus on C09, associated with up to 40 % of the phenotypic variability of 2-hydroxy-3-butenyl GSL over multiple years, was not associated with the variability of precursor compounds. Similarly, QTLs on C02, C04, and C09 were associated with 4-methylsulfinylbutyl GSL concentration over multiple years but were not significantly associated with downstream compounds. Genome-specific SNP markers were used to identify candidate genes that co-localized to marker intervals and previously sequenced Brassica oleracea BAC clones containing known GSL genes (GSL-ALK, GSL-PRO, and GSL-ELONG) were aligned to the genomic sequence, providing support that at least three of our 14 QTLs likely correspond to previously identified GSL loci. The results demonstrate that previously identified loci do not fully explain GSL variation in broccoli. The identification of additional genetic factors influencing the accumulation of GSL in broccoli florets provides novel insight into the regulation of GSL levels in Brassicaceae and will accelerate development of vegetables with modified or enhanced GSL

Latent class models for classification

NARCIS (Netherlands)

Vermunt, J.K.; Magidson, J.

2003-01-01

An overview is provided of recent developments in the use of latent class (LC) and other types of finite mixture models for classification purposes. Several extensions of existing models are presented. Two basic types of LC models for classification are defined: supervised and unsupervised

Radiographer use of anatomical side markers and the latent conditions affecting their use in practice

International Nuclear Information System (INIS)

Titley, Anna G.; Cosson, Philip

2014-01-01

Background: Patient safety is a primary concern within the NHS. It has been reported that anatomical side marker (ASM) use in radiography does not meet the ‘best practice’ standard. Case reports suggest this may be a contributing factor to adverse events in healthcare. Purpose: This study aimed to investigate the latent conditions contributing to poor ASM practice; communities of practice, time of image acquisition and competing priorities with collimation practice. Method: Proxy variables of projection and laterality were used to measure communities of practice. ASM practice on 330 examinations (170 lumbar spine, 160 finger) was retrospectively observed using a data collection tool. Aggregate scores were calculated from the two images in each examination. Data was analysed using descriptive statistics, chi-square tests (projection) and Mann–Whitney U tests (laterality, time of acquisition and collimation practice). Results: ‘Best practice’ ASM use was met on one examination. Correct ASM were observed within the primary collimation in 32.0% images. Projection, laterality and collimation practice were associated with ASM use. Time of acquisition was not found to be associated. Discussion: Communities of practice and competing priorities impact on ASM use. Logistic regression to determine a primary latent condition was not possible. However, comparison with previous research suggests this is likely to be specific to each radiography department. Conclusion: Latent conditions are associated with poor ASM practice. These must be identified and addressed in each individual radiography department, to improve patient safety and uphold NHS Constitutional standards

Rapid detection of drug metabolites in latent fingermarks.

Science.gov (United States)

Hazarika, Pompi; Jickells, Sue M; Russell, David A

2009-01-01

Magnetic particles functionalised with anti-cotinine antibody have been used to image latent fingermarks through the detection of the cotinine antigen in the sweat deposited within the fingerprints of smokers. The antibody-magnetic particle conjugates are readily applied to latent fingerprints while excess reagents are removed through the use of a magnetic wand. The results have shown that drug metabolites, such as cotinine, can be detected and used to image the fingermark to establish the identity of an individual within 15 minutes.

A personality-based latent class typology of outpatients with major depressive disorder: association with symptomatology, prescription pattern and social function.

Science.gov (United States)

Hori, Hiroaki; Teraishi, Toshiya; Nagashima, Anna; Koga, Norie; Ota, Miho; Hattori, Kotaro; Kim, Yoshiharu; Higuchi, Teruhiko; Kunugi, Hiroshi

2017-08-01

While major depressive disorder (MDD) is considered to be a heterogeneous disorder, the nature of the heterogeneity remains unclear. Studies have attempted to classify patients with MDD using latent variable techniques, yet the empirical approaches to symptom-based subtyping of MDD have not provided conclusive evidence. Here we aimed to identify homogeneous classes of MDD based on personality traits, using a latent profile analysis. We studied 238 outpatients with DSM-IV MDD recruited from our specialized depression outpatient clinic and assessed their dimensional personality traits with the Temperament and Character Inventory. Latent profile analysis was conducted with 7 dimensions of the Temperament and Character Inventory as indicators. Relationships of the identified classes with symptomatology, prescription pattern, and social function were then examined. The latent profile analysis indicated that a 3-class solution best fit the data. Of the sample, 46.2% was classified into a "neurotic" group characterized by high harm avoidance and low self-directedness; 30.3% into an "adaptive" group characterized by high self-directedness and cooperativeness; and 23.5% into a "socially-detached" group characterized by low reward dependence and cooperativeness and high self-transcendence. The 2 maladaptive groups, namely neurotic and socially-detached groups, demonstrated unique patterns of symptom expression, different classes of psychotropic medication use, and lower social functioning. Generalizability of the findings was limited since our patients were recruited from the specialized depression outpatient clinic. Our personality-based latent profile analysis identified clinically meaningful 3 MDD groups that were markedly different in their personality profiles associated with distinct symptomatology and functioning. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of latent toxoplasmosis on autoimmune thyroid diseases in pregnancy.

Science.gov (United States)

Kaňková, Šárka; Procházková, Lucie; Flegr, Jaroslav; Calda, Pavel; Springer, Drahomíra; Potluková, Eliška

2014-01-01

Toxoplasmosis, one of the most common zoonotic diseases worldwide, can induce various hormonal and behavioural alterations in infected hosts, and its most common form, latent toxoplasmosis, influences the course of pregnancy. Autoimmune thyroid diseases (AITD) belong to the well-defined risk factors for adverse pregnancy outcomes. The aim of this study was to investigate whether there is a link between latent toxoplasmosis and maternal AITD in pregnancy. Cross-sectional study in 1248 consecutive pregnant women in the 9-12th gestational weeks. Serum thyroid-stimulating hormone (TSH), thyroperoxidase antibodies (TPOAb), and free thyroxine (FT4) were assessed by chemiluminescence; the Toxoplasma status was detected by the complement fixation test (CFT) and anti-Toxoplasma IgG enzyme-linked immunosorbent assay (ELISA). Overall, 22.5% of the women were positive for latent toxoplasmosis and 14.7% were screened positive for AITD. Women with latent toxoplasmosis had more often highly elevated TPOAb than the Toxoplasma-negative ones (p = 0.004), and latent toxoplasmosis was associated with decrease in serum TSH levels (p = 0.049). Moreover, we found a positive correlation between FT4 and the index of positivity for anti-Toxoplasma IgG antibodies (p = 0.033), which was even stronger in the TPOAb-positive Toxoplasma-positive women, (p = 0.014), as well as a positive correlation between FT4 and log2 CFT (p = 0.009). Latent toxoplasmosis was associated with a mild increase in thyroid hormone production in pregnancy. The observed Toxoplasma-associated changes in the parameters of AITD are mild and do not seem to be clinically relevant; however, they could provide new clues to the complex pathogenesis of autoimmune thyroid diseases.

Adolescent substance use behavior and suicidal behavior for boys and girls: a cross-sectional study by latent analysis approach

OpenAIRE

Wang, Peng-Wei; Yen, Cheng-Fang

2017-01-01

Background Adolescent suicidal behavior may consist of different symptoms, including suicidal ideation, suicidal planning and suicidal attempts. Adolescent substance use behavior may contribute to adolescent suicidal behavior. However, research on the relationships between specific substance use and individual suicidal behavior is insufficient, as adolescents may not use only one substance or develop only one facet of suicidal behavior. Latent variables permit us to describe the relationships...

Latent effectiveness of desiccant wheel: A silica gels- water system

International Nuclear Information System (INIS)

Rabah, A. A.; Mohamed, S. A.

2009-01-01

A latent heat effectiveness model in term of dimensionless groups? =f (NTU, m * ,Crm * ) for energy wheel has been analytically derived. The energy wheel is divided into humidification and dehumidification sections. For each section macroscopic mass differential equations for gas and the matrix were applied. In this process local latent effectiveness (? c ,? h ) for the humidification and dehumidification section of the wheel were obtained. The Latent effectiveness of the wheel is then derived form local effectiveness [? =f (? c ,? h)]. The model is compared with the existing experimental investigation and manufacturer data for energy wheel. More than 90% of the experimental data within a confidence limit of 95%. (Author)

Intercept Centering and Time Coding in Latent Difference Score Models

Science.gov (United States)

Grimm, Kevin J.

2012-01-01

Latent difference score (LDS) models combine benefits derived from autoregressive and latent growth curve models allowing for time-dependent influences and systematic change. The specification and descriptions of LDS models include an initial level of ability or trait plus an accumulation of changes. A limitation of this specification is that the…

Friendship networks of inner-city adults: a latent class analysis and multi-level regression of supporter types and the association of supporter latent class membership with supporter and recipient drug use.

Science.gov (United States)

Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A

2010-03-01

Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.

Large-scale weakly supervised object localization via latent category learning.

Science.gov (United States)

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

Reliability measures in item response theory: manifest versus latent correlation functions.

Science.gov (United States)

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Verbeke, Geert; De Boeck, Paul

2015-02-01

For item response theory (IRT) models, which belong to the class of generalized linear or non-linear mixed models, reliability at the scale of observed scores (i.e., manifest correlation) is more difficult to calculate than latent correlation based reliability, but usually of greater scientific interest. This is not least because it cannot be calculated explicitly when the logit link is used in conjunction with normal random effects. As such, approximations such as Fisher's information coefficient, Cronbach's α, or the latent correlation are calculated, allegedly because it is easy to do so. Cronbach's α has well-known and serious drawbacks, Fisher's information is not meaningful under certain circumstances, and there is an important but often overlooked difference between latent and manifest correlations. Here, manifest correlation refers to correlation between observed scores, while latent correlation refers to correlation between scores at the latent (e.g., logit or probit) scale. Thus, using one in place of the other can lead to erroneous conclusions. Taylor series based reliability measures, which are based on manifest correlation functions, are derived and a careful comparison of reliability measures based on latent correlations, Fisher's information, and exact reliability is carried out. The latent correlations are virtually always considerably higher than their manifest counterparts, Fisher's information measure shows no coherent behaviour (it is even negative in some cases), while the newly introduced Taylor series based approximations reflect the exact reliability very closely. Comparisons among the various types of correlations, for various IRT models, are made using algebraic expressions, Monte Carlo simulations, and data analysis. Given the light computational burden and the performance of Taylor series based reliability measures, their use is recommended. © 2014 The British Psychological Society.

Targeting nanodisks via a single chain variable antibody - Apolipoprotein chimera

International Nuclear Information System (INIS)

Iovannisci, David M.; Beckstead, Jennifer A.; Ryan, Robert O.

2009-01-01

Nanodisks (ND) are nanometer scale complexes of phospholipid and apolipoprotein that have been shown to function as drug delivery vehicles. ND harboring significant quantities of the antifungal agent, amphotericin B, or the bioactive isoprenoid, all trans retinoic acid, have been generated and characterized. As currently formulated, ND possess limited targeting capability. In this study, we constructed a single chain variable antibody (scFv).apolipoprotein chimera and assessed the ability of this fusion protein to form ND and recognize the antigen to which the scFv is directed. Data obtained revealed that α-vimentin scFv.apolipoprotein A-I is functional in ND formation and antigen recognition, opening the door to the use of such chimeras in targeting drug-enriched ND to specific tissues.

Personal and Financial Risk Typologies Among Women Who Engage in Sex Work in Mongolia: A Latent Class Analysis.

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Offringa, Reid; Tsai, Laura Cordisco; Aira, Toivgoo; Riedel, Marion; Witte, Susan S

2017-08-01

Women engaged in sex work bear a disproportionate burden of HIV infection worldwide, particularly in low- to middle-income countries. Stakeholders interested in promoting prevention and treatment programs are challenged to efficiently and effectively target heterogeneous groups of women. This problem is particularly difficult because it is nearly impossible to know how those groups are composed a priori. Although grouping based on individual variables (e.g., age or place of solicitation) can describe a sample of women engaged in sex work, selecting these variables requires a strong intuitive understanding of the population. Furthermore, this approach is difficult to quantify and has the potential to reinforce preconceived notions, rather than generate new information. We aimed to investigate groupings of women engaged in sex work. The data were collected from a sample of 204 women who were referred to an HIV prevention intervention in Ulaanbaatar, Mongolia. Latent class analysis was used to create subgroups of women engaged in sex work, based on personal and financial risk factors. This analysis found three latent classes, representing unique response pattern profiles of personal and financial risk. The current study approached typology research in a novel, more empirical way and provided a description of different subgroups, which may respond differently to HIV risk interventions.

A single exercise bout augments adenovirus-specific T-cell mobilization and function.

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Kunz, Hawley E; Spielmann, Guillaume; Agha, Nadia H; O'Connor, Daniel P; Bollard, Catherine M; Simpson, Richard J

2018-04-30

Adoptive transfer of virus-specific T-cells (VSTs) effectively treats viral infections following allogeneic hematopoietic stem cell transplantation (alloHSCT), but logistical difficulties have limited widespread availability of VSTs as a post-transplant therapeutic. A single exercise bout mobilizes VSTs specific for latent herpesviruses (i.e. CMV and EBV) to peripheral blood and augments their ex vivo expansion. We investigated whether exercise exerts similar effects on T-cells specific for a NON-latent virus such as adenovirus, which is a major contributor to infection-related morbidity and mortality after alloHSCT. Thirty minutes of cycling exercise increased circulating adenovirus-specific T-cells 2.0-fold and augmented their ex vivo expansion by ~33% compared to rest without altering antigen and MHC-specific autologous target cell killing capabilities. We conclude that exercise is a simple and economical adjuvant to boost the isolation and manufacture of therapeutic VSTs specific to latent and non-latent viruses from healthy donors. Copyright © 2018. Published by Elsevier Inc.

A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.

Science.gov (United States)

Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven

2003-01-01

Proposed a taxonomy of latent structure assumptions for probability matrix decomposition (PMD) that includes the original PMD model and a three-way extension of the multiple classification latent class model. Simulation study results show the usefulness of the taxonomy. (SLD)

Rapid visualization of latent fingermarks using gold seed-mediated enhancement

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Chia-Hao Su

2016-11-01

Full Text Available Abstract Background Fingermarks are one of the most important and useful forms of physical evidence in forensic investigations. However, latent fingermarks are not directly visible, but can be visualized due to the presence of other residues (such as inorganic salts, proteins, polypeptides, enzymes and human metabolites which can be detected or recognized through various strategies. Convenient and rapid techniques are still needed to provide obvious contrast between the background and the fingermark ridges and to then visualize latent fingermark with a high degree of selectivity and sensitivity. Results In this work, lysozyme-binding aptamer-conjugated Au nanoparticles (NPs are used to recognize and target lysozyme in the fingermark ridges, and Au+-complex solution is used as a growth agent to reduce Au+ from Au+ to Au0 on the surface of the Au NPs. Distinct fingermark patterns were visualized on a range of professional forensic within 3 min; the resulting images could be observed by the naked eye without background interference. The entire processes from fingermark collection to visualization only entails two steps and can be completed in less than 10 min. The proposed method provides cost and time savings over current fingermark visualization methods. Conclusions We report a simple, inexpensive, and fast method for the rapid visualization of latent fingermarks on the non-porous substrates using Au seed-mediated enhancement. Au seed-mediated enhancement is used to achieve the rapid visualization of latent fingermarks on non-porous substrates by the naked eye without the use of expensive or sophisticated instruments. The proposed approach offers faster detection and visualization of latent fingermarks than existing methods. The proposed method is expected to increase detection efficiency for latent fingermarks and reduce time requirements and costs for forensic investigations.

Interferon-gamma release assay for the diagnosis of latent tuberculosis infection: A latent-class analysis.

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Tan N Doan

Full Text Available Accurate diagnosis and subsequent treatment of latent tuberculosis infection (LTBI is essential for TB elimination. However, the absence of a gold standard test for diagnosing LTBI makes assessment of the true prevalence of LTBI and the accuracy of diagnostic tests challenging. Bayesian latent class models can be used to make inferences about disease prevalence and the sensitivity and specificity of diagnostic tests using data on the concordance between tests. We performed the largest meta-analysis to date aiming to evaluate the performance of tuberculin skin test (TST and interferon-gamma release assays (IGRAs for LTBI diagnosis in various patient populations using Bayesian latent class modelling.Systematic search of PubMeb, Embase and African Index Medicus was conducted without date and language restrictions on September 11, 2017 to identify studies that compared the performance of TST and IGRAs for LTBI diagnosis. Two IGRA methods were considered: QuantiFERON-TB Gold In Tube (QFT-GIT and T-SPOT.TB. Studies were included if they reported 2x2 agreement data between TST and QFT-GIT or T-SPOT.TB. A Bayesian latent class model was developed to estimate the sensitivity and specificity of TST and IGRAs in various populations, including immune-competent adults, immune-compromised adults and children. A TST cut-off value of 10 mm was used for immune-competent subjects and 5 mm for immune-compromised individuals.A total of 157 studies were included in the analysis. In immune-competent adults, the sensitivity of TST and QFT-GIT were estimated to be 84% (95% credible interval [CrI] 82-85% and 52% (50-53%, respectively. The specificity of QFT-GIT was 97% (96-97% in non-BCG-vaccinated and 93% (92-94% in BCG-vaccinated immune-competent adults. The estimated figures for TST were 100% (99-100% and 79% (76-82%, respectively. T-SPOT.TB has comparable specificity (97% for both tests and better sensitivity (68% versus 52% than QFT-GIT in immune-competent adults

Autonomic Differentiation Map: A Novel Statistical Tool for Interpretation of Heart Rate Variability

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Daniela Lucini

2018-04-01

Full Text Available In spite of the large body of evidence suggesting Heart Rate Variability (HRV alone or combined with blood pressure variability (providing an estimate of baroreflex gain as a useful technique to assess the autonomic regulation of the cardiovascular system, there is still an ongoing debate about methodology, interpretation, and clinical applications. In the present investigation, we hypothesize that non-parametric and multivariate exploratory statistical manipulation of HRV data could provide a novel informational tool useful to differentiate normal controls from clinical groups, such as athletes, or subjects affected by obesity, hypertension, or stress. With a data-driven protocol in 1,352 ambulant subjects, we compute HRV and baroreflex indices from short-term data series as proxies of autonomic (ANS regulation. We apply a three-step statistical procedure, by first removing age and gender effects. Subsequently, by factor analysis, we extract four ANS latent domains that detain the large majority of information (86.94%, subdivided in oscillatory (40.84%, amplitude (18.04%, pressure (16.48%, and pulse domains (11.58%. Finally, we test the overall capacity to differentiate clinical groups vs. control. To give more practical value and improve readability, statistical results concerning individual discriminant ANS proxies and ANS differentiation profiles are displayed through peculiar graphical tools, i.e., significance diagram and ANS differentiation map, respectively. This approach, which simultaneously uses all available information about the system, shows what domains make up the difference in ANS discrimination. e.g., athletes differ from controls in all domains, but with a graded strength: maximal in the (normalized oscillatory and in the pulse domains, slightly less in the pressure domain and minimal in the amplitude domain. The application of multiple (non-parametric and exploratory statistical and graphical tools to ANS proxies defines

Latent Toxoplasma gondii infection leads to improved action control.

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Stock, Ann-Kathrin; Heintschel von Heinegg, Evelyn; Köhling, Hedda-Luise; Beste, Christian

2014-03-01

The parasite Toxoplasma gondii has been found to manipulate the behavior of its secondary hosts to increase its own dissemination which is commonly believed to be to the detriment of the host (manipulation hypothesis). The manipulation correlates with an up-regulation of dopaminergic neurotransmission. In humans, different pathologies have been associated with T. gondii infections but most latently infected humans do not seem to display overt impairments. Since a dopamine plus does not necessarily bear exclusively negative consequences in humans, we investigated potential positive consequences of latent toxoplasmosis (and the presumed boosting of dopaminergic neurotransmission) on human cognition and behavior. For this purpose, we focused on action cascading which has been shown to be modulated by dopamine. Based on behavioral and neurophysiological (EEG) data obtained by means of a stop-change paradigm, we were able to demonstrate that healthy young humans can actually benefit from latent T. gondii infection as regards their performance in this task (as indicated by faster response times and a smaller P3 component). The data shows that a latent infection which is assumed to affect the dopaminergic system can lead to paradoxical improvements of cognitive control processes in humans. Copyright © 2013 Elsevier Inc. All rights reserved.

Chromatin Structure of Epstein-Barr Virus Latent Episomes.

Science.gov (United States)

Lieberman, Paul M

2015-01-01

EBV latent infection is characterized by a highly restricted pattern of viral gene expression. EBV can establish latent infections in multiple different tissue types with remarkable variation and plasticity in viral transcription and replication. During latency, the viral genome persists as a multi-copy episome, a non-integrated-closed circular DNA with nucleosome structure similar to cellular chromosomes. Chromatin assembly and histone modifications contribute to the regulation of viral gene expression, DNA replication, and episome persistence during latency. This review focuses on how EBV latency is regulated by chromatin and its associated processes.

A joint latent class model for classifying severely hemorrhaging trauma patients.

Science.gov (United States)

Rahbar, Mohammad H; Ning, Jing; Choi, Sangbum; Piao, Jin; Hong, Chuan; Huang, Hanwen; Del Junco, Deborah J; Fox, Erin E; Rahbar, Elaheh; Holcomb, John B

2015-10-24

In trauma research, "massive transfusion" (MT), historically defined as receiving ≥10 units of red blood cells (RBCs) within 24 h of admission, has been routinely used as a "gold standard" for quantifying bleeding severity. Due to early in-hospital mortality, however, MT is subject to survivor bias and thus a poorly defined criterion to classify bleeding trauma patients. Using the data from a retrospective trauma transfusion study, we applied a latent-class (LC) mixture model to identify severely hemorrhaging (SH) patients. Based on the joint distribution of cumulative units of RBCs and binary survival outcome at 24 h of admission, we applied an expectation-maximization (EM) algorithm to obtain model parameters. Estimated posterior probabilities were used for patients' classification and compared with the MT rule. To evaluate predictive performance of the LC-based classification, we examined the role of six clinical variables as predictors using two separate logistic regression models. Out of 471 trauma patients, 211 (45 %) were MT, while our latent SH classifier identified only 127 (27 %) of patients as SH. The agreement between the two classification methods was 73 %. A non-ignorable portion of patients (17 out of 68, 25 %) who died within 24 h were not classified as MT but the SH group included 62 patients (91 %) who died during the same period. Our comparison of the predictive models based on MT and SH revealed significant differences between the coefficients of potential predictors of patients who may be in need of activation of the massive transfusion protocol. The traditional MT classification does not adequately reflect transfusion practices and outcomes during the trauma reception and initial resuscitation phase. Although we have demonstrated that joint latent class modeling could be used to correct for potential bias caused by misclassification of severely bleeding patients, improvement in this approach could be made in the presence of time to event

Using latent effects to determine the ecological importance of dissolved organic matter to marine invertebrates.

Science.gov (United States)

Wendt, Dean E; Johnson, Collin H

2006-10-01

The uptake and utilization of dissolved organic matter (DOM) by marine invertebrates is a field that has received significant attention over the past 100 years. Although it is well established that DOM is taken up by marine invertebrates, the extent to which it contributes to an animal's survival, growth, and reproduction (that is, the ecological benefits) remains largely unknown. Previous work seeking to demonstrate the putative ecological benefits of DOM uptake have examined them within a single life stage of an animal. Moreover, most of the benefits are demonstrated through indirect approaches by examining (1) mass balance, or (2) making comparisons of oxyenthalpic conversions of transport rates to metabolic rate as judged by oxygen consumption. We suggest that directly examining delayed metamorphosis or the latent effects associated with nutritional stress of larvae is a better model for investigating the ecological importance of DOM to marine invertebrates. We also provide direct evidence that availability of DOM enhances survival and growth of the bryozoan Bugula neritina. That DOM offsets latent effects in B. neritina suggests that the underlying mechanisms are at least in part energetic.

Reporting guidelines for diagnostic accuracy studies that use Bayesian latent class models (STARD-BLCM)

DEFF Research Database (Denmark)

Kostoulas, Polychronis; Nielsen, Søren S.; Branscum, Adam J.

2017-01-01

of disease status (i.e., disease status is a latent variable). Statistical methods were introduced in this context by Hui and Walter and have been succesfully applied since then, with the majority of the work being carried out in a Bayesian framework. While STARD provides useful reporting guidelines...... for studies designed to estimate the accuracy of tests when disease status is known. The original STARD statement was initially published in seven journals, while an updated version — STARD2015 — has been recently released. More than 200 biomedical journals encourage its use in their instructions to authors...

Self-Consciousness and Assertiveness as Explanatory Variables of L2 Oral Ability: A Latent Variable Approach

Science.gov (United States)

Ockey, Gary

2011-01-01

Drawing on current theories in personality, second-language (L2) oral ability, and psychometrics, this study investigates the extent to which self-consciousness and assertiveness are explanatory variables of L2 oral ability. Three hundred sixty first-year Japanese university students who were studying English as a foreign language participated in…

Probabilistic Latent Semantic Analyses (PLSA in Bibliometric Analysis for Technology Forecasting

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Wang Zan

2007-03-01

Full Text Available Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency

Latent class models in financial data analysis

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Attilio Gardini

2007-10-01

Full Text Available This paper deals with optimal international portfolio choice by developing a latent class approach based on the distinction between international and non-international investors. On the basis of micro data, we analyze the effects of many social, demographic, economic and financial characteristics on the probability to be an international investor. Traditional measures of equity home bias do not allow for the existence of international investment rationing operators. On the contrary, by resorting to latent class analysis it is possible to detect the unobservable distinction between international investors and investors who are precluded from operating into international financial markets and, therefore, to evaluate the role of these unobservable constraints on equity home bias.

Undergraduate Nurse Variables that Predict Academic Achievement and Clinical Competence in Nursing

Science.gov (United States)

Blackman, Ian; Hall, Margaret; Darmawan, I Gusti Ngurah.

2007-01-01

A hypothetical model was formulated to explore factors that influenced academic and clinical achievement for undergraduate nursing students. Sixteen latent variables were considered including the students' background, gender, type of first language, age, their previous successes with their undergraduate nursing studies and status given for…

Characterization of a Latent Virus-Like Infection of Symbiotic Zooxanthellae▿

Science.gov (United States)

Lohr, Jayme; Munn, Colin B.; Wilson, William H.

2007-01-01

A latent virus-like agent, which we designated zooxanthella filamentous virus 1 (ZFV1), was isolated from Symbiodinium sp. strain CCMP 2465 and characterized. Transmission electron microscopy and analytical flow cytometry revealed the presence of a new group of distinctive filamentous virus-like particles after exposure of the zooxanthellae to UV light. Examination of thin sections of the zooxanthellae revealed the formation and proliferation of filamentous virus-like particles in the UV-induced cells. Assessment of Symbiodinium sp. cultures was used here as a model to show the effects of UV irradiance and induction of potential latent viruses. The unique host-virus system described here provides insight into the role of latent infections in zooxanthellae through environmentally regulated viral induction mechanisms. PMID:17351090

Characterization of a latent virus-like infection of symbiotic zooxanthellae.

Science.gov (United States)

Lohr, Jayme; Munn, Colin B; Wilson, William H

2007-05-01

A latent virus-like agent, which we designated zooxanthella filamentous virus 1 (ZFV1), was isolated from Symbiodinium sp. strain CCMP 2465 and characterized. Transmission electron microscopy and analytical flow cytometry revealed the presence of a new group of distinctive filamentous virus-like particles after exposure of the zooxanthellae to UV light. Examination of thin sections of the zooxanthellae revealed the formation and proliferation of filamentous virus-like particles in the UV-induced cells. Assessment of Symbiodinium sp. cultures was used here as a model to show the effects of UV irradiance and induction of potential latent viruses. The unique host-virus system described here provides insight into the role of latent infections in zooxanthellae through environmentally regulated viral induction mechanisms.

Single-trial estimation of stimulus and spike-history effects on time-varying ensemble spiking activity of multiple neurons: a simulation study

International Nuclear Information System (INIS)

Shimazaki, Hideaki

2013-01-01

Neurons in cortical circuits exhibit coordinated spiking activity, and can produce correlated synchronous spikes during behavior and cognition. We recently developed a method for estimating the dynamics of correlated ensemble activity by combining a model of simultaneous neuronal interactions (e.g., a spin-glass model) with a state-space method (Shimazaki et al. 2012 PLoS Comput Biol 8 e1002385). This method allows us to estimate stimulus-evoked dynamics of neuronal interactions which is reproducible in repeated trials under identical experimental conditions. However, the method may not be suitable for detecting stimulus responses if the neuronal dynamics exhibits significant variability across trials. In addition, the previous model does not include effects of past spiking activity of the neurons on the current state of ensemble activity. In this study, we develop a parametric method for simultaneously estimating the stimulus and spike-history effects on the ensemble activity from single-trial data even if the neurons exhibit dynamics that is largely unrelated to these effects. For this goal, we model ensemble neuronal activity as a latent process and include the stimulus and spike-history effects as exogenous inputs to the latent process. We develop an expectation-maximization algorithm that simultaneously achieves estimation of the latent process, stimulus responses, and spike-history effects. The proposed method is useful to analyze an interaction of internal cortical states and sensory evoked activity

The latent effect of inertia in the modal choice

DEFF Research Database (Denmark)

Cherchi, Elisabetta; Meloni, Italo; Ortúzar, Juan de Dios

2014-01-01

The existence of habit (leading to inertia) in the choice process has been approached in the literature in a number of ways. In transport, inertia has been studied mainly using “long panel” data, or mixed revealed and stated preference data. In these studies inertia links the choice made in two...... approaches. We assume that inertia is revealed by past behaviour and affects also the initial condition, but we recognise that past behaviour is only an indicator of habitual behaviour, the true process behind the formation of habitual behaviour being latent. We estimate a hybrid choice model using a set...... of revealed and stated mode choice preferences collected in Cagliari (Italy). We found a significant latent inertia in the revealed preference data, indicating that inertia affects the initial conditions. The latent inertia is revealed by the frequency of past behaviour but the effect of trip frequency...

Maltreatment histories of foster youth exiting out-of-home care through emancipation: a latent class analysis.

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Havlicek, Judy

2014-01-01

Little is known about maltreatment among foster youth transitioning to adulthood. Multiple entries into out-of-home care and unsuccessful attempts at reunification may nevertheless reflect extended exposure to chronic maltreatment and multiple types of victimization. This study used administrative data from the Illinois Department of Children and Family Services to identify all unduplicated allegations of maltreatment in a cohort of 801 foster youth transitioning to adulthood in the state of Illinois. A latent variable modeling approach generated profiles of maltreatment based on substantiated and unsubstantiated reports of maltreatment taken from state administrative data. Four indicators of maltreatment were included in the latent class analysis: multiple types of maltreatment, predominant type of maltreatment, chronicity, and number of different perpetrators. The analysis identified four subpopulations of foster youth in relation to maltreatment. Study findings highlight the heterogeneity of maltreatment in the lives of foster youth transitioning to adulthood and draw attention to a need to raise awareness among service providers to screen for chronic maltreatment and multiple types of victimization. © The Author(s) 2014.

Using standard serology blood tests to diagnose latent syphilis

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G. L. Katunin

2016-01-01

Full Text Available Goal. To conduct a comparative assessment of the results of regulated serological tests obtained as a result of blood tests in patients suffering from latent syphilis. Materials and methods. The authors examined 187 patient medical records with newly diagnosed latent syphilis in FGBU GNTsDK (State Research Center for Dermatology, Venereology and Cosmetology, Health Ministry of the Russian Federation, in 2006-2015. The results of patient blood tests were analyzed with the use of non-treponemal (microprecipitation test/RPR and treponemal (passive hemagglutination test, immune-enzyme assay (IgA, IgM, IgG, IFabs, immunofluorescence test and Treponema pallidum immobilization test serology tests. Results. According to the results of blood tests of latent syphilis patients, the largest number of positive results was obtained as a result of treponemal serology tests such as immune-enzyme assay (100%, passive hemagglutination test (100% and IFabs (100%. The greatest number of negative results was observed in non-treponemal (microprecipitation test/RPR serology tests: in 136 (72.7% patients; evidently positive results (4+ test results were obtained in 8 (4.3% patients only. According to the results of a comparative analysis of blood tests in patients suffering from latent syphilis obtained with the use of treponemal serology tests, the greatest number of evidently positive results (4+ was noted for the passive hemagglutination test (67.9%. Negative treponemal test results were obtained with the use of the immunofluorescence test and Treponema pallidum immobilization test (21.9% and 11.8% of cases, respectively. Moreover, weakly positive results prevailed for the immunofluorescence test: in 65 (34.7% patients. Conclusion. These data confirm that the following treponemal tests belong to the most reliable ones for revealing patients suffering from latent syphilis: immune-enzyme assay, passive hemagglutination test and IFabs.

PTSD's latent structure in Malaysian tsunami victims: assessing the newly proposed Dysphoric Arousal model.

Science.gov (United States)

Armour, Cherie; Raudzah Ghazali, Siti; Elklit, Ask

2013-03-30

The underlying latent structure of Posttraumatic Stress Disorder (PTSD) is widely researched. However, despite a plethora of factor analytic studies, no single model has consistently been shown as superior to alternative models. The two most often supported models are the Emotional Numbing and the Dysphoria models. However, a recently proposed five-factor Dysphoric Arousal model has been gathering support over and above existing models. Data for the current study were gathered from Malaysian Tsunami survivors (N=250). Three competing models (Emotional Numbing/Dysphoria/Dysphoric Arousal) were specified and estimated using Confirmatory Factor Analysis (CFA). The Dysphoria model provided superior fit to the data compared to the Emotional Numbing model. However, using chi-square difference tests, the Dysphoric Arousal model showed a superior fit compared to both the Emotional Numbing and Dysphoria models. In conclusion, the current results suggest that the Dysphoric Arousal model better represents PTSD's latent structure and that items measuring sleeping difficulties, irritability/anger and concentration difficulties form a separate, unique PTSD factor. These results are discussed in relation to the role of Hyperarousal in PTSD's on-going symptom maintenance and in relation to the DSM-5. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Endogenous Opioid-Masked Latent Pain Sensitization

DEFF Research Database (Denmark)

Pereira, Manuel P; Donahue, Renee R; Dahl, Jørgen B

2015-01-01

UNLABELLED: Following the resolution of a severe inflammatory injury in rodents, administration of mu-opioid receptor inverse agonists leads to reinstatement of pain hypersensitivity. The mechanisms underlying this form of latent pain sensitization (LS) likely contribute to the development of chr...

Perbandingan Hasil Deteksi Plagiarisme Dokumen dengan Metode Jaro-Winkler Distance dan Metode Latent Semantic Analysis

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Tinaliah Tinaliah

2018-01-01

Full Text Available Various methods are applied in the application of plagiarism detection to help check the similarity of a document. Jaro-Winkler Distance can measure the distance between two strings. However, this method basically depends on the position of the word. Latent Semantic Analysis emphasizes the words contained in the document regardless of its linguistic character. This study compares the results of plagiarism detection using the Jaro-Winkler Distance and the Latent Semantic Analysis method. From comparing results of  Jaro-Winkler Distance method and Latent Semantic Analysis method, Jaro-Winkler Distance method is better than Latent Semantic Analysis method if using the same test data. Jaro-Winkler Distance method will give plagiarism result 100% and Latent Semantic Analysis method will give plagiarism result 97,14%. Beragam metode diterapkan dalam aplikasi deteksi plagiarisme untuk membantu mengecek tingkat kesamaan sebuah dokumen. Metode Jaro-Winkler Distance dapat mengukur kesamaan antara dua buah string dan sangat bergantung pada urutan atau posisi kata. Latent Semantic Analysis mementingkan kata-kata yang terkandung di dalam dokumen tanpa memperhatikan karakter linguistiknya. Penelitian ini melakukan perbandingan hasil deteksi plagiarisme dengan menggunakan metode Jaro-Winkler Distance dan metode Latent Semantic Analysis. Hasil pendeteksian plagiarisme dokumen menggunakan metode Jaro-Winkler Distance memberikan hasil yang lebih baik daripada metode Latent Semantic Analysis, yaitu jika data yang dibandingkan sama persis maka akan menghasilkan nilai plagiat sebesar 100%, sedangkan metode Latent Semantic Analysis menghasilkan nilai plagiat sebesar 97,14%.

Effect of Latent Heat Released by Freezing Droplets during Frost Wave Propagation.

Science.gov (United States)

Chavan, Shreyas; Park, Deokgeun; Singla, Nitish; Sokalski, Peter; Boyina, Kalyan; Miljkovic, Nenad

2018-05-21

Frost spreads on nonwetting surfaces during condensation frosting via an interdroplet frost wave. When a supercooled condensate water droplet freezes on a hydrophobic or superhydrophobic surface, neighboring droplets still in the liquid phase begin to evaporate. Two possible mechanisms govern the evaporation of neighboring water droplets: (1) The difference in saturation pressure of the water vapor surrounding the liquid and frozen droplets induces a vapor pressure gradient, and (2) the latent heat released by freezing droplets locally heats the substrate, leading to evaporation of nearby droplets. The relative significance of these two mechanisms is still not understood. Here, we study the significance of the latent heat released into the substrate by freezing droplets, and its effect on adjacent droplet evaporation, by studying the dynamics of individual water droplet freezing on aluminum-, copper-, and glass-based hydrophobic and superhydrophobic surfaces. The latent heat flux released into the substrate was calculated from the measured droplet sizes and the respective freezing times ( t f ), defined as the time from initial ice nucleation within the droplet to complete droplet freezing. To probe the effect of latent heat release, we performed three-dimensional transient finite element simulations showing that the transfer of latent heat to neighboring droplets is insignificant and accounts for a negligible fraction of evaporation during microscale frost wave propagation. Furthermore, we studied the effect of substrate thermal conductivity on the transfer of latent heat transfer to neighboring droplets by investigating the velocity of ice bridge formation. The velocity of the ice bridge was independent of the substrate thermal conductivity, indicating that adjacent droplet evaporation during condensation frosting is governed solely by vapor pressure gradients. This study not only provides key insights into the individual droplet freezing process but also

New developing reagent for latent fingermark visualization: Fuller’s earth (Multani Mitti

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Pallavi Thakur

2016-12-01

Full Text Available A number of methods have been reported in the literature for the development of latent fingermarks on different surfaces. This paper reports a new and simple powdering method which is non-toxic and has been employed on different substrates successfully for the development and visualization of latent fingermarks up to the time period of 6 days in varying temperature conditions. In this investigation a less expensive, simple and easily available fuller’s earth (Multani Mitti powder has been used to decipher the latent fingermarks on different substrates namely black cardboard box, clear glass, coverslip box, steel surface, laminated wooden sheet, clear plastic, colored plastic bag and surface of highlighter pen. It is observed that it gives very clear results on majority of substrates and can be successfully used for the development and visualization of latent fingermarks.

The latent rationality of risky decisions

Energy Technology Data Exchange (ETDEWEB)

Japp, K.P. [Bielefeld Univ. (Germany). Faculty for Sociology

1999-12-01

The general question of rationality has changed from the old-fashioned difference of means and ends to the modern difference of system and environment. Organizations as social systems producing and reproducing decisions translate this difference into the difference of stability and variety. The question then is: In which way can the difference between stability and variety express rationality? - In the temporal dimension of risk-taking, re-entries may be expressed as 'present futures' or 'future presences'. These expressions indicate both: The irresolvable uncertainty of any risk-taking, indicated by open futures, and its boundedness by self-application of distinctions, e.g. projected futures from the background of a known past. - In the material dimension of risk-taking, re-entries may be expressed as 'stable flexibility' or 'flexible stability'. Again, these expressions indicate both: The irresolvable uncertainty of any risk-taking, indicted by open flexibilities, and its boundedness by self-application of distinctions, e.g. flexibility and stability after learning the respective costs of the single options. In the social dimension of risk-taking, re-entries may be expressed as 'pragmatic dissent' or 'controversial pragmatism'. Again, these expressions indicate both: The irresolvable uncertainty of any risk-taking, indicated by open dissent or controversies, and its boundedness by self-application of distinctions, e.g. pragmatic agreements and irresolvable dissent. Again, all three asymmetries represent re-entries. The built-in preferences simply do not work without the subtleties of re-entries, at least when these processes are described by sociologically informed observers. Who else should know that he or she is operating on the basis of something called re-entries? In everyday life communication, no one sees a thing like that since every observation has an in-built bias for one side of a distinction

The latent rationality of risky decisions

International Nuclear Information System (INIS)

Japp, K.P.

1999-01-01

The general question of rationality has changed from the old-fashioned difference of means and ends to the modern difference of system and environment. Organizations as social systems producing and reproducing decisions translate this difference into the difference of stability and variety. The question then is: In which way can the difference between stability and variety express rationality? - In the temporal dimension of risk-taking, re-entries may be expressed as 'present futures' or 'future presences'. These expressions indicate both: The irresolvable uncertainty of any risk-taking, indicated by open futures, and its boundedness by self-application of distinctions, e.g. projected futures from the background of a known past. - In the material dimension of risk-taking, re-entries may be expressed as 'stable flexibility' or 'flexible stability'. Again, these expressions indicate both: The irresolvable uncertainty of any risk-taking, indicted by open flexibilities, and its boundedness by self-application of distinctions, e.g. flexibility and stability after learning the respective costs of the single options. In the social dimension of risk-taking, re-entries may be expressed as 'pragmatic dissent' or 'controversial pragmatism'. Again, these expressions indicate both: The irresolvable uncertainty of any risk-taking, indicated by open dissent or controversies, and its boundedness by self-application of distinctions, e.g. pragmatic agreements and irresolvable dissent. Again, all three asymmetries represent re-entries. The built-in preferences simply do not work without the subtleties of re-entries, at least when these processes are described by sociologically informed observers. Who else should know that he or she is operating on the basis of something called re-entries? In everyday life communication, no one sees a thing like that since every observation has an in-built bias for one side of a distinction. So rationality will stay latent as the operation of re

Structure of health-enhancing behavior in adolescence: a latent-variable approach.

Science.gov (United States)

Donovan, J E; Jessor, R; Costa, F M

1993-12-01

The structure of the interrelations among a variety of health-enhancing behaviors was examined using structural equation modeling analyses of questionnaire data from 1,280 middle school students and 2,219 high school students. The health-enhancing behaviors included seat belt use, adequate hours of sleep, attention to healthy diet, adequate exercise, low sedentary behavior, and regular toothbrushing. In the middle school sample, all of the health-enhancing behaviors correlated significantly but modestly with each other, except for sleep with toothbrushing. In the high school sample, all but three of the 15 correlations among the behaviors were significant. The results further show that a single underlying factor can account for the modest correlations among these health-enhancing behaviors in both samples. The generality of the single-factor model was also established for male, female, White, Hispanic, and Black students at each school level. These findings provide some support for the existence of health-related lifestyles in adolescence.

Accidental cloning of a single-photon qubit in two-channel continuous-variable quantum teleportation

International Nuclear Information System (INIS)

Ide, Toshiki; Hofmann, Holger F.

2007-01-01

The information encoded in the polarization of a single photon can be transferred to a remote location by two-channel continuous-variable quantum teleportation. However, the finite entanglement used in the teleportation causes random changes in photon number. If more than one photon appears in the output, the continuous-variable teleportation accidentally produces clones of the original input photon. In this paper, we derive the polarization statistics of the N-photon output components and show that they can be decomposed into an optimal cloning term and completely unpolarized noise. We find that the accidental cloning of the input photon is nearly optimal at experimentally feasible squeezing levels, indicating that the loss of polarization information is partially compensated by the availability of clones

Maximum generation power evaluation of variable frequency offshore wind farms when connected to a single power converter

Energy Technology Data Exchange (ETDEWEB)

Gomis-Bellmunt, Oriol; Sumper, Andreas [Centre d' Innovacio Tecnologica en Convertidors Estatics i Accionaments (CITCEA-UPC), Universitat Politecnica de Catalunya UPC, Av. Diagonal, 647, Pl. 2, 08028 Barcelona (Spain); IREC Catalonia Institute for Energy Research, Barcelona (Spain); Junyent-Ferre, Adria; Galceran-Arellano, Samuel [Centre d' Innovacio Tecnologica en Convertidors Estatics i Accionaments (CITCEA-UPC), Universitat Politecnica de Catalunya UPC, Av. Diagonal, 647, Pl. 2, 08028 Barcelona (Spain)

2010-10-15

The paper deals with the evaluation of power generated by variable and constant frequency offshore wind farms connected to a single large power converter. A methodology to analyze different wind speed scenarios and system electrical frequencies is presented and applied to a case study, where it is shown that the variable frequency wind farm concept (VF) with a single power converter obtains 92% of the total available power, obtained with individual power converters in each wind turbine (PC). The PC scheme needs multiple power converters implying drawbacks in terms of cost, maintenance and reliability. The VF scheme is also compared to a constant frequency scheme CF, and it is shown that a significant power increase of more than 20% can be obtained with VF. The case study considers a wind farm composed of four wind turbines based on synchronous generators. (author)

The efficiency of parameter estimation of latent path analysis using summated rating scale (SRS) and method of successive interval (MSI) for transformation of score to scale

Science.gov (United States)

Solimun, Fernandes, Adji Achmad Rinaldo; Arisoesilaningsih, Endang

2017-12-01

Research in various fields generally investigates systems and involves latent variables. One method to analyze the model representing the system is path analysis. The data of latent variables measured using questionnaires by applying attitude scale model yields data in the form of score, before analyzed should be transformation so that it becomes data of scale. Path coefficient, is parameter estimator, calculated from scale data using method of successive interval (MSI) and summated rating scale (SRS). In this research will be identifying which data transformation method is better. Path coefficients have smaller varieties are said to be more efficient. The transformation method that produces scaled data and used in path analysis capable of producing path coefficients (parameter estimators) with smaller varieties is said to be better. The result of analysis using real data shows that on the influence of Attitude variable to Intention Entrepreneurship, has relative efficiency (ER) = 1, where it shows that the result of analysis using data transformation of MSI and SRS as efficient. On the other hand, for simulation data, at high correlation between items (0.7-0.9), MSI method is more efficient 1.3 times better than SRS method.

Variation in Latent Classes of Adult Attention-Deficit Hyperactivity Disorder by Sex and Environmental Adversity.

Science.gov (United States)

Ebejer, Jane L; Medland, Sarah E; van der Werf, Julius; Lynskey, Michael; Martin, Nicholas G; Duffy, David L

2016-11-01

The findings of genetic, imaging and neuropsychological studies of attention-deficit hyperactivity disorder (ADHD) are mixed. To understand why this might be the case we use both dimensional and categorical symptom measurement to provide alternate and detailed perspectives of symptom expression. Interviewers collected ADHD, conduct problems (CP) and sociodemographic data from 3793 twins and their siblings aged 22 to 49 (M = 32.6). We estimate linear weighting of symptoms across ADHD and CP items. Latent class analyses and regression describe associations between measured variables, environmental risk factors and subsequent disadvantage. Additionally, the clinical relevance of each class was estimated. Five classes were found for women and men; few symptoms, hyperactive-impulsive, CP, inattentive, combined symptoms with CP. Women within the inattentive class reported more symptoms and reduced emotional health when compared to men and to women within other latent classes. Women and men with combined ADHD symptoms reported comorbid conduct problems but those with either inattention or hyperactivity-impulsivity only did not. The dual perspective of dimensional and categorical measurement of ADHD provides important detail about symptom variation across sex and with environmental covariates. © The Author(s) 2013.

Multiplex real-time PCR for the detection and quantification of latent and persistent viral genomes in cellular or plasma blood fractions.

Science.gov (United States)

Compston, Lara Isobel; Sarkobie, Francis; Li, Chengyao; Candotti, Daniel; Opare-Sem, Ohene; Allain, Jean-Pierre

2008-07-01

In common with latent viruses such as herpesviruses, parvovirus B19, HBV and GBV-C are contained successfully by the immune response and persist in the host. When immune control breaks down, reactivation of both latent and persistent viruses occurs. Two multiplex assays were developed (B19, HBV, HHV-8), (EBV, CMV, VZV) for blood screening, and tested on blood donor samples from Ghana to determine baseline prevalence of viraemia in immunocompetent persons. Single-virus real-time quantitative PCR (qPCR) assays were optimised for viral load determination of positive initial screening. The qPCR method utilised was absolute quantification with external standards. Multiplex and single-virus qPCR assays had similar sensitivity, except for the B19 assay in which sensitivity was 100-fold lower. Assays were optimised for reproducibility and repeatability, with R(2) of 0.9 being obtained for most assays. With the exception of B19 and CMV, assays had 100% detection limit ranging between 10(1) and 10(2) copies, IU or arbitrary units under single-virus and multiplex assay conditions. The prevalence of viraemia was 1.6% HBV (0.8% DNA+/HBsAg-, 0.8% DNA+/HBsAg+), 0.8% parvovirus B19, and 3.3% GBV-C viraemia in the plasma fraction. The prevalence of four herpesviruses was 1.0% HHV-8, 0.85% CMV, and 8.3% EBV, and no detectable VZV viraemia.

A Cell Culture Model of Latent and Lytic Herpes Simplex Virus Type 1 Infection in Spiral Ganglion.

Science.gov (United States)

Liu, Yuehong; Li, Shufeng

2015-01-01

Reactivation of latent herpes simplex virus type 1 (HSV-1) in spiral ganglion neurons (SGNs) is supposed to be one of the causes of idiopathic sudden sensorineural hearing loss. This study aims to establish a cell culture model of latent and lytic HSV-1 infection in spiral ganglia. In the presence of acyclovir, primary cultures of SGNs were latently infected with HSV-1 expressing green fluorescent protein. Four days later, these cells were treated with trichostatin A (TSA), a known chemical reactivator of HSV-1. TCID50 was used to measure the titers of virus in cultures on Vero cells. RNA from cultures was detected for the presence of transcripts of ICP27 and latency-associated transcript (LAT) using reverse transcription polymerase chain reaction. There is no detectable infectious HSV-1 in latently infected cultures, whereas they could be observed in both lytically infected and latently infected/TSA-treated cultures. LAT was the only detectable transcript during latent infection, whereas lytic ICP27 transcript was detected in lytically infected and latently infected/TSA-treated cultures. Cultured SGNs can be both latently and lytically infected with HSV-1. Furthermore, latently infected SGNs can be reactivated using TSA, yielding infectious virus.

The Latent Class Model as a Measurement Model for Situational Judgment Tests

Directory of Open Access Journals (Sweden)

Frank Rijmen

2011-11-01

Full Text Available In a situational judgment test, it is often debatable what constitutes a correct answer to a situation. There is currently a multitude of scoring procedures. Establishing a measurement model can guide the selection of a scoring rule. It is argued that the latent class model is a good candidate for a measurement model. Two latent class models are applied to the Managing Emotions subtest of the Mayer, Salovey, Caruso Emotional Intelligence Test: a plain-vanilla latent class model, and a second-order latent class model that takes into account the clustering of several possible reactions within each hypothetical scenario of the situational judgment test. The results for both models indicated that there were three subgroups characterised by the degree to which differentiation occurred between possible reactions in terms of perceived effectiveness. Furthermore, the results for the second-order model indicated a moderate cluster effect.

Natural Language Search Interfaces: Health Data Needs Single-Field Variable Search

Science.gov (United States)

Smith, Sam; Sufi, Shoaib; Goble, Carole; Buchan, Iain

2016-01-01

Background Data discovery, particularly the discovery of key variables and their inter-relationships, is key to secondary data analysis, and in-turn, the evolving field of data science. Interface designers have presumed that their users are domain experts, and so they have provided complex interfaces to support these “experts.” Such interfaces hark back to a time when searches needed to be accurate first time as there was a high computational cost associated with each search. Our work is part of a governmental research initiative between the medical and social research funding bodies to improve the use of social data in medical research. Objective The cross-disciplinary nature of data science can make no assumptions regarding the domain expertise of a particular scientist, whose interests may intersect multiple domains. Here we consider the common requirement for scientists to seek archived data for secondary analysis. This has more in common with search needs of the “Google generation” than with their single-domain, single-tool forebears. Our study compares a Google-like interface with traditional ways of searching for noncomplex health data in a data archive. Methods Two user interfaces are evaluated for the same set of tasks in extracting data from surveys stored in the UK Data Archive (UKDA). One interface, Web search, is “Google-like,” enabling users to browse, search for, and view metadata about study variables, whereas the other, traditional search, has standard multioption user interface. Results Using a comprehensive set of tasks with 20 volunteers, we found that the Web search interface met data discovery needs and expectations better than the traditional search. A task × interface repeated measures analysis showed a main effect indicating that answers found through the Web search interface were more likely to be correct (F 1,19=37.3, Peffect of task (F 3,57=6.3, Pinterface (F 1,19=18.0, Peffect of task (F 2,38=4.1, P=.025, Greenhouse

Prevalence of latent Mycobacterium tuberculosis infection among professionals of the primary healthcare network

Directory of Open Access Journals (Sweden)

Tássia Silvana Borges

2014-06-01

Full Text Available Objective: To estimate the prevalence of latent M. tuberculosis infection and identify characteristics related to latent infection among workers of the primary healthcare network.Methods: Cross-sectional, observational and descriptive study, conducted in 2011, included 137 basic health workers who performed their activities in a municipality. Interviews were carried out addressing characteristics of exposure at work (BCG vaccination, length of time working in the health system, potential exposure to tuberculosis, HIV infection, use of corticosteroids, diabetes, use of tobacco or alcohol and subsequently performed tuberculin skin test (TST. Data was analyzed with Fischer and Student’s t-test (p < 0.05. Results: Health professionals were mostly women (n=126, 92% with mean age of 35.3 (± 9.1 years. Among the reactors, 25 (55.5% sought medical care, and of these, 7 (28% underwent prophylactic treatment. The prevalence of latent tuberculosis was 32.8%. Of the characteristics evaluated, only smoking (OR 3.03; 95%CI 1.05-8.77 was associated with latent infection. Conclusion: The estimated prevalence of latent M. tuberculosis infection among the evaluated health workers was 32.8%. As for the characteristics studied, it was not possible to relate them to latent infection among workers in primary healthcare network, with the exception of the smoking habit. doi: 10.5020/18061230.2014.p269

Variations in Care Quality Outcomes of Dying People: Latent Class Analysis of an Adult National Register Population.

Science.gov (United States)

Öhlén, Joakim; Russell, Lara; Håkanson, Cecilia; Alvariza, Anette; Fürst, Carl Johan; Årestedt, Kristofer; Sawatzky, Richard

2017-01-01

Symptom relief is a key goal of palliative care. There is a need to consider complexities in symptom relief patterns for groups of people to understand and evaluate symptom relief as an indicator of quality of care at end of life. The aims of this study were to distinguish classes of patients who have different symptom relief patterns during the last week of life and to identify predictors of these classes in an adult register population. In a cross-sectional retrospective design, data were used from 87,026 decedents with expected deaths registered in the Swedish Register of Palliative Care in 2011 and 2012. Study variables were structured into patient characteristics, and processes and outcomes of quality of care. A latent class analysis was used to identify symptom relief patterns. Multivariate multinomial regression analyses were used to identify predictors of class membership. Five latent classes were generated: "relieved pain," "relieved pain and rattles," "relieved pain and anxiety," "partly relieved shortness of breath, rattles and anxiety," and "partly relieved pain, anxiety and confusion." Important predictors of class membership were age, sex, cause of death, and having someone present at death, individual prescriptions as needed (PRN) and expert consultations. Interindividual variability and complexity in symptom relief patterns may inform quality of care and its evaluation for dying people across care settings. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Latent class analysis of early developmental trajectory in baby siblings of children with autism.

Science.gov (United States)

Landa, Rebecca J; Gross, Alden L; Stuart, Elizabeth A; Bauman, Margaret

2012-09-01

Siblings of children with autism (sibs-A) are at increased genetic risk for autism spectrum disorders (ASD) and milder impairments. To elucidate diversity and contour of early developmental trajectories exhibited by sibs-A, regardless of diagnostic classification, latent class modeling was used. Sibs-A (N = 204) were assessed with the Mullen Scales of Early Learning from age 6 to 36 months. Mullen T scores served as dependent variables. Outcome classifications at age 36 months included: ASD (N = 52); non-ASD social/communication delay (broader autism phenotype; BAP; N = 31); and unaffected (N = 121). Child-specific patterns of performance were studied using latent class growth analysis. Latent class membership was then related to diagnostic outcome through estimation of within-class proportions of children assigned to each diagnostic classification. A 4-class model was favored. Class 1 represented accelerated development and consisted of 25.7% of the sample, primarily unaffected children. Class 2 (40.0% of the sample), was characterized by normative development with above-average nonverbal cognitive outcome. Class 3 (22.3% of the sample) was characterized by receptive language, and gross and fine motor delay. Class 4 (12.0% of the sample), was characterized by widespread delayed skill acquisition, reflected by declining trajectories. Children with an outcome diagnosis of ASD were spread across Classes 2, 3, and 4. Results support a category of ASD that involves slowing in early non-social development. Receptive language and motor development is vulnerable to early delay in sibs-A with and without ASD outcomes. Non-ASD sibs-A are largely distributed across classes depicting average or accelerated development. Developmental trajectories of motor, language, and cognition appear independent of communication and social delays in non-ASD sibs-A. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.

Evaluation of HIV Risk Reduction and Intervention Programs via Latent Growth Model.

Science.gov (United States)

Wang, Jichuan; Siegal, Harvey A.; Falck, Russel S.; Carlson, Robert G.; Rahman, Ahmmed

1999-01-01

Demonstrates how the latent growth model can be applied to the evaluation of programs targeting HIV risk behavior among drug users. Multigroup piecewise latent growth models were fit to longitudinal data with three repeated response measures. Participants were 430 drug users and their sex partners. (SLD)

Full Text or Abstract? : Examining Topic Coherence Scores Using Latent Dirichlet Allocation

NARCIS (Netherlands)

Syed, S.; Spruit, M.

2017-01-01

This paper assesses topic coherence and human topic ranking of uncovered latent topics from scientific publications when utilizing the topic model latent Dirichlet allocation (LDA) on abstract and full-text data. The coherence of a topic, used as a proxy for topic quality, is based on the

Microbeam mapping of single event latchups and single event upsets in CMOS SRAMs

International Nuclear Information System (INIS)

Barak, J.; Adler, E.; Fischer, B.E.; Schloegl, M.; Metzger, S.

1998-01-01

The first simultaneous microbeam mapping of single event upset (SEU) and latchup (SEL) in the CMOS RAM HM65162 is presented. The authors found that the shapes of the sensitive areas depend on V DD , on the ions being used and on the site on the chip being hit by the ion. In particular, they found SEL sensitive sites close to the main power supply lines between the memory-bit-arrays by detecting the accompanying current surge. All these SELs were also accompanied by bit-flips elsewhere in the memory (which they call indirect SEUs in contrast to the well known SEUs induced in the hit memory cell only). When identical SEL sensitive sites were hit farther away from the supply lines only indirect SEL sensitive sites could be detected. They interpret these events as latent latchups in contrast to the classical ones detected by their induced current surge. These latent SELs were probably decoupled from the main supply lines by the high resistivity of the local supply lines

The Latent Structure of Attention Deficit/Hyperactivity Disorder in an Adult Sample

Science.gov (United States)

Marcus, David K.; Norris, Alyssa L.; Coccaro, Emil F.

2012-01-01

The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. PMID:22480749

The latent structure of attention deficit/hyperactivity disorder in an adult sample.

Science.gov (United States)

Marcus, David K; Norris, Alyssa L; Coccaro, Emil F

2012-06-01

The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. Copyright © 2012 Elsevier Ltd. All rights reserved.

New Treatment Regimen for Latent Tuberculosis Infection

Centers for Disease Control (CDC) Podcasts

In this podcast, Dr. Kenneth Castro, Director of the Division of Tuberculosis Elimination, discusses the December 9, 2011 CDC guidelines for the use of a new regimen for the treatment of persons with latent tuberculosis infection.

Single-quadrature continuous-variable quantum key distribution

DEFF Research Database (Denmark)

Gehring, Tobias; Jacobsen, Christian Scheffmann; Andersen, Ulrik Lund

2016-01-01

Most continuous-variable quantum key distribution schemes are based on the Gaussian modulation of coherent states followed by continuous quadrature detection using homodyne detectors. In all previous schemes, the Gaussian modulation has been carried out in conjugate quadratures thus requiring two...... commercialization of continuous-variable quantum key distribution, provided that the low noise requirement can be achieved....

Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches.

Science.gov (United States)

Yang, Jun-Ho; Yoh, Jack J

2018-01-01

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

Anxiety, bulimia, drug and alcohol addiction, depression, and schizophrenia: what do you think about their aetiology, dangerousness, social distance, and treatment? A latent class analysis approach.

Science.gov (United States)

Mannarini, Stefania; Boffo, Marilisa

2015-01-01

Mental illness stigma is a serious societal problem and a critical impediment to treatment seeking for mentally ill people. To improve the understanding of mental illness stigma, this study focuses on the simultaneous analysis of people's aetiological beliefs, attitudes (i.e. perceived dangerousness and social distance), and recommended treatments related to several mental disorders by devising an over-arching latent structure that could explain the relations among these variables. Three hundred and sixty university students randomly received an unlabelled vignette depicting one of six mental disorders to be evaluated on the four variables on a Likert-type scale. A one-factor Latent Class Analysis (LCA) model was hypothesized, which comprised the four manifest variables as indicators and the mental disorder as external variable. The main findings were the following: (a) a one-factor LCA model was retrieved; (b) alcohol and drug addictions are the most strongly stigmatized; (c) a realistic opinion about the causes and treatment of schizophrenia, anxiety, bulimia, and depression was associated to lower prejudicial attitudes and social rejection. Beyond the general appraisal of mental illness an individual might have, the results generally point to the acknowledgement of the specific features of different diagnostic categories. The implications of the present results are discussed in the framework of a better understanding of mental illness stigma.

Reward devaluation disrupts latent inhibition in fear conditioning.

Science.gov (United States)

De la Casa, Luís Gonzalo; Mena, Auxiliadora; Ruiz-Salas, Juán Carlos; Quintero, Esperanza; Papini, Mauricio R

2018-03-01

Three experiments explored the link between reward shifts and latent inhibition (LI). Using consummatory procedures, rewards were either downshifted from 32% to 4% sucrose (Experiments 1-2), or upshifted from 4% to 32% sucrose (Experiment 3). In both cases, appropriate unshifted controls were also included. LI was implemented in terms of fear conditioning involving a single tone-shock pairing after extensive tone-only preexposure. Nonpreexposed controls were also included. Experiment 1 demonstrated a typical LI effect (i.e., disruption of fear conditioning after preexposure to the tone) in animals previously exposed only to 4% sucrose. However, the LI effect was eliminated by preexposure to a 32%-to-4% sucrose devaluation. Experiment 2 replicated this effect when the LI protocol was administered immediately after the reward devaluation event. However, LI was restored when preexposure was administered after a 60-min retention interval. Finally, Experiment 3 showed that a reward upshift did not affect LI. These results point to a significant role of negative emotion related to reward devaluation in the enhancement of stimulus processing despite extensive nonreinforced preexposure experience.

Intraclass Correlation Coefficients in Hierarchical Design Studies with Discrete Response Variables: A Note on a Direct Interval Estimation Procedure

Science.gov (United States)

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling procedure that can be used to evaluate intraclass correlation coefficients in two-level settings with discrete response variables is discussed. The approach is readily applied when the purpose is to furnish confidence intervals at prespecified confidence levels for these coefficients in setups with binary or ordinal…

Space-time latent component Modeling of Geo-referenced health data

OpenAIRE

Lawson, Andrew B.; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

2010-01-01

Latent structure models have been proposed in many applications. For space time health data it is often important to be able to find underlying trends in time which are supported by subsets of small areas. Latent structure modeling is one approach to this analysis. This paper presents a mixture-based approach that can be appied to component selction. The analysis of a Georgia ambulatory asthma county level data set is presented and a simulation-based evaluation is made.

Translating latent trends in food consumer behavior into new products

OpenAIRE

Gellynck, Xavier; Kühne, Bianka; Van Wezemael, Lynn; Verbeke, Wim

2010-01-01

For successful product development it is important to explore the latent changes in consumer behavior prior to the product development process. The identification of a latent trend before the manifestation moment can be achieved by trend analysis. Trend analysis delivers insights that explore the future in order to identify prospective consumers and new product ideas, but also includes a feeling for the currents in market and technology. Hence, the aim is to identify emerging weak signals in ...

Perceptions of care in women sent home in latent labor.

Science.gov (United States)

Hosek, Claire; Faucher, Mary Ann; Lankford, Janice; Alexander, James

2014-01-01

To assess perceptions of care from woman discharged from an obstetrical (OB) triage unit or a labor and delivery unit with a diagnosis of false or latent labor in order to determine factors that may increase or decrease the woman's satisfaction with care. Descriptive, convenience sample. One hundred low-income pregnant women at term presenting for care in latent labor consented to participate in a telephone survey. The survey was based on the relevant research about care of women in early labor and the Donabedian quality improvement framework assessing structure, process, and outcomes of care. Forty-one percent of women did not want to be discharged home in latent labor. Common reasons included women stating they were in too much pain or they were living too far from the birth setting. Eating, drinking, and comfort measures were the most common measures women cited that would have made them feel better when in the hospital. A reoccurring response from women was their desire for very clear and specific written instructions about how to stay comfortable at home and when to return to the hospital. Comfort measures in the birth setting, including in triage, should include a variety of options including ambulation and oral nutrition. Detailed and specific written instructions about early labor and staying comfortable while at home have value for women in this survey regarding their perceptions of care. Results from this survey of low-income women suggest that a subset of women in latent labor just do not want to go home and this may be related to having too much pain and/or travel distance to the hospital. Hospital birth settings also have an opportunity to create a care environment that provides services and embodies attributes that women report as important for their satisfaction with care in latent labor.

Identifying Predictors of Interferon-γ Release Assay Results in Pediatric Latent Tuberculosis: A Protective Role of Bacillus Calmette-Guérin?

Science.gov (United States)

Sotgiu, Giovanni; Altet-Gómez, Neus; Tsolia, Maria; Ruga, Ezia; Velizarova, Svetlana; Kampmann, Beate

2012-01-01

Rationale: Interferon-γ (IFN-γ) release assays are widely used to diagnose latent infection with Mycobacterium tuberculosis in adults, but their performance in children remains incompletely evaluated to date. Objectives: To investigate factors influencing results of IFN-γ release assays in children using a large European data set. Methods: The Pediatric Tuberculosis Network European Trials group pooled and analyzed data from five sites across Europe comprising 1,128 children who were all investigated for latent tuberculosis infection by tuberculin skin test and at least one IFN-γ release assay. Multivariate analyses examined age, bacillus Calmette-Guérin (BCG) vaccination status, and sex as predictor variables of results. Subgroup analyses included children who were household contacts. Measurements and Main Results: A total of 1,093 children had a QuantiFERON-TB Gold In-Tube assay and 382 had a T-SPOT.TB IFN-γ release assay. Age was positively correlated with a positive blood result (QuantiFERON-TB Gold In-Tube: odds ratio [OR], 1.08 per year increasing age [P 5 yr). Conclusions: Our data show that BCG vaccination may be effective in protecting children against Mycobacterium tuberculosis infection. To restrict use of IFN-γ release assays to children with positive skin tests risks underestimating latent infection. PMID:22700862

Systematic identification of latent disease-gene associations from PubMed articles.

Science.gov (United States)

Zhang, Yuji; Shen, Feichen; Mojarad, Majid Rastegar; Li, Dingcheng; Liu, Sijia; Tao, Cui; Yu, Yue; Liu, Hongfang

2018-01-01

Recent scientific advances have accumulated a tremendous amount of biomedical knowledge providing novel insights into the relationship between molecular and cellular processes and diseases. Literature mining is one of the commonly used methods to retrieve and extract information from scientific publications for understanding these associations. However, due to large data volume and complicated associations with noises, the interpretability of such association data for semantic knowledge discovery is challenging. In this study, we describe an integrative computational framework aiming to expedite the discovery of latent disease mechanisms by dissecting 146,245 disease-gene associations from over 25 million of PubMed indexed articles. We take advantage of both Latent Dirichlet Allocation (LDA) modeling and network-based analysis for their capabilities of detecting latent associations and reducing noises for large volume data respectively. Our results demonstrate that (1) the LDA-based modeling is able to group similar diseases into disease topics; (2) the disease-specific association networks follow the scale-free network property; (3) certain subnetwork patterns were enriched in the disease-specific association networks; and (4) genes were enriched in topic-specific biological processes. Our approach offers promising opportunities for latent disease-gene knowledge discovery in biomedical research.

Non-destructive forensic latent fingerprint acquisition with chromatic white light sensors

Science.gov (United States)

Leich, Marcus; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus

2011-02-01

Non-destructive latent fingerprint acquisition is an emerging field of research, which, unlike traditional methods, makes latent fingerprints available for additional verification or further analysis like tests for substance abuse or age estimation. In this paper a series of tests is performed to investigate the overall suitability of a high resolution off-the-shelf chromatic white light sensor for the contact-less and non-destructive latent fingerprint acquisition. Our paper focuses on scanning previously determined regions with exemplary acquisition parameter settings. 3D height field and reflection data of five different latent fingerprints on six different types of surfaces (HDD platter, brushed metal, painted car body (metallic and non-metallic finish), blued metal, veneered plywood) are experimentally studied. Pre-processing is performed by removing low-frequency gradients. The quality of the results is assessed subjectively; no automated feature extraction is performed. Additionally, the degradation of the fingerprint during the acquisition period is observed. While the quality of the acquired data is highly dependent on surface structure, the sensor is capable of detecting the fingerprint on all sample surfaces. On blued metal the residual material is detected; however, the ridge line structure dissolves within minutes after fingerprint placement.

Reactivation of Latent HIV-1 Expression by Engineered TALE Transcription Factors.

Science.gov (United States)

Perdigão, Pedro; Gaj, Thomas; Santa-Marta, Mariana; Barbas, Carlos F; Goncalves, Joao

2016-01-01

The presence of replication-competent HIV-1 -which resides mainly in resting CD4+ T cells--is a major hurdle to its eradication. While pharmacological approaches have been useful for inducing the expression of this latent population of virus, they have been unable to purge HIV-1 from all its reservoirs. Additionally, many of these strategies have been associated with adverse effects, underscoring the need for alternative approaches capable of reactivating viral expression. Here we show that engineered transcriptional modulators based on customizable transcription activator-like effector (TALE) proteins can induce gene expression from the HIV-1 long terminal repeat promoter, and that combinations of TALE transcription factors can synergistically reactivate latent viral expression in cell line models of HIV-1 latency. We further show that complementing TALE transcription factors with Vorinostat, a histone deacetylase inhibitor, enhances HIV-1 expression in latency models. Collectively, these findings demonstrate that TALE transcription factors are a potentially effective alternative to current pharmacological routes for reactivating latent virus and that combining synthetic transcriptional activators with histone deacetylase inhibitors could lead to the development of improved therapies for latent HIV-1 infection.

Reactivation of Latent HIV-1 Expression by Engineered TALE Transcription Factors.

Directory of Open Access Journals (Sweden)

Pedro Perdigão

Full Text Available The presence of replication-competent HIV-1 -which resides mainly in resting CD4+ T cells--is a major hurdle to its eradication. While pharmacological approaches have been useful for inducing the expression of this latent population of virus, they have been unable to purge HIV-1 from all its reservoirs. Additionally, many of these strategies have been associated with adverse effects, underscoring the need for alternative approaches capable of reactivating viral expression. Here we show that engineered transcriptional modulators based on customizable transcription activator-like effector (TALE proteins can induce gene expression from the HIV-1 long terminal repeat promoter, and that combinations of TALE transcription factors can synergistically reactivate latent viral expression in cell line models of HIV-1 latency. We further show that complementing TALE transcription factors with Vorinostat, a histone deacetylase inhibitor, enhances HIV-1 expression in latency models. Collectively, these findings demonstrate that TALE transcription factors are a potentially effective alternative to current pharmacological routes for reactivating latent virus and that combining synthetic transcriptional activators with histone deacetylase inhibitors could lead to the development of improved therapies for latent HIV-1 infection.

Latent Heat Storage Through Phase Change Materials

Indian Academy of Sciences (India)

IAS Admin

reducing storage volume for different materials. The examples are numerous: ... Latent heat is an attractive way to store solar heat as it provides high energy storage density, .... Maintenance of the PCM treated fabric is easy. The melted PCM.

Stress-induced light scattering method for the detection of latent flaws on fine polished glass substrates.

Science.gov (United States)

Sakata, Y; Sakai, K; Nonaka, K

2014-08-01

Fine polishing techniques, such as the chemical mechanical polishing treatment, are one of the most important technique to glass substrate manufacturing. Mechanical interaction in the form of friction occurs between the abrasive and the substrate surface during polishing, which may cause formation of latent flaws on the glass substrate surface. Fine polishing-induced latent flaws may become obvious during a subsequent cleaning process if glass surfaces are corroded away by chemical interaction with the cleaning liquid. Latent flaws thus reduce product yield. In general, non-destructive inspection techniques, such as the light-scattering methods, used to detect foreign matters on the glass substrate surface. However, it is difficult to detect latent flaws by these methods because the flaws remain closed. Authors propose a novel inspection technique for fine polishing-induced latent flaws by combining the light scattering method with stress effects, referred to as the stress-induced light scattering method (SILSM). SILSM is able to distinguish between latent flaws and particles on the surface. In this method, samples are deformed by an actuator and stress effects are induced around the tips of latent flaws. Due to the photoelastic effect, the refractive index of the material around the tip of a latent flaw is changed. This changed refractive index is in turn detected by a cooled charge-coupled device camera as variations in light scattering intensity. In this report, surface latent flaws are detected non-destructively by applying SILSM to glass substrates, and the utility of SILSM evaluated as a novel inspection technique.

Prevalence of latent alpha-herpesviruses in Thoroughbred racing horses.

Science.gov (United States)

Pusterla, Nicola; Mapes, Samantha; David Wilson, W

2012-08-01

The objective of this study was to detect and characterize latent equine herpes virus (EHV)-1 and -4 from the submandibular (SMLN) and bronchial lymph (BLN) nodes, as well as from the trigeminal ganglia (TG) of 70 racing Thoroughbred horses submitted for necropsy following sustaining serious musculoskeletal injuries while racing. A combination of nucleic acid precipitation and pre-amplification steps was used to increase analytical sensitivity. Tissues were deemed positive for latent EHV-1 and/or -4 infection when found PCR positive for the corresponding glycoprotein B (gB) gene in the absence of detectable late structural protein gene (gB gene) mRNA. The EHV-1 genotype was also determined using a discriminatory real-time PCR assay targeting the DNA polymerase gene (ORF 30). Eighteen (25.7%) and 58 (82.8%) horses were PCR positive for the gB gene of EHV-1 and -4, respectively, in at least one of the three tissues sampled. Twelve horses were dually infected with EHV-1 and -4, two carried a latent neurotropic strain of EHV-1, six carried a non-neurotropic genotype of EHV-1 and 10 were dually infected with neurotropic and non-neurotropic EHV-1. The distribution of latent EHV-1 and -4 infection varied in the samples, with the TG found to be most commonly infected. Overall, non-neurotropic strains were more frequently detected than neurotropic strains, supporting the general consensus that non-neurotropic strains are more prevalent in horse populations, and hence the uncommon occurrence of equine herpes myeloencephalopathy. Copyright © 2012 Elsevier Ltd. All rights reserved.

Climate forcing and response to idealized changes in surface latent and sensible heat

International Nuclear Information System (INIS)

Ban-Weiss, George A; Cao Long; Pongratz, Julia; Caldeira, Ken; Bala, Govindasamy

2011-01-01

Land use and land cover changes affect the partitioning of latent and sensible heat, which impacts the broader climate system. Increased latent heat flux to the atmosphere has a local cooling influence known as 'evaporative cooling', but this energy will be released back to the atmosphere wherever the water condenses. However, the extent to which local evaporative cooling provides a global cooling influence has not been well characterized. Here, we perform a highly idealized set of climate model simulations aimed at understanding the effects that changes in the balance between surface sensible and latent heating have on the global climate system. We find that globally adding a uniform 1 W m -2 source of latent heat flux along with a uniform 1 W m -2 sink of sensible heat leads to a decrease in global mean surface air temperature of 0.54 ± 0.04 K. This occurs largely as a consequence of planetary albedo increases associated with an increase in low elevation cloudiness caused by increased evaporation. Thus, our model results indicate that, on average, when latent heating replaces sensible heating, global, and not merely local, surface temperatures decrease.

Transcriptional regulation of latent feline immunodeficiency virus in peripheral CD4+ T-lymphocytes.

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McDonnel, Samantha J; Sparger, Ellen E; Luciw, Paul A; Murphy, Brian G

2012-05-01

Feline immunodeficiency virus (FIV), the lentivirus of domestic cats responsible for feline AIDS, establishes a latent infection in peripheral blood CD4+ T-cells approximately eight months after experimental inoculation. In this study, cats experimentally infected with the FIV-C strain in the asymptomatic phase demonstrated an estimated viral load of 1 infected cell per approximately 10(3) CD4+ T-cells, with about 1 copy of viral DNA per cell. Approximately 1 in 10 proviral copies was capable of transcription in the asymptomatic phase. The latent FIV proviral promoter was associated with deacetylated, methylated histones, which is consistent with a condensed chromatin structure. In contrast, the transcriptionally active FIV promoter was associated with histone acetylation and demethylation. In addition, RNA polymerase II appeared to be paused on the latent viral promoter, and short promoter-proximal transcripts were detected. Our findings for the FIV promoter in infected cats are similar to results obtained in studies of human immunodeficiency virus (HIV)-1 latent proviruses in cell culture in vitro studies. Thus, the FIV/cat model may offer insights into in vivo mechanisms of HIV latency and provides a unique opportunity to test novel therapeutic interventions aimed at eradicating latent virus.

Relevance and acceptability of using the Quantiferon gold test (QGIT) to screen CD4 blood draws for latent TB infection among PLHIV in South Africa: formative qualitative research findings from the TEKO trial.

Science.gov (United States)

Kerrigan, Deanna; Tudor, Carrie; Motlhaoleng, Katlego; Lebina, Limakatso; Qomfu, Cokiswa; Variava, Ebrahim; Chon, Sandy; Martinson, Neil; Golub, Jonathan E

2018-04-16

Tuberculosis (TB) is the leading cause of mortality among people living with HIV (PLHIV), despite the availability of effective preventive therapy. The TEKO trial is assessing the impact of using a blood test, Quantiferon-TB Gold In-Tube Test (QGIT), to screen for latent TB compared to the Tuberculin Screening Test (TST) among PLHIV in South Africa. Fifty-six qualitative interviews were conducted with PLHIV and clinical providers participating in the TEKO trial. We explored TB screening, diagnosis, and treatment guidelines and processes and the use of the QGIT to screen for latent TB infection at the time of CD4 blood draw. Thematic content analysis was conducted. Considerable variability in TB screening procedures was documented due to lack of personnel and clarity regarding current national TB guidelines for PLHIV. Few clinics had started using the TST per national guidelines and many patients had never heard of isoniazid preventive therapy (IPT). Nearly all participants supported the idea of latent TB screening using routine blood drawn for CD4 counts. Findings indicate that screening for latent TB infection using QGIT from blood drawn for CD4 counts among PLHIV is an acceptable approach to increase latent TB detection given the challenges associated with ensuring systematic latent TB screening in overburdened public clinics. The results presented here were from formative research related to the TEKO trial (Identifier NCT02119130 , registered 10 April 2014).

Changes in latent fingerprint examiners' markup between analysis and comparison.

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Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn

2015-02-01

After the initial analysis of a latent print, an examiner will sometimes revise the assessment during comparison with an exemplar. Changes between analysis and comparison may indicate that the initial analysis of the latent was inadequate, or that confirmation bias may have affected the comparison. 170 volunteer latent print examiners, each randomly assigned 22 pairs of prints from a pool of 320 total pairs, provided detailed markup documenting their interpretations of the prints and the bases for their comparison conclusions. We describe changes in value assessments and markup of features and clarity. When examiners individualized, they almost always added or deleted minutiae (90.3% of individualizations); every examiner revised at least some markups. For inconclusive and exclusion determinations, changes were less common, and features were added more frequently when the image pair was mated (same source). Even when individualizations were based on eight or fewer corresponding minutiae, in most cases some of those minutiae had been added during comparison. One erroneous individualization was observed: the markup changes were notably extreme, and almost all of the corresponding minutiae had been added during comparison. Latents assessed to be of value for exclusion only (VEO) during analysis were often individualized when compared to a mated exemplar (26%); in our previous work, where examiners were not required to provide markup of features, VEO individualizations were much less common (1.8%). Published by Elsevier Ireland Ltd.

Fitting and interpreting continuous-time latent Markov models for panel data.

Science.gov (United States)

Lange, Jane M; Minin, Vladimir N

2013-11-20

Multistate models characterize disease processes within an individual. Clinical studies often observe the disease status of individuals at discrete time points, making exact times of transitions between disease states unknown. Such panel data pose considerable modeling challenges. Assuming the disease process progresses accordingly, a standard continuous-time Markov chain (CTMC) yields tractable likelihoods, but the assumption of exponential sojourn time distributions is typically unrealistic. More flexible semi-Markov models permit generic sojourn distributions yet yield intractable likelihoods for panel data in the presence of reversible transitions. One attractive alternative is to assume that the disease process is characterized by an underlying latent CTMC, with multiple latent states mapping to each disease state. These models retain analytic tractability due to the CTMC framework but allow for flexible, duration-dependent disease state sojourn distributions. We have developed a robust and efficient expectation-maximization algorithm in this context. Our complete data state space consists of the observed data and the underlying latent trajectory, yielding computationally efficient expectation and maximization steps. Our algorithm outperforms alternative methods measured in terms of time to convergence and robustness. We also examine the frequentist performance of latent CTMC point and interval estimates of disease process functionals based on simulated data. The performance of estimates depends on time, functional, and data-generating scenario. Finally, we illustrate the interpretive power of latent CTMC models for describing disease processes on a dataset of lung transplant patients. We hope our work will encourage wider use of these models in the biomedical setting. Copyright © 2013 John Wiley & Sons, Ltd.

Application of core–shell-structured CdTe-SiO2 quantum dots synthesized via a facile solution method for improving latent fingerprint detection

International Nuclear Information System (INIS)

Gao Feng; Han Jiaxing; Lv Caifeng; Wang Qin; Zhang Jun; Li Qun; Bao Liru; Li Xin

2012-01-01

Fingerprint detection is important in criminal investigation. This paper reports a facile powder brushing technique for improving latent fingerprint detection using core–shell-structured CdTe-SiO 2 quantum dots (QDs) as fluorescent labeling marks. Core–shell-structured CdTe-SiO 2 QDs are prepared via a simple solution-based approach using NH 2 NH 2 ·H 2 O as pH adjustor and stabilizer, and their application for improving latent fingerprint detection is explored. The obtained CdTe-SiO 2 QDs show spherical shapes with well-defined core–shell structures encapsulating different amounts of QDs depending on the type of the pH adjustor and stabilizer. Moreover, the fluorescence of CdTe-SiO 2 QDs is largely enhanced by surface modification of the SiO 2 shell. The CdTe-SiO 2 QDs overcome the oxidation problem of pure CdTe QDs in air, thus affording better variability with strong adhesive ability, better resolution, and bright emission colors for practical application in latent fingerprint detection. In comparison with the conventional fluorescence powders, silver powders, and others, the effectiveness of CdTe-SiO 2 QD powders for detection of latent fingerprints present on a large variety of object surfaces is greatly improved. The synthesis method for CdTe-SiO 2 QDs is simple, cheap, and easy for large-scale production, and thus offers many advantages in the practical application of fingerprint detection.

Examination of the change in latent statuses in bullying behaviors across time.

Science.gov (United States)

Ryoo, Ji Hoon; Wang, Cixin; Swearer, Susan M

2015-03-01

Involvement in bullying and victimization has been mostly studied using cross-sectional data from 1 time point. As such, much of our understanding of bullying and victimization has not captured the dynamic experiences of youth over time. To examine the change of latent statuses in bullying and victimization, we applied latent transition analysis examining self-reported bullying involvement from 1,180 students in 5th through 9th grades across 3 time points. We identified unobserved heterogeneous subgroups (i.e., latent statuses) and investigated how students transition between the unobserved subgroups over time. For victimization, 4 latent statuses were identified: frequent victim (11.23%), occasional traditional victim (28.86%), occasional cyber and traditional victim (10.34%), and infrequent victim (49.57%). For bullying behavior, 3 latent statuses were identified: frequent perpetrator (5.12%), occasional verbal/relational perpetrator (26.04%), and infrequent perpetrator (68.84%). The characteristics of the transitions were examined. The multiple-group effects of gender, grade, and first language learned on transitions across statuses were also investigated. The infrequent victim and infrequent perpetrator groups were the most stable, and the frequent victim and frequent perpetrator groups were the least stable. These findings suggest instability in perpetration and victimization over time, as well as significant changes, especially during school transition years. Findings suggest that school-based interventions need to address the heterogeneity in perpetrator and victim experiences in adolescence.

Rapid quantification of the latent reservoir for HIV-1 using a viral outgrowth assay.

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Gregory M Laird

Full Text Available HIV-1 persists in infected individuals in a stable pool of resting CD4(+ T cells as a latent but replication-competent provirus. This latent reservoir is the major barrier to the eradication of HIV-1. Clinical trials are currently underway investigating the effects of latency-disrupting compounds on the persistence of the latent reservoir in infected individuals. To accurately assess the effects of such compounds, accurate assays to measure the frequency of latently infected cells are essential. The development of a simpler assay for the latent reservoir has been identified as a major AIDS research priority. We report here the development and validation of a rapid viral outgrowth assay that quantifies the frequency of cells that can release replication-competent virus following cellular activation. This new assay utilizes bead and column-based purification of resting CD4(+ T cells from the peripheral blood of HIV-1 infected patients rather than cell sorting to obtain comparable resting CD4(+ T cell purity. This new assay also utilizes the MOLT-4/CCR5 cell line for viral expansion, producing statistically comparable measurements of the frequency of latent HIV-1 infection. Finally, this new assay employs a novel quantitative RT-PCR specific for polyadenylated HIV-1 RNA for virus detection, which we demonstrate is a more sensitive and cost-effective method to detect HIV-1 replication than expensive commercial ELISA detection methods. The reductions in both labor and cost make this assay suitable for quantifying the frequency of latently infected cells in clinical trials of HIV-1 eradication strategies.

Using a single tablet daily to treat latent tuberculosis infection in Brazil: bioequivalence of two different isoniazid formulations (300 mg and 100 mg) demonstrated by a sensitive and rapid high-performance liquid chromatography-tandem mass spectrometry method in a randomised, crossover study.

Science.gov (United States)

Daher, André; Pitta, Luciana; Santos, Tereza; Barreira, Draurio; Pinto, Douglas

2015-06-01

The recommended treatment for latent tuberculosis (TB) infection in adults is a daily dose of isoniazid (INH) 300 mg for six months. In Brazil, INH was formulated as 100 mg tablets. The treatment duration and the high pill burden compromised patient adherence to the treatment. The Brazilian National Programme for Tuberculosis requested a new 300 mg INH formulation. The aim of our study was to compare the bioavailability of the new INH 300 mg formulation and three 100 mg tablets of the reference formulation. We conducted a randomised, single dose, open label, two-phase crossover bioequivalence study in 28 healthy human volunteers. The 90% confidence interval for the INH maximum concentration of drug observed in plasma and area under the plasma concentration vs. time curve from time zero to the last measurable concentration "time t" was 89.61-115.92 and 94.82-119.44, respectively. The main limitation of our study was that neither adherence nor the safety profile of multiple doses was evaluated. To determine the level of INH in human plasma, we developed and validated a sensitive, simple and rapid high-performance liquid chromatography-tandem mass spectrometry method. Our results showed that the new formulation was bioequivalent to the 100 mg reference product. This finding supports the use of a single 300 mg tablet daily strategy to treat latent TB. This new formulation may increase patients' adherence to the treatment and quality of life.

Using a single tablet daily to treat latent tuberculosis infection in Brazil: bioequivalence of two different isoniazid formulations (300 mg and 100 mg demonstrated by a sensitive and rapid high-performance liquid chromatography-tandem mass spectrometry method in a randomised, crossover study

Directory of Open Access Journals (Sweden)

André Daher

2015-06-01

Full Text Available The recommended treatment for latent tuberculosis (TB infection in adults is a daily dose of isoniazid (INH 300 mg for six months. In Brazil, INH was formulated as 100 mg tablets. The treatment duration and the high pill burden compromised patient adherence to the treatment. The Brazilian National Programme for Tuberculosis requested a new 300 mg INH formulation. The aim of our study was to compare the bioavailability of the new INH 300 mg formulation and three 100 mg tablets of the reference formulation. We conducted a randomised, single dose, open label, two-phase crossover bioequivalence study in 28 healthy human volunteers. The 90% confidence interval for the INH maximum concentration of drug observed in plasma and area under the plasma concentration vs. time curve from time zero to the last measurable concentration “time t” was 89.61-115.92 and 94.82-119.44, respectively. The main limitation of our study was that neither adherence nor the safety profile of multiple doses was evaluated. To determine the level of INH in human plasma, we developed and validated a sensitive, simple and rapid high-performance liquid chromatography-tandem mass spectrometry method. Our results showed that the new formulation was bioequivalent to the 100 mg reference product. This finding supports the use of a single 300 mg tablet daily strategy to treat latent TB. This new formulation may increase patients’ adherence to the treatment and quality of life.

Research of thermal dynamic characteristics for variable load single screw refrigeration compressor with different capacity control mechanism

International Nuclear Information System (INIS)

Wang, Zengli; Wang, Zhenbo; Wang, Jun; Jiang, Wenchun; Feng, Quanke

2017-01-01

Highlights: • Theoretical models of SSRC under part-load condition have been established. • The experiment of SSRC performance under part-load condition was conducted. • Thermal dynamic characteristic of SSRC under part-load condition was gained. • Economy and reliability of SSRC under part-load condition was analyzed. - Abstract: In the single screw refrigeration compressor (SSRC), the capacity control mechanism is normally employed to meet the actual required cooling capacity under different load conditions. In this paper, theoretical calculation models describing the working process of the SSRC with the single slide valve capacity control mechanism (SVCCM) and SSRC with the frequency conversion regulating mechanism (FCRM) are established to research the thermal dynamic characteristics for variable load SSRC under part-load conditions. Experimental investigation on a SSRC under part-load conditions is also carried out to verify the theoretical calculation models. By using these validated models, the thermodynamic performances and dynamic characteristics of the SSRC with different capacity control mechanism under part-load conditions have been analyzed and compared. Through the comparison, the economical efficiency and reliability of the SSRC with different capacity control mechanism were obtained. All of these works can provide the basis for the later optimization design for the variable load single screw refrigeration compressor.

Modeling associations between latent event processes governing time series of pulsing hormones.

Science.gov (United States)

Liu, Huayu; Carlson, Nichole E; Grunwald, Gary K; Polotsky, Alex J

2017-10-31

This work is motivated by a desire to quantify relationships between two time series of pulsing hormone concentrations. The locations of pulses are not directly observed and may be considered latent event processes. The latent event processes of pulsing hormones are often associated. It is this joint relationship we model. Current approaches to jointly modeling pulsing hormone data generally assume that a pulse in one hormone is coupled with a pulse in another hormone (one-to-one association). However, pulse coupling is often imperfect. Existing joint models are not flexible enough for imperfect systems. In this article, we develop a more flexible class of pulse association models that incorporate parameters quantifying imperfect pulse associations. We propose a novel use of the Cox process model as a model of how pulse events co-occur in time. We embed the Cox process model into a hormone concentration model. Hormone concentration is the observed data. Spatial birth and death Markov chain Monte Carlo is used for estimation. Simulations show the joint model works well for quantifying both perfect and imperfect associations and offers estimation improvements over single hormone analyses. We apply this model to luteinizing hormone (LH) and follicle stimulating hormone (FSH), two reproductive hormones. Use of our joint model results in an ability to investigate novel hypotheses regarding associations between LH and FSH secretion in obese and non-obese women. © 2017, The International Biometric Society.

Self-Calibrating Wave-Encoded Variable-Density Single-Shot Fast Spin Echo Imaging.

Science.gov (United States)

Chen, Feiyu; Taviani, Valentina; Tamir, Jonathan I; Cheng, Joseph Y; Zhang, Tao; Song, Qiong; Hargreaves, Brian A; Pauly, John M; Vasanawala, Shreyas S

2018-04-01

It is highly desirable in clinical abdominal MR scans to accelerate single-shot fast spin echo (SSFSE) imaging and reduce blurring due to T 2 decay and partial-Fourier acquisition. To develop and investigate the clinical feasibility of wave-encoded variable-density SSFSE imaging for improved image quality and scan time reduction. Prospective controlled clinical trial. With Institutional Review Board approval and informed consent, the proposed method was assessed on 20 consecutive adult patients (10 male, 10 female, range, 24-84 years). A wave-encoded variable-density SSFSE sequence was developed for clinical 3.0T abdominal scans to enable high acceleration (3.5×) with full-Fourier acquisitions by: 1) introducing wave encoding with self-refocusing gradient waveforms to improve acquisition efficiency; 2) developing self-calibrated estimation of wave-encoding point-spread function and coil sensitivity to improve motion robustness; and 3) incorporating a parallel imaging and compressed sensing reconstruction to reconstruct highly accelerated datasets. Image quality was compared pairwise with standard Cartesian acquisition independently and blindly by two radiologists on a scale from -2 to 2 for noise, contrast, confidence, sharpness, and artifacts. The average ratio of scan time between these two approaches was also compared. A Wilcoxon signed-rank tests with a P value under 0.05 considered statistically significant. Wave-encoded variable-density SSFSE significantly reduced the perceived noise level and improved the sharpness of the abdominal wall and the kidneys compared with standard acquisition (mean scores 0.8, 1.2, and 0.8, respectively, P variable-density sampling SSFSE achieves improved image quality with clinically relevant echo time and reduced scan time, thus providing a fast and robust approach for clinical SSFSE imaging. 1 Technical Efficacy: Stage 6 J. Magn. Reson. Imaging 2018;47:954-966. © 2017 International Society for Magnetic Resonance in Medicine.

Interactions between lower urinary tract symptoms and cardiovascular risk factors determine distinct patterns of erectile dysfunction: a latent class analysis.

Science.gov (United States)

Barbosa, João A B A; Muracca, Eduardo; Nakano, Élcio; Assalin, Adriana R; Cordeiro, Paulo; Paranhos, Mario; Cury, José; Srougi, Miguel; Antunes, Alberto A

2013-12-01

An epidemiological association between lower urinary tract symptoms and erectile dysfunction is well established. However, interactions among multiple risk factors and the role of each in pathological mechanisms are not fully elucidated We enrolled 898 men undergoing prostate cancer screening for evaluation with the International Prostate Symptom Score (I-PSS) and simplified International Index of Erectile Function-5 (IIEF-5) questionnaires. Age, race, hypertension, diabetes, dyslipidemia, metabolic syndrome, cardiovascular disease, serum hormones and anthropometric parameters were also evaluated. Risk factors for erectile dysfunction were identified by logistic regression. The 333 men with at least mild to moderate erectile dysfunction (IIEF 16 or less) were included in a latent class model to identify relationships across erectile dysfunction risk factors. Age, hypertension, diabetes, lower urinary tract symptoms and cardiovascular event were independent predictors of erectile dysfunction (pclasses of patients with erectile dysfunction (R2 entropy=0.82). Latent class 1 had younger men at low cardiovascular risk and a moderate/high prevalence of lower urinary tract symptoms. Latent class 2 had the oldest patients at moderate cardiovascular risk with an increased prevalence of lower urinary tract symptoms. Latent class 3 had men of intermediate age with the highest prevalence of cardiovascular risk factors and lower urinary tract symptoms. Erectile dysfunction severity and lower urinary tract symptoms increased from latent class 1 to 3. Risk factor interactions determined different severities of lower urinary tract symptoms and erectile dysfunction. The effect of lower urinary tract symptoms and cardiovascular risk outweighed that of age. While in the youngest patients lower urinary tract symptoms acted as a single risk factor for erectile dysfunction, the contribution of vascular disease resulted in significantly more severe dysfunction. Applying a risk factor

Dorsal bundle lesions do not affect latent inhibition of conditioned suppression.

Science.gov (United States)

Tsaltas, E; Preston, G C; Rawlins, J N; Winocur, G; Gray, J A

1984-01-01

Three experiments are reported which examine the effects of lesions of the dorsal ascending noradrenergic bundle (DB) on latent inhibition using a conditioned suppression procedure in rats. In none of the experiments did the DB lesion have any effect, despite changes in the extent of latent inhibition and in the control procedures used to assess it. The results are discussed in relation to the attentional theory of DB function.

Latent Class Models in action: bridging social capital & Internet usage.

Science.gov (United States)

Neves, Barbara Barbosa; Fonseca, Jaime R S

2015-03-01

This paper explores how Latent Class Models (LCM) can be applied in social research, when the basic assumptions of regression models cannot be validated. We examine the usefulness of this method with data collected from a study on the relationship between bridging social capital and the Internet. Social capital is defined here as the resources that are potentially available in one's social ties. Bridging is a dimension of social capital, usually related to weak ties (acquaintances), and a source of instrumental resources such as information. The study surveyed a stratified random sample of 417 inhabitants of Lisbon, Portugal. We used LCM to create the variable bridging social capital, but also to estimate the relationship between bridging social capital and Internet usage when we encountered convergence problems with the logistic regression analysis. We conclude by showing a positive relationship between bridging and Internet usage, and by discussing the potential of LCM for social science research. Copyright © 2014 Elsevier Inc. All rights reserved.

Managing latent tuberculosis infection and tuberculosis in children

Directory of Open Access Journals (Sweden)

I. Carvalho

2018-03-01

Full Text Available Tuberculosis (TB is a major cause of childhood morbidity and mortality worldwide. The aim of this review is to describe the management of the child with TB and latent tuberculosis infection (LTBI.To develop this article, a working group reviewed relevant epidemiological and other scientific studies and established practices in conducting LBTI and TB in children. The article describes how to manage the child with LTBI, considering transmission and infectiousness of tuberculosis, contact screening and prioritization of contacts and recommendations on treatment of children with LTBI and how to manage the child with TB considering the susceptibility of children to developing tuberculosis, epidemiology and classification of tuberculosis in children, diagnosis and treatment. Keywords: Tuberculosis, Pediatric, Childhood, Latent tuberculosis infection

Latent memory facilitates relearning through molecular signaling mechanisms that are distinct from original learning.

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Menges, Steven A; Riepe, Joshua R; Philips, Gary T

2015-09-01

A highly conserved feature of memory is that it can exist in a latent, non-expressed state which is revealed during subsequent learning by its ability to significantly facilitate (savings) or inhibit (latent inhibition) subsequent memory formation. Despite the ubiquitous nature of latent memory, the mechanistic nature of the latent memory trace and its ability to influence subsequent learning remains unclear. The model organism Aplysia californica provides the unique opportunity to make strong links between behavior and underlying cellular and molecular mechanisms. Using Aplysia, we have studied the mechanisms of savings due to latent memory for a prior, forgotten experience. We previously reported savings in the induction of three distinct temporal domains of memory: short-term (10min), intermediate-term (2h) and long-term (24h). Here we report that savings memory formation utilizes molecular signaling pathways that are distinct from original learning: whereas the induction of both original intermediate- and long-term memory in naïve animals requires mitogen activated protein kinase (MAPK) activation and ongoing protein synthesis, 2h savings memory is not disrupted by inhibitors of MAPK or protein synthesis, and 24h savings memory is not dependent on MAPK activation. Collectively, these findings reveal that during forgetting, latent memory for the original experience can facilitate relearning through molecular signaling mechanisms that are distinct from original learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Statistical inference based on latent ability estimates

NARCIS (Netherlands)

Hoijtink, H.J.A.; Boomsma, A.

The quality of approximations to first and second order moments (e.g., statistics like means, variances, regression coefficients) based on latent ability estimates is being discussed. The ability estimates are obtained using either the Rasch, oi the two-parameter logistic model. Straightforward use

Space-time latent component modeling of geo-referenced health data.

Science.gov (United States)

Lawson, Andrew B; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

2010-08-30

Latent structure models have been proposed in many applications. For space-time health data it is often important to be able to find the underlying trends in time, which are supported by subsets of small areas. Latent structure modeling is one such approach to this analysis. This paper presents a mixture-based approach that can be applied to component selection. The analysis of a Georgia ambulatory asthma county-level data set is presented and a simulation-based evaluation is made. Copyright (c) 2010 John Wiley & Sons, Ltd.

MememxGATE: Unearthing Latent Content Features for Improved Search and Relevancy Ranking Across Scientific Literature

Science.gov (United States)

Wilson, B. D.; McGibbney, L. J.; Mattmann, C. A.; Ramirez, P.; Joyce, M.; Whitehall, K. D.

2015-12-01

Quantifying scientific relevancy is of increasing importance to NASA and the research community. Scientific relevancy may be defined by mapping the impacts of a particular NASA mission, instrument, and/or retrieved variables to disciplines such as climate predictions, natural hazards detection and mitigation processes, education, and scientific discoveries. Related to relevancy, is the ability to expose data with similar attributes. This in turn depends upon the ability for us to extract latent, implicit document features from scientific data and resources and make them explicit, accessible and useable for search activities amongst others. This paper presents MemexGATE; a server side application, command line interface and computing environment for running large scale metadata extraction, general architecture text engineering, document classification and indexing tasks over document resources such as social media streams, scientific literature archives, legal documentation, etc. This work builds on existing experiences using MemexGATE (funded, developed and validated through the DARPA Memex Progrjam PI Mattmann) for extracting and leveraging latent content features from document resources within the Materials Research domain. We extend the software functionality capability to the domain of scientific literature with emphasis on the expansion of gazetteer lists, named entity rules, natural language construct labeling (e.g. synonym, antonym, hyponym, etc.) efforts to enable extraction of latent content features from data hosted by wide variety of scientific literature vendors (AGU Meeting Abstract Database, Springer, Wiley Online, Elsevier, etc.) hosting earth science literature. Such literature makes both implicit and explicit references to NASA datasets and relationships between such concepts stored across EOSDIS DAAC's hence we envisage that a significant part of this effort will also include development and understanding of relevancy signals which can ultimately

Health status transitions in community-living elderly with complex care needs: a latent class approach.

Science.gov (United States)

Lafortune, Louise; Béland, François; Bergman, Howard; Ankri, Joël

2009-02-03

For older persons with complex care needs, accounting for the variability and interdependency in how health dimensions manifest themselves is necessary to understand the dynamic of health status. Our objective is to test the hypothesis that a latent classification can capture this heterogeneity in a population of frail elderly persons living in the community. Based on a person-centered approach, the classification corresponds to substantively meaningful groups of individuals who present with a comparable constellation of health problems. Using data collected for the SIPA project, a system of integrated care for frail older people (n = 1164), we performed latent class analyses to identify homogenous categories of health status (i.e. health profiles) based on 17 indicators of prevalent health problems (chronic conditions; depression; cognition; functional and sensory limitations; instrumental, mobility and personal care disability) Then, we conducted latent transition analyses to study change in profile membership over 2 consecutive periods of 12 and 10 months, respectively. We modeled competing risks for mortality and lost to follow-up as absorbing states to avoid attrition biases. We identified four health profiles that distinguish the physical and cognitive dimensions of health and capture severity along the disability dimension. The profiles are stable over time and robust to mortality and lost to follow-up attrition. The differentiated and gender-specific patterns of transition probabilities demonstrate the profiles' sensitivity to change in health status and unmasked the differential relationship of physical and cognitive domains with progression in disability. Our approach may prove useful at organization and policy levels where many issues call for classification of individuals into pragmatically meaningful groups. In dealing with attrition biases, our analytical strategy could provide critical information for the planning of longitudinal studies of aging

Barcelona - Talent Latent 09 / Ahto Sooaru

Index Scriptorium Estoniae

Sooaru, Ahto

2010-01-01

Fotonäitusest "Talent Latent 09" Barcelonas Arts Santa Monica kunstikeskuses. Loetletud näitusel eksponeeritud fotode autorid. Pikemalt Rafael Milach'i (sünd. 1978), Lucia Ganieva, Javier Marquerie Thomas'i (sünd. 1986), Amaury da Cunha (sünd. 1976) töödest. Lühidalt ka teistest näitustest Arts Santa Monica kunstikeskuses

Transcriptional Regulation of Latent Feline Immunodeficiency Virus in Peripheral CD4+ T-lymphocytes

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Brian G. Murphy

2012-05-01

Full Text Available Feline immunodeficiency virus (FIV, the lentivirus of domestic cats responsible for feline AIDS, establishes a latent infection in peripheral blood CD4+ T-cells approximately eight months after experimental inoculation. In this study, cats experimentally infected with the FIV-C strain in the asymptomatic phase demonstrated an estimated viral load of 1 infected cell per approximately 10³ CD4+ T-cells, with about 1 copy of viral DNA per cell. Approximately 1 in 10 proviral copies was capable of transcription in the asymptomatic phase. The latent FIV proviral promoter was associated with deacetylated, methylated histones, which is consistent with a condensed chromatin structure. In contrast, the transcriptionally active FIV promoter was associated with histone acetylation and demethylation. In addition, RNA polymerase II appeared to be paused on the latent viral promoter, and short promoter-proximal transcripts were detected. Our findings for the FIV promoter in infected cats are similar to results obtained in studies of human immunodeficiency virus (HIV-1 latent proviruses in cell culture in vitro studies. Thus, the FIV/cat model may offer insights into in vivo mechanisms of HIV latency and provides a unique opportunity to test novel therapeutic interventions aimed at eradicating latent virus.

Estimating Non-Normal Latent Trait Distributions within Item Response Theory Using True and Estimated Item Parameters

Science.gov (United States)

Sass, D. A.; Schmitt, T. A.; Walker, C. M.

2008-01-01

Item response theory (IRT) procedures have been used extensively to study normal latent trait distributions and have been shown to perform well; however, less is known concerning the performance of IRT with non-normal latent trait distributions. This study investigated the degree of latent trait estimation error under normal and non-normal…

Treatment of Latent Tuberculosis Infection

OpenAIRE

Tang, Patrick; Johnston, James

2017-01-01

Opinion statement The treatment of latent tuberculosis infection (LTBI) is an essential component of tuberculosis (TB) elimination in regions that have a low incidence of TB. However, the decision to treat individuals with LTBI must consider the limitations of current diagnostic tests for LTBI, the risk of developing active TB disease, the potential adverse effects from chemoprophylactic therapy, and the importance of treatment adherence. When an individual has been diagnosed with LTBI and ac...

The latent structure of oppositional defiant disorder in children and adults.

Science.gov (United States)

Barry, Tammy D; Marcus, David K; Barry, Christopher T; Coccaro, Emil F

2013-12-01

An understanding of the latent structure of oppositional defiant disorder (ODD) is essential for better developing causal models, improving diagnostic and assessment procedures, and enhancing treatments for the disorder. Although much research has focused on ODD-including recent studies informing the diagnostic criteria for DSM-5-research examining the latent structure of ODD is sparse, and no known study has specifically undertaken a taxometric analysis to address the issue of whether ODD is a categorical or dimensional construct. To address this gap, the authors conducted two separate studies using a set of taxometric analyses with data from the NICHD Study of Early Child Care and Youth Development (child study; n = 969) and with data from a large mixed sample of adults, which included participants reporting psychiatric difficulties as well as healthy controls (adult study; n = 600). The results of a variety of non-redundant analyses across both studies revealed a dimensional latent structure for ODD symptoms among both children and adults. These findings are consistent with previous studies that have examined latent structure of related constructs (e.g., aggression, antisocial behavior) as well as studies that have examined the dimensional versus categorical structure of ODD using methods other than taxometric analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cross-Informant Agreement on Child and Adolescent Withdrawn Behavior: A Latent Class Approach

Science.gov (United States)

Rubin, David H.; Althoff, Robert R.; Walkup, John T.; Hudziak, James J.

2013-01-01

Withdrawn behavior (WB) relates to many developmental outcomes, including pervasive developmental disorders, anxiety, depression, psychosis, personality disorders and suicide. No study has compared the latent profiles of different informants' reports on WB. This study uses multi-informant latent class analyses (LCA) of the child behavior checklist…

Residual Structures in Latent Growth Curve Modeling

Science.gov (United States)

Grimm, Kevin J.; Widaman, Keith F.

2010-01-01

Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…

VARIABEL LATEN SEBAGAI MODERATOR DAN MEDIATOR DALAM HUBUNGAN KAUSAL

OpenAIRE

I KOMANG GEDE ANTARA; I PUTU EKA NILA KENCANA; KETUT JAYANEGARA

2014-01-01

Latent variables are variables that can not be measured directly. In analysis of causal relationship involving three latent variables, one latent variable can be a moderator or mediator variables. Goodness of Fit moderation and mediation model of latent variables is affected by the value of the canonical correlation between moderator/mediator latent variables with the independent latent variables and dependent latent variables. If the value of both canonical correlation is well , so the Good...

Shared Gaussian Process Latent Variable Model for Multi-view Facial Expression Recognition

NARCIS (Netherlands)

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

Facial-expression data often appear in multiple views either due to head-movements or the camera position. Existing methods for multi-view facial expression recognition perform classification of the target expressions either by using classifiers learned separately for each view or by using a single

An in-depth comparison of latent HIV-1 reactivation in multiple cell model systems and resting CD4+ T cells from aviremic patients.

Directory of Open Access Journals (Sweden)

Celsa A Spina

Full Text Available The possibility of HIV-1 eradication has been limited by the existence of latently infected cellular reservoirs. Studies to examine control of HIV latency and potential reactivation have been hindered by the small numbers of latently infected cells found in vivo. Major conceptual leaps have been facilitated by the use of latently infected T cell lines and primary cells. However, notable differences exist among cell model systems. Furthermore, screening efforts in specific cell models have identified drug candidates for "anti-latency" therapy, which often fail to reactivate HIV uniformly across different models. Therefore, the activity of a given drug candidate, demonstrated in a particular cellular model, cannot reliably predict its activity in other cell model systems or in infected patient cells, tested ex vivo. This situation represents a critical knowledge gap that adversely affects our ability to identify promising treatment compounds and hinders the advancement of drug testing into relevant animal models and clinical trials. To begin to understand the biological characteristics that are inherent to each HIV-1 latency model, we compared the response properties of five primary T cell models, four J-Lat cell models and those obtained with a viral outgrowth assay using patient-derived infected cells. A panel of thirteen stimuli that are known to reactivate HIV by defined mechanisms of action was selected and tested in parallel in all models. Our results indicate that no single in vitro cell model alone is able to capture accurately the ex vivo response characteristics of latently infected T cells from patients. Most cell models demonstrated that sensitivity to HIV reactivation was skewed toward or against specific drug classes. Protein kinase C agonists and PHA reactivated latent HIV uniformly across models, although drugs in most other classes did not.

An In-Depth Comparison of Latent HIV-1 Reactivation in Multiple Cell Model Systems and Resting CD4+ T Cells from Aviremic Patients

Science.gov (United States)

Spina, Celsa A.; Anderson, Jenny; Archin, Nancie M.; Bosque, Alberto; Chan, Jonathan; Famiglietti, Marylinda; Greene, Warner C.; Kashuba, Angela; Lewin, Sharon R.; Margolis, David M.; Mau, Matthew; Ruelas, Debbie; Saleh, Suha; Shirakawa, Kotaro; Siliciano, Robert F.; Singhania, Akul; Soto, Paula C.; Terry, Valeri H.; Verdin, Eric; Woelk, Christopher; Wooden, Stacey; Xing, Sifei; Planelles, Vicente

2013-01-01

The possibility of HIV-1 eradication has been limited by the existence of latently infected cellular reservoirs. Studies to examine control of HIV latency and potential reactivation have been hindered by the small numbers of latently infected cells found in vivo. Major conceptual leaps have been facilitated by the use of latently infected T cell lines and primary cells. However, notable differences exist among cell model systems. Furthermore, screening efforts in specific cell models have identified drug candidates for “anti-latency” therapy, which often fail to reactivate HIV uniformly across different models. Therefore, the activity of a given drug candidate, demonstrated in a particular cellular model, cannot reliably predict its activity in other cell model systems or in infected patient cells, tested ex vivo. This situation represents a critical knowledge gap that adversely affects our ability to identify promising treatment compounds and hinders the advancement of drug testing into relevant animal models and clinical trials. To begin to understand the biological characteristics that are inherent to each HIV-1 latency model, we compared the response properties of five primary T cell models, four J-Lat cell models and those obtained with a viral outgrowth assay using patient-derived infected cells. A panel of thirteen stimuli that are known to reactivate HIV by defined mechanisms of action was selected and tested in parallel in all models. Our results indicate that no single in vitro cell model alone is able to capture accurately the ex vivo response characteristics of latently infected T cells from patients. Most cell models demonstrated that sensitivity to HIV reactivation was skewed toward or against specific drug classes. Protein kinase C agonists and PHA reactivated latent HIV uniformly across models, although drugs in most other classes did not. PMID:24385908

Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood.

Science.gov (United States)

Behrendt, Silke; Bühringer, Gerhard; Höfler, Michael; Lieb, Roselind; Beesdo-Baum, Katja

2017-10-01

Comorbid internalizing mental disorders in alcohol use disorders (AUD) can be understood as putative independent risk factors for AUD or as expressions of underlying shared psychopathology vulnerabilities. However, it remains unclear whether: 1) specific latent internalizing psychopathology risk-profiles predict AUD-incidence and 2) specific latent internalizing comorbidity-profiles in AUD predict AUD-stability. To investigate baseline latent internalizing psychopathology risk profiles as predictors of subsequent AUD-incidence and -stability in adolescents and young adults. Data from the prospective-longitudinal EDSP study (baseline age 14-24 years) were used. The study-design included up to three follow-up assessments in up to ten years. DSM-IV mental disorders were assessed with the DIA-X/M-CIDI. To investigate risk-profiles and their associations with AUD-outcomes, latent class analysis with auxiliary outcome variables was applied. AUD-incidence: a 4-class model (N=1683) was identified (classes: normative-male [45.9%], normative-female [44.2%], internalizing [5.3%], nicotine dependence [4.5%]). Compared to the normative-female class, all other classes were associated with a higher risk of subsequent incident alcohol dependence (p<0.05). AUD-stability: a 3-class model (N=1940) was identified with only one class (11.6%) with high probabilities for baseline AUD. This class was further characterized by elevated substance use disorder (SUD) probabilities and predicted any subsequent AUD (OR 8.5, 95% CI 5.4-13.3). An internalizing vulnerability may constitute a pathway to AUD incidence in adolescence and young adulthood. In contrast, no indication for a role of internalizing comorbidity profiles in AUD-stability was found, which may indicate a limited importance of such profiles - in contrast to SUD-related profiles - in AUD stability. Copyright © 2017 Elsevier B.V. All rights reserved.

Maternal anaemia at delivery and haemoglobin evolution in children during their first 18 months of life using latent class analysis.

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Kobto G Koura

Full Text Available BACKGROUND: Anaemia during pregnancy and at delivery is an important public health problem in low- and middle-income countries. Its association with the children's haemoglobin level over time remains unclear. Our goals were to identify distinct haemoglobin level trajectories using latent class analysis and to assess the association between these trajectories and maternal anaemia and other risk factors. METHOD: A prospective study of children from birth to 18 months of life was conducted in a rural setting in Tori-Bossito, Benin. The main outcome measure was the haemoglobin levels repeatedly measured at 3, 6, 9, 12, 15 and 18 months. Variables were collected from the mothers at delivery and from their children at birth and during the follow-up. The analyses were performed by means of Latent Class Analysis which has never been used for this kind of data. All the analyses were performed with Stata software, version 11.0, using the generalized linear latent and mixed model (GLLAMM framework. RESULTS: We showed that 33.7% of children followed a low haemoglobin trajectory and 66.3% a high trajectory during the first 18 months of life. Newborn anaemia, placental malaria, malaria attack, sickle cell trait and male gender were significantly associated with a lower children's haemoglobin level over time, whereas maternal age, children living in a polygamous family and with good feeding practices had a higher Hb level in the first18 months. We also showed that maternal anaemia was a predictor for 'low haemoglobin level trajectory' group membership but have no significant effect on children haemoglobin level over time. CONCLUSION: Latent Class Analyses framework seems well suited to analyse longitudinal data under the hypothesis that different subpopulations of subjects are present in the data, each with its own set of parameters, with distinctive evolutions that themselves may reflect distinctive aetiologies.

Fitting a Mixture Rasch Model to English as a Foreign Language Listening Tests: The Role of Cognitive and Background Variables in Explaining Latent Differential Item Functioning

Science.gov (United States)

Aryadoust, Vahid

2015-01-01

The present study uses a mixture Rasch model to examine latent differential item functioning in English as a foreign language listening tests. Participants (n = 250) took a listening and lexico-grammatical test and completed the metacognitive awareness listening questionnaire comprising problem solving (PS), planning and evaluation (PE), mental…

Examining the Latent Structure of the Delis-Kaplan Executive Function System.

Science.gov (United States)

Karr, Justin E; Hofer, Scott M; Iverson, Grant L; Garcia-Barrera, Mauricio A

2018-05-04

The current study aimed to determine whether the Delis-Kaplan Executive Function System (D-KEFS) taps into three executive function factors (inhibition, shifting, fluency) and to assess the relationship between these factors and tests of executive-related constructs less often measured in latent variable research: reasoning, abstraction, and problem solving. Participants included 425 adults from the D-KEFS standardization sample (20-49 years old; 50.1% female; 70.1% White). Eight alternative measurement models were compared based on model fit, with test scores assigned a priori to three factors: inhibition (Color-Word Interference, Tower), shifting (Trail Making, Sorting, Design Fluency), and fluency (Verbal/Design Fluency). The Twenty Questions, Word Context, and Proverb Tests were predicted in separate structural models. The three-factor model fit the data well (CFI = 0.938; RMSEA = 0.047), although a two-factor model, with shifting and fluency merged, fit similarly well (CFI = 0.929; RMSEA = 0.048). A bifactor model fit best (CFI = 0.977; RMSEA = 0.032) and explained the most variance in shifting indicators, but rarely converged among 5,000 bootstrapped samples. When the three first-order factors simultaneously predicted the criterion variables, only shifting was uniquely predictive (p measuring executive-related constructs and provide a framework through which clinicians can interpret D-KEFS results.

Life-threatening infectious diseases of childhood: single-gene inborn errors of immunity?

Science.gov (United States)

Alcaïs, Alexandre; Quintana-Murci, Lluis; Thaler, David S; Schurr, Erwin; Abel, Laurent; Casanova, Jean-Laurent

2010-12-01

The hypothesis that inborn errors of immunity underlie infectious diseases is gaining experimental support. However, the apparent modes of inheritance of predisposition or resistance differ considerably among diseases and among studies. A coherent genetic architecture of infectious diseases is lacking. We suggest here that life-threatening infectious diseases in childhood, occurring in the course of primary infection, result mostly from individually rare but collectively diverse single-gene variations of variable clinical penetrance, whereas the genetic component of predisposition to secondary or reactivation infections in adults is more complex. This model is consistent with (i) the high incidence of most infectious diseases in early childhood, followed by a steady decline; (ii) theoretical modeling of the impact of monogenic or polygenic predisposition on the incidence distribution of infectious diseases before reproductive age; (iii) available molecular evidence from both monogenic and complex genetics of infectious diseases in children and adults; (iv) current knowledge of immunity to primary and secondary or latent infections; (v) the state of the art in the clinical genetics of noninfectious pediatric and adult diseases; and (vi) evolutionary data for the genes underlying single-gene and complex disease risk. With the recent advent of new-generation deep resequencing, this model of single-gene variations underlying severe pediatric infectious diseases is experimentally testable. © 2010 New York Academy of Sciences.

Homeostatic proliferation fails to efficiently reactivate HIV-1 latently infected central memory CD4+ T cells.

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Alberto Bosque

2011-10-01

Full Text Available Homeostatic proliferation ensures the longevity of central memory T-cells by inducing cell proliferation in the absence of cellular differentiation or activation. This process is governed mainly by IL-7. Central memory T-cells can also be stimulated via engagement of the T-cell receptor, leading to cell proliferation but also activation and differentiation. Using an in vitro model of HIV-1 latency, we have examined in detail the effects of homeostatic proliferation on latently infected central memory T cells. We have also used antigenic stimulation via anti-CD3/anti-CD28 antibodies and established a comparison with a homeostatic proliferation stimulus, to evaluate potential differences in how either treatment affects the dynamics of latent virus populations. First, we show that homeostatic proliferation, as induced by a combination of IL-2 plus IL-7, leads to partial reactivation of latent HIV-1 but is unable to reduce the size of the reservoir in vitro. Second, latently infected cells are able to homeostatically proliferate in the absence of viral reactivation or cell differentiation. These results indicate that IL-2 plus IL-7 may induce a detrimental effect by favoring the maintenance of the latent HIV-1 reservoir. On the other hand, antigenic stimulation efficiently reactivated latent HIV-1 in cultured central memory cells and led to depletion of the latently infected cells via virus-induced cell death.

Substantiation for Approaches to Treatment of Latent Autoimmune Diabetes in Adults

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T.M. Tykhonova

2014-10-01

Conclusions. Analysis of carbohydrate metabolism on the manifestation stage and over time development of latent autoimmune diabetes in adults as well as reduction of β-cells insulin-producing function associated with autoimmune insulitis and progressing while the development of this form of disease, substantiate the rational for insulin administration as this form of diabetes has been diagnosed. If patients with latent autoimmune diabetes in adults have metabolic syndrome clusters it is quite reasonable to add metformin to insulin.

Extra Heat Loss Through Light Weight Roofs Due to Latent Heat

DEFF Research Database (Denmark)

Rode, Carsten

1996-01-01

that changes phase at the terminals of its passage.Note however, that convection of air most often will have an important effect on the overall heat flow - but that is a different topic.Macroscopic latent heat transferConsider the following scenario: Initially, moisture is present in its condensed or frozen......This report is one in a series of papers in Task 5 of IEA Annex 24 on how moisture and air movements affect the energy performance of building constructions. The effect of latent heat flow will be demonstrated by means of an example: a light weight flat roof.Latent heat flow is one of three...... processes by which moisture affects energy performance:Higher thermal conductivityMoist materials have higher thermal con-ductivity than when they are dry. This is because thermally conducting moisture replaces the better insulating air in the pores of the materials. Moisture also enhan-ces the thermal...

Do gender and directness of trauma exposure moderate PTSD's latent structure?

Science.gov (United States)

Frankfurt, Sheila B; Armour, Cherie; Contractor, Ateka A; Elhai, Jon D

2016-11-30

The PTSD diagnosis and latent structure were substantially revised in the transition from DSM-IV to DSM-5. However, three alternative models (i.e., anhedonia model, externalizing behavior model, and hybrid model) of PTSD fit the DSM-5 symptom criteria better than the DSM-5 factor model. Thus, the psychometric performance of the DSM-5 and alternative models' PTSD factor structure needs to be critically evaluated. The current study examined whether gender or trauma directness (i.e., direct or indirect trauma exposure) moderates the PTSD latent structure when using the DSM-5 or alternative models. Model performance was evaluated with measurement invariance testing procedures on a large undergraduate sample (n=455). Gender and trauma directness moderated the DSM-5 PTSD and externalizing behavior model and did not moderate the anhedonia and hybrid models' latent structure. Clinical implications and directions for future research are discussed. Published by Elsevier Ireland Ltd.

Pre-clinical cognitive phenotypes for Alzheimer disease: a latent profile approach.

Science.gov (United States)

Hayden, Kathleen M; Kuchibhatla, Maragatha; Romero, Heather R; Plassman, Brenda L; Burke, James R; Browndyke, Jeffrey N; Welsh-Bohmer, Kathleen A

2014-11-01

Cognitive profiles for pre-clinical Alzheimer disease (AD) can be used to identify groups of individuals at risk for disease and better characterize pre-clinical disease. Profiles or patterns of performance as pre-clinical phenotypes may be more useful than individual test scores or measures of global decline. To evaluate patterns of cognitive performance in cognitively normal individuals to derive latent profiles associated with later onset of disease using a combination of factor analysis and latent profile analysis. The National Alzheimer Coordinating Centers collect data, including a battery of neuropsychological tests, from participants at 29 National Institute on Aging-funded Alzheimer Disease Centers across the United States. Prior factor analyses of this battery demonstrated a four-factor structure comprising memory, attention, language, and executive function. Factor scores from these analyses were used in a latent profile approach to characterize cognition among a group of cognitively normal participants (N = 3,911). Associations between latent profiles and disease outcomes an average of 3 years later were evaluated with multinomial regression models. Similar analyses were used to determine predictors of profile membership. Four groups were identified; each with distinct characteristics and significantly associated with later disease outcomes. Two groups were significantly associated with development of cognitive impairment. In post hoc analyses, both the Trail Making Test Part B, and a contrast score (Delayed Recall - Trails B), significantly predicted group membership and later cognitive impairment. Latent profile analysis is a useful method to evaluate patterns of cognition in large samples for the identification of preclinical AD phenotypes; comparable results, however, can be achieved with very sensitive tests and contrast scores. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Combining choice experiments with psychometric scales to assess the social acceptability of wind energy projects: A latent class approach

International Nuclear Information System (INIS)

Strazzera, Elisabetta; Mura, Marina; Contu, Davide

2012-01-01

A choice experiment exercise is combined with psychometric scales in order: (1) to identify factors that explain support/opposition toward a wind energy development project; and (2) to assess (monetary) trade-offs between attributes of the project. A Latent Class estimator is fitted to the data, and different utility parameters are estimated, conditional on class allocation. It is found that the probability of class membership depends on specific psychometric variables. Visual impacts on valued sites are an important factor of opposition toward a project, and this effect is magnified when identity values are attached to the specific site, so much that no trade-off would be acceptable for a class of individuals characterized by strong place attachment. Conversely, other classes of individuals are willing to accept compensations, in form of private and/or public benefits. The distribution of benefits in the territory, and preservation of the option value related to the possible development of an archeological site, are important for a class of individuals concerned with the sustainability of the local economy. - Highlights: ► A Choice Experiment approach is used to assess acceptability of a wind farm project. ► Psychometric variables are used to model heterogeneity in a Latent Class model. ► No trade-off would be acceptable for a class of individuals. ► Another class of individuals is interested in private benefits. ► Other classes are interested in public benefits and sustainability of the development.

Single cell adhesion strength assessed with variable-angle total internal reflection fluorescence microscopy

Directory of Open Access Journals (Sweden)

Marcelina Cardoso Dos Santos

2017-06-01

Full Text Available We propose a new strategy to evaluate adhesion strength at the single cell level. This approach involves variable-angle total internal reflection fluorescence microscopy to monitor in real time the topography of cell membranes, i.e. a map of the membrane/substrate separation distance. According to the Boltzmann distribution, both potential energy profile and dissociation energy related to the interactions between the cell membrane and the substrate were determined from the membrane topography. We have highlighted on glass substrates coated with poly-L-lysine and fibronectin, that the dissociation energy is a reliable parameter to quantify the adhesion strength of MDA-MB-231 motile cells.

Sensible and latent heat forced divergent circulations in the West African Monsoon System

Science.gov (United States)

Hagos, S.; Zhang, C.

2008-12-01

Field properties of divergent circulation are utilized to identify the roles of various diabatic processes in forcing moisture transport in the dynamics of the West African Monsoon and its seasonal cycle. In this analysis, the divergence field is treated as a set of point sources and is partitioned into two sub-sets corresponding to latent heat release and surface sensible heat flux at each respective point. The divergent circulation associated with each set is then calculated from the Poisson's equation using Gauss-Seidel iteration. Moisture transport by each set of divergent circulation is subsequently estimated. The results show different roles of the divergent circulations forced by surface sensible and latent heating in the monsoon dynamics. Surface sensible heating drives a shallow meridional circulation, which transports moisture deep into the continent at the polar side of the monsoon rain band and thereby promotes the seasonal northward migration of monsoon precipitation during the monsoon onset season. In contrast, the circulation directly associated with latent heating is deep and the corresponding moisture convergence is within the region of precipitation. Latent heating also induces dry air advection from the north. Neither effect promotes the seasonal northward migration of precipitation. The relative contributions of the processes associated with latent and sensible heating to the net moisture convergence, and hence the seasonal evolution of monsoon precipitation, depend on the background moisture.

Modeling the Daly Gap: The Influence of Latent Heat Production in Controlling Magma Extraction and Eruption

Science.gov (United States)

Nelson, B. K.; Ghiorso, M. S.; Bachmann, O.; Dufek, J.

2011-12-01

model, we move the extracted liquid to a shallower chamber (1.5 kbar as inferred for Tenerife phonolite) and resume crystallization. At the optimal magma extraction window of ≈50% crystallinity, the composition matches well with the observed composition of the second peak of the bimodal distribution. In contrast, CI does not show an early spike in latent heat production, but a late (≈900°C) pseudo-invariant point where latent heat production spikes. This spike is very near the 50% crystallinity window, again enhancing the probability of magma extraction. The model liquid composition at this crystallinity matches the observed trachyte composition. In both systems, phase chemistry supports a two-chamber evolution, one deep and the second shallow, corresponding to two primary melt extraction events. Realistically incorporating chemical, thermal and physical processes in magma chamber models provides composition-volume estimates of extracted magma that coincide with observed bimodal composition-volume relations. The strong variability in latent heat production is an important control, and its characterization is central to physical models of magma chamber evolution.

Some children with autism have latent social skills that can be tested

Czech Academy of Sciences Publication Activity Database

Hrdlička, M.; Urbánek, Tomáš; Vacová, M.; Beranová, Š.; Dudová, I.

2017-01-01

Roč. 13, March (2017), s. 827-833 ISSN 1178-2021 Institutional support: RVO:68081740 Keywords : autism * latent social skills * Autism Diagnostic Interview – Revised * Autism Diagnostic Observation Schedule * prediction Subject RIV: AN - Psychology OBOR OECD: Psychology (including human - machine relations) Impact factor: 2.198, year: 2016 https://www.dovepress.com/some-children-with- autism -have-latent-social-skills-that-can-be-tested-peer-reviewed-article-NDT

Some children with autism have latent social skills that can be tested

Czech Academy of Sciences Publication Activity Database

Hrdlička, M.; Urbánek, Tomáš; Vacová, M.; Beranová, Š.; Dudová, I.

2017-01-01

Roč. 13, March (2017), s. 827-833 ISSN 1178-2021 Institutional support: RVO:68081740 Keywords : autism * latent social skills * Autism Diagnostic Interview – Revised * Autism Diagnostic Observation Schedule * prediction Subject RIV: AN - Psychology OBOR OECD: Psychology (including human - machine relations) Impact factor: 2.198, year: 2016 https://www.dovepress.com/some-children-with-autism-have-latent- social -skills-that-can-be-tested-peer-reviewed-article-NDT

Influence of WFIKKN1 on BMP1-mediated activation of latent myostatin.

Science.gov (United States)

Szláma, György; Vásárhelyi, Viktor; Trexler, Mária; Patthy, László

2016-12-01

The NTR domain of WFIKKN1 protein has been shown to have significant affinity for the prodomain regions of promyostatin and latent myostatin but the biological significance of these interactions remained unclear. In view of its role as a myostatin antagonist, we tested the assumption that WFIKKN1 inhibits the release of myostatin from promyostatin and/or latent myostatin. WFIKKN1 was found to have no effect on processing of promyostatin by furin, the rate of cleavage of latent myostatin by BMP1, however, was significantly enhanced in the presence of WFIKKN1 and this enhancer activity was superstimulated by heparin. Unexpectedly, WFIKKN1 was also cleaved by BMP1 and our studies have shown that the KKN1 fragment generated by BMP1-cleavage of WFIKKN1 contributes most significantly to the observed enhancer activity. Analysis of a pro-TGF-β -based homology model of homodimeric latent myostatin revealed that the BMP1-cleavage sites are buried and not readily accessible to BMP1. In view of this observation, the most plausible explanation for the BMP1-enhancer activity of the KKN1 fragment is that it shifts a conformational equilibrium of latent myostatin from the closed circular structure of the homodimer to a more open form, making the cleavage sites more accessible to BMP1. On the other hand, the observation that the enhancer activity of KKN1 is superstimulated in the presence of heparin is explained by the fact KKN1, latent myostatin, and BMP1 have affinity for heparin and these interactions with heparin increase the local concentrations of the reactants thereby facilitating the action of BMP1. Furin: EC 3.4.21.75; BMP1, bone morphogentic protein 1 or procollagen C-endopeptidase: EC 3.4.24.19. © 2016 The Authors. The FEBS Journal published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

Step-to-step spatiotemporal variables and ground reaction forces of intra-individual fastest sprinting in a single session.

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Nagahara, Ryu; Mizutani, Mirai; Matsuo, Akifumi; Kanehisa, Hiroaki; Fukunaga, Tetsuo

2018-06-01

We aimed to investigate the step-to-step spatiotemporal variables and ground reaction forces during the acceleration phase for characterising intra-individual fastest sprinting within a single session. Step-to-step spatiotemporal variables and ground reaction forces produced by 15 male athletes were measured over a 50-m distance during repeated (three to five) 60-m sprints using a long force platform system. Differences in measured variables between the fastest and slowest trials were examined at each step until the 22nd step using a magnitude-based inferences approach. There were possibly-most likely higher running speed and step frequency (2nd to 22nd steps) and shorter support time (all steps) in the fastest trial than in the slowest trial. Moreover, for the fastest trial there were likely-very likely greater mean propulsive force during the initial four steps and possibly-very likely larger mean net anterior-posterior force until the 17th step. The current results demonstrate that better sprinting performance within a single session is probably achieved by 1) a high step frequency (except the initial step) with short support time at all steps, 2) exerting a greater mean propulsive force during initial acceleration, and 3) producing a greater mean net anterior-posterior force during initial and middle acceleration.

Latent factor structure of a behavioral economic marijuana demand curve.

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Aston, Elizabeth R; Farris, Samantha G; MacKillop, James; Metrik, Jane

2017-08-01

Drug demand, or relative value, can be assessed via analysis of behavioral economic purchase task performance. Five demand indices are typically obtained from drug purchase tasks. The goal of this research was to determine whether metrics of marijuana reinforcement from a marijuana purchase task (MPT) exhibit a latent factor structure that efficiently characterizes marijuana demand. Participants were regular marijuana users (n = 99; 37.4% female, 71.5% marijuana use days [5 days/week], 15.2% cannabis dependent) who completed study assessments, including the MPT, during a baseline session. Principal component analysis was used to examine the latent structure underlying MPT indices. Concurrent validity was assessed via examination of relationships between latent factors and marijuana use, past quit attempts, and marijuana expectancies. A two-factor solution was confirmed as the best fitting structure, accounting for 88.5% of the overall variance. Factor 1 (65.8% variance) reflected "Persistence," indicating sensitivity to escalating marijuana price, which comprised four MPT indices (elasticity, O max , P max , and breakpoint). Factor 2 (22.7% variance) reflected "Amplitude," indicating the amount consumed at unrestricted price (intensity). Persistence factor scores were associated with fewer past marijuana quit attempts and lower expectancies of negative use outcomes. Amplitude factor scores were associated with more frequent use, dependence symptoms, craving severity, and positive marijuana outcome expectancies. Consistent with research on alcohol and cigarette purchase tasks, the MPT can be characterized with a latent two-factor structure. Thus, demand for marijuana appears to encompass distinct dimensions of price sensitivity and volumetric consumption, with differential relations to other aspects of marijuana motivation.

Mental toughness latent profiles in endurance athletes.

Directory of Open Access Journals (Sweden)

Joanna S Zeiger

Full Text Available Mental toughness in endurance athletes, while an important factor for success, has been scarcely studied. An online survey was used to examine eight mental toughness factors in endurance athletes. The study aim was to determine mental toughness profiles via latent profile analysis in endurance athletes and whether associations exist between the latent profiles and demographics and sports characteristics. Endurance athletes >18 years of age were recruited via social media outlets (n = 1245, 53% female. Mental toughness was measured using the Sports Mental Toughness Questionnaire (SMTQ, Psychological Performance Inventory-Alternative (PPI-A, and self-esteem was measured using the Rosenberg Self-Esteem Scale (RSE. A three-class solution emerged, designated as high mental toughness (High MT, moderate mental toughness (Moderate MT and low mental toughness (Low MT. ANOVA tests showed significant differences between all three classes on all 8 factors derived from the SMTQ, PPI-A and the RSE. There was an increased odds of being in the High MT class compared to the Low MT class for males (OR = 1.99; 95% CI, 1.39, 2.83; P<0.001, athletes who were over 55 compared to those who were 18-34 (OR = 2.52; 95% CI, 1.37, 4.62; P<0.01, high sports satisfaction (OR = 8.17; 95% CI, 5.63, 11.87; P<0.001, and high division placement (OR = 2.18; 95% CI, 1.46,3.26; P<0.001. The data showed that mental toughness latent profiles exist in endurance athletes. High MT is associated with demographics and sports characteristics. Mental toughness screening in athletes may help direct practitioners with mental skills training.

Polarization-based and specular-reflection-based noncontact latent fingerprint imaging and lifting

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Lin, Shih-Schön; Yemelyanov, Konstantin M.; Pugh, Edward N., Jr.; Engheta, Nader

2006-09-01

In forensic science the finger marks left unintentionally by people at a crime scene are referred to as latent fingerprints. Most existing techniques to detect and lift latent fingerprints require application of a certain material directly onto the exhibit. The chemical and physical processing applied to the fingerprint potentially degrades or prevents further forensic testing on the same evidence sample. Many existing methods also have deleterious side effects. We introduce a method to detect and extract latent fingerprint images without applying any powder or chemicals on the object. Our method is based on the optical phenomena of polarization and specular reflection together with the physiology of fingerprint formation. The recovered image quality is comparable to existing methods. In some cases, such as the sticky side of tape, our method shows unique advantages.

Interference Control, Working Memory Capacity, and Cognitive Abilities: A Latent Variable Analysis

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Unsworth, Nash

2010-01-01

The present study examined whether various indices of interference control were related to one another and to other cognitive abilities. It was found that the interference control measures were weakly correlated and could form a single factor that was related to overall memory performance on the tasks as well as to measures of working memory…

[Latent Class Analysis of Gambling Activities among Korean Adolescents].

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Kang, Kyonghwa; Kim, Hyeongsu; Park, Ae Ran; Kim, Hee Young; Lee, Kunsei

2018-04-01

The aim of this study is to identify the types of gambling among adolescents and provide basic prevention information regarding adolescents' gambling problems. Secondary data from representative national survey on 2015 Youth Gambling Problems of Korea Center on Gambling Problems were used. Using latent class analysis (LCA), 13 gambling types such as offline and online games of 14,011 adolescents were classified, and gambling experiences and characteristics were analyzed. The subgroups of adolescent gambling were identified as four latent classes: a rare group (84.5% of the sample), a risk group (1.0%), an offline group (11.9%), and an expanded group (2.6%). The types and characteristics of gambling among the latent classes differed. In the risk group, adolescents participated in online illegal sports betting and internet casino, and gambling time, gambling expenses, and the number of gambling types were higher than other groups. Gambling frequently occur among adolescent, and the subtypes of gambling did not reveal homogeneous characteristics. In order to prevent adolescent gambling problems, it is a necessary to develop tailored prevention intervention in the nursing field, which is appropriate to the characteristics of adolescent gambling group and can help with early identification. © 2018 Korean Society of Nursing Science.

A New Extension of the Binomial Error Model for Responses to Items of Varying Difficulty in Educational Testing and Attitude Surveys.

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James A Wiley

Full Text Available We put forward a new item response model which is an extension of the binomial error model first introduced by Keats and Lord. Like the binomial error model, the basic latent variable can be interpreted as a probability of responding in a certain way to an arbitrarily specified item. For a set of dichotomous items, this model gives predictions that are similar to other single parameter IRT models (such as the Rasch model but has certain advantages in more complex cases. The first is that in specifying a flexible two-parameter Beta distribution for the latent variable, it is easy to formulate models for randomized experiments in which there is no reason to believe that either the latent variable or its distribution vary over randomly composed experimental groups. Second, the elementary response function is such that extensions to more complex cases (e.g., polychotomous responses, unfolding scales are straightforward. Third, the probability metric of the latent trait allows tractable extensions to cover a wide variety of stochastic response processes.

Latent Membrane Protein 1 as a molecular adjuvant for single-cycle lentiviral vaccines

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Rahmberg Andrew R

2011-05-01

Full Text Available Abstract Background Molecular adjuvants are a promising method to enhance virus-specific immune responses and protect against HIV-1 infection. Immune activation by ligands for receptors such as CD40 can induce dendritic cell activation and maturation. Here we explore the incorporation of two CD40 mimics, Epstein Barr Virus gene LMP1 or an LMP1-CD40 chimera, into a strain of SIV that was engineered to be limited to a single cycle of infection. Results Full length LMP1 or the chimeric protein LMP1-CD40 was cloned into the nef-locus of single-cycle SIV. Human and Macaque monocyte derived macrophages and DC were infected with these viruses. Infected cells were analyzed for activation surface markers by flow cytometry. Cells were also analyzed for secretion of pro-inflammatory cytokines IL-1β, IL-6, IL-8, IL-12p70 and TNF by cytometric bead array. Conclusions Overall, single-cycle SIV expressing LMP1 and LMP1-CD40 produced a broad and potent TH1-biased immune response in human as well as rhesus macaque macrophages and DC when compared with control virus. Single-cycle SIV-LMP1 also enhanced antigen presentation by lentiviral vector vaccines, suggesting that LMP1-mediated immune activation may enhance lentiviral vector vaccines against HIV-1.

Specific heat and magnetization of a ZrB12 single crystal: characterization of a type II/1 superconductor

OpenAIRE

Wang, Yuxing; Lortz, Rolf; Paderno, Yuriy; Filippov, Vladimir; Abe, Satoko; Tutsch, Ulrich; Junod, Alain

2005-01-01

We measured the specific heat, the magnetization, and the magnetoresistance of a single crystal of ZrB12, which is superconducting below Tc ~ 6 K. The specific heat in zero field shows a BCS-type superconducting transition. The normal- to superconducting-state transition changes from first order (with a latent heat) to second order (without latent heat) with increasing magnetic field, indicating that the pure compound is a low-kappa, type-II/1 superconductor in the classification of Auer and ...

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection.

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Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-11-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices.

Broad CTL response is required to clear latent HIV-1 due to dominance of escape mutations

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Deng, Kai; Pertea, Mihaela; Rongvaux, Anthony; Wang, Leyao; Durand, Christine M.; Ghiaur, Gabriel; Lai, Jun; McHugh, Holly L.; Hao, Haiping; Zhang, Hao; Margolick, Joseph B.; Gurer, Cagan; Murphy, Andrew J.; Valenzuela, David M.; Yancopoulos, George D.; Deeks, Steven G.; Strowig, Till; Kumar, Priti; Siliciano, Janet D.; Salzberg, Steven L.; Flavell, Richard A.; Shan, Liang; Siliciano, Robert F.

2015-01-01

Despite antiretroviral therapy (ART), HIV-1 persists in a stable latent reservoir1, 2, primarily in resting memory CD4+ T cells3, 4. This reservoir presents a major barrier to the cure of HIV-1 infection. To purge the reservoir, pharmacological reactivation of latent HIV-1 has been proposed5 and tested both in vitro and in vivo6–8. A key remaining question is whether virus-specific immune mechanisms including cytolytic T lymphocytes (CTL) can clear infected cells in ART-treated patients after latency is reversed. Here we show that there is a striking all or none pattern for CTL escape mutations in HIV-1 Gag epitopes. Unless ART is started early, the vast majority (>98%) of latent viruses carry CTL escape mutations that render infected cells insensitive to CTLs directed at common epitopes. To solve this problem, we identified CTLs that could recognize epitopes from latent HIV-1 that were unmutated in every chronically infected patient tested. Upon stimulation, these CTLs eliminated target cells infected with autologous virus derived from the latent reservoir, both in vitro and in patient-derived humanized mice. The predominance of CTL-resistant viruses in the latent reservoir poses a major challenge to viral eradication. Our results demonstrate that chronically infected patients retain a broad spectrum viral-specific CTL response and that appropriate boosting of this response may be required for the elimination of the latent reservoir. PMID:25561180

A Variable Single Photon Plasmonic Beamsplitter

DEFF Research Database (Denmark)

Israelsen, Niels Møller; Kumar, Shailesh; Huck, Alexander

Plasmonic structures can both be exploited for scaling down optical components beyond the diffraction limit and enhancing andcollecting the emission from a single dipole emitter. Here, we experimentally demonstrate adiabatic coupling between two silvernanowires using a nitrogen vacancy center as ...

Alternative approaches for econometric analysis of panel count data using dynamic latent class models (with application to doctor visits data).

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Hyppolite, Judex; Trivedi, Pravin

2012-06-01

Cross-sectional latent class regression models, also known as switching regressions or hidden Markov models, cannot identify transitions between classes that may occur over time. This limitation can potentially be overcome when panel data are available. For such data, we develop a sequence of models that combine features of the static cross-sectional latent class (finite mixture) models with those of hidden Markov models. We model the probability of movement between categories in terms of a Markovian structure, which links the current state with a previous state, where state may refer to the category of an individual. This article presents a suite of mixture models of varying degree of complexity and flexibility for use in a panel count data setting, beginning with a baseline model which is a two-component mixture of Poisson distribution in which latent classes are fixed and permanent. Sequentially, we extend this framework (i) to allow the mixing proportions to be smoothly varying continuous functions of time-varying covariates, (ii) to add time dependence to the benchmark model by modeling the class-indicator variable as a first-order Markov chain and (iii) to extend item (i) by making it dynamic and introducing covariate dependence in the transition probabilities. We develop and implement estimation algorithms for these models and provide an empirical illustration using 1995-1999 panel data on the number of doctor visits derived from the German Socio-Economic Panel. Copyright © 2012 John Wiley & Sons, Ltd.

Cost-effectiveness of post-landing latent tuberculosis infection control strategies in new migrants to Canada.

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Campbell, Jonathon R; Johnston, James C; Sadatsafavi, Mohsen; Cook, Victoria J; Elwood, R Kevin; Marra, Fawziah

2017-01-01

The majority of tuberculosis in migrants to Canada occurs due to reactivation of latent TB infection. Risk of tuberculosis in those with latent tuberculosis infection can be significantly reduced with treatment. Presently, only 2.4% of new migrants are flagged for post-landing surveillance, which may include latent tuberculosis infection screening; no other migrants receive routine latent tuberculosis infection screening. To aid in reducing the tuberculosis burden in new migrants to Canada, we determined the cost-effectiveness of using different latent tuberculosis infection interventions in migrants under post-arrival surveillance and in all new migrants. A discrete event simulation model was developed that focused on a Canadian permanent resident cohort after arrival in Canada, utilizing a ten-year time horizon, healthcare system perspective, and 1.5% discount rate. Latent tuberculosis infection interventions were evaluated in the population under surveillance (N = 6100) and the total cohort (N = 260,600). In all evaluations, six different screening and treatment combinations were compared to the base case of tuberculin skin test screening followed by isoniazid treatment only in the population under surveillance. Quality adjusted life years, incident tuberculosis cases, and costs were recorded for each intervention and incremental cost-effectiveness ratios were calculated in relation to the base case. In the population under surveillance (N = 6100), using an interferon-gamma release assay followed by rifampin was dominant compared to the base case, preventing 4.90 cases of tuberculosis, a 4.9% reduction, adding 4.0 quality adjusted life years, and saving $353,013 over the ensuing ten-years. Latent tuberculosis infection screening in the total population (N = 260,600) was not cost-effective when compared to the base case, however could potentially prevent 21.8% of incident tuberculosis cases. Screening new migrants under surveillance with an interferon

A variable-temperature scanning tunneling microscope capable of single-molecule vibrational spectroscopy

International Nuclear Information System (INIS)

Stipe, B.C.; Rezaei, M.A.; Ho, W.

1999-01-01

The design and performance of a variable-temperature scanning tunneling microscope (STM) is presented. The microscope operates from 8 to 350 K in ultrahigh vacuum. The thermally compensated STM is suspended by springs from the cold tip of a continuous flow cryostat and is completely surrounded by two radiation shields. The design allows for in situ dosing and irradiation of the sample as well as for the exchange of samples and STM tips. With the STM feedback loop off, the drift of the tip-sample spacing is approximately 0.001 Angstrom/min at 8 K. It is demonstrated that the STM is well-suited for the study of atomic-scale chemistry over a wide temperature range, for atomic-scale manipulation, and for single-molecule inelastic electron tunneling spectroscopy (IETS). copyright 1999 American Institute of Physics

Ultra high temperature latent heat energy storage and thermophotovoltaic energy conversion

OpenAIRE

Datas Medina, Alejandro; Ramos Cabal, Alba; Martí Vega, Antonio; Cañizo Nadal, Carlos del; Luque López, Antonio

2016-01-01

A conceptual energy storage system design that utilizes ultra high temperature phase change materials is presented. In this system, the energy is stored in the form of latent heat and converted to electricity upon demand by TPV (thermophotovoltaic) cells. Silicon is considered in this study as PCM (phase change material) due to its extremely high latent heat (1800 J/g or 500 Wh/kg), melting point (1410 C), thermal conductivity (~25 W/mK), low cost (less than $2/kg or $4/kWh) and a...

Forensic Chemistry: The Revelation of Latent Fingerprints

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Friesen, J. Brent

2015-01-01

The visualization of latent fingerprints often involves the use of a chemical substance that creates a contrast between the fingerprint residues and the surface on which the print was deposited. The chemical-aided visualization techniques can be divided into two main categories: those that chemically react with the fingerprint residue and those…

The Latent Class Structure of Chinese Patients with Eating Disorders in Shanghai.

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Zheng, Yuchen; Kang, Qing; Huang, Jiabin; Jiang, Wenhui; Liu, Qiang; Chen, Han; Fan, Qing; Wang, Zhen; Chen, Jue; Xiao, Zeping

2017-08-25

Eating disorder is culture related, and the clinical symptoms are different between eastern and western patients. So the validity of feeding and eating disorders in the upcoming ICD-11 guide for Chinese patients is unclear. To explore the latent class structure of Chinese patients with eating disorder and the cross-cultural validity of the eating disorder section of the new ICD-11 guide in China. A total of 379 patients with eating disorders at Shanghai Mental Health Center were evaluated using the EDI questionnaire and a questionnaire developed by researchers from 2010 to 2016. SPSS 20.0 was used to enter data and analyze demographic data, and Latent GOLD was employed to conduct latent profile analysis. According to the results of latent profile analysis, patients with eating disorder were divided into five classes: low-weight fasting class (23.1%), non-fat-phobic binge/purge class (21.54%), low-fat-phobic binge class (19.27%), fat-phobic binge class (19.27%), and non-fat-phobic low-weight class (16.76%). Among the clinical symptoms extracted, there were significant differences in Body Mass Index (BMI), binge eating behavior, self-induced vomiting, laxative use and fat-phobic opinion; while there was no significant difference in restrictive food intake. Based on the clinical symptoms, there are five latent classes in Chinese patients with eating disorder, which is in accordance with the diagnostic categories of feeding and eating disorder in ICD-11. However, further work is needed in improving the fat-phobic opinion of patients with eating disorder and clarifying the BMI standard of thinness in the Chinese population.

Resveratrol Reactivates Latent HIV through Increasing Histone Acetylation and Activating Heat Shock Factor 1.

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Zeng, Xiaoyun; Pan, Xiaoyan; Xu, Xinfeng; Lin, Jian; Que, Fuchang; Tian, Yuanxin; Li, Lin; Liu, Shuwen

2017-06-07

The persistence of latent HIV reservoirs presents a significant challenge to viral eradication. Effective latency reversing agents (LRAs) based on "shock and kill" strategy are urgently needed. The natural phytoalexin resveratrol has been demonstrated to enhance HIV gene expression, although its mechanism remains unclear. In this study, we demonstrated that resveratrol was able to reactivate latent HIV without global T cell activation in vitro. Mode of action studies showed resveratrol-mediated reactivation from latency did not involve the activation of silent mating type information regulation 2 homologue 1 (SIRT1), which belonged to class-3 histone deacetylase (HDAC). However, latent HIV was reactivated by resveratrol mediated through increasing histone acetylation and activation of heat shock factor 1 (HSF1). Additionally, synergistic activation of the latent HIV reservoirs was observed under cotreatment with resveratrol and conventional LRAs. Collectively, this research reveals that resveratrol is a natural LRA and shows promise for HIV therapy.

Identification of subgroups of patients with low back pain using Latent Class Analysis

DEFF Research Database (Denmark)

Nielsen, Anne Mølgaard

questionnaire and the clinicians’ findings on a standardised examination of the low back. By using pattern recognition, subgroups of patients were identified within which their responses and scores are similar, and therefore the patients are more alike within the subgroups than across the subgroups. Latent......, the optimal application of the LCA method in this context is unknown and therefore, two methodological considerations were addressed during the process. Firstly, when using existing questionnaire data, whether using each single item or the summary scores would provide better subgroup information. Secondly...... the questionnaires was preferred, due to the more nuanced description available within the resulting subgroups. Therefore, the single‐item strategy was used in the subsequent single‐stage and two‐stage LCA, which identified seven and nine patient subgroups, respectively, with similar face validity and adequate...

Development of molecular tests for the detection of ILAR and latent viruses in fruit trees.

Science.gov (United States)

Roussel, S; Kummert, J; Dutrecq, O; Lepoivre, P; Jijakli, M H

2004-01-01

The detection throughout the year of latent and ILAR viruses in fruit tress by classical serological tests appear to be unreliable. We have developed RT-PCR tests for a reliable detection of latent and ILAR viruses in fruit trees. These assays were then simplified to allow the direct use of crude plant extracts instead of total RNA preparations, and the analyses of pooled samples. In this way, such RT-PCR protocols are suitable for a routine diagnosis of latent and ILAR viruses in fruit tree certification.

Using existing questionnaires in latent class analysis: should we use summary scores or single items as input? A methodological study using a cohort of patients with low back pain

Directory of Open Access Journals (Sweden)

Nielsen AM

2016-04-01

Full Text Available Anne Molgaard Nielsen,1 Werner Vach,2 Peter Kent,1,3 Lise Hestbaek,1,4 Alice Kongsted1,4 1Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark; 2Center for Medical Biometry and Medical Informatics, Medical Center, University of Freiburg, Freiburg, Germany; 3School of Physiotherapy and Exercise Science, Curtin University, Perth, Australia; 4Nordic Institute of Chiropractic and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark Background: Latent class analysis (LCA is increasingly being used in health research, but optimal approaches to handling complex clinical data are unclear. One issue is that commonly used questionnaires are multidimensional, but expressed as summary scores. Using the example of low back pain (LBP, the aim of this study was to explore and descriptively compare the application of LCA when using questionnaire summary scores and when using single items to subgrouping of patients based on multidimensional data. Materials and methods: Baseline data from 928 LBP patients in an observational study were classified into four health domains (psychology, pain, activity, and participation using the World Health Organization’s International Classification of Functioning, Disability, and Health framework. LCA was performed within each health domain using the strategies of summary-score and single-item analyses. The resulting subgroups were descriptively compared using statistical measures and clinical interpretability. Results: For each health domain, the preferred model solution ranged from five to seven subgroups for the summary-score strategy and seven to eight subgroups for the single-item strategy. There was considerable overlap between the results of the two strategies, indicating that they were reflecting the same underlying data structure. However, in three of the four health domains, the single-item strategy resulted in a more nuanced description, in terms

A stable latent reservoir for HIV-1 in resting CD4+ T lymphocytes in infected children

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Persaud, Deborah; Pierson, Theodore; Ruff, Christian; Finzi, Diana; Chadwick, Karen R.; Margolick, Joseph B.; Ruff, Andrea; Hutton, Nancy; Ray, Stuart; Siliciano, Robert F.

2000-01-01

HIV-1 persists in a latent state in resting CD4+ T lymphocytes of infected adults despite prolonged highly active antiretroviral therapy (HAART). To determine whether a latent reservoir for HIV-1 exists in infected children, we performed a quantitative viral culture assay on highly purified resting CD4+ T cells from 21 children with perinatally acquired infection. Replication-competent HIV-1 was recovered from all 18 children from whom sufficient cells were obtained. The frequency of latently infected resting CD4+ T cells directly correlated with plasma virus levels, suggesting that in children with ongoing viral replication, most latently infected cells are in the labile preintegration state of latency. However, in each of 7 children who had suppression of viral replication to undetectable levels for 1–3 years on HAART, latent replication-competent HIV-1 persisted with little decay, owing to a stable reservoir of infected cells in the postintegration stage of latency. Drug-resistance mutations generated by previous nonsuppressive regimens persisted in this compartment despite more than 1 year of fully suppressive HAART, rendering untenable the idea of recycling drugs that were part of failed regimens. Thus the latent reservoir for HIV-1 in resting CD4+ T cells will be a major obstacle to HIV-1 eradication in children. PMID:10749578

Friction massage versus kinesiotaping for short-term management of latent trigger points in the upper trapezius: a randomized controlled trial.

Science.gov (United States)

Mohamadi, Marzieh; Piroozi, Soraya; Rashidi, Iman; Hosseinifard, Saeed

2017-01-01

Latent trigger points in the upper trapezius muscle may disrupt muscle movement patterns and cause problems such as cramping and decreased muscle strength. Because latent trigger points may spontaneously become active trigger points, they should be addressed and treated to prevent further problems. In this study we compared the short-term effect of kinesiotaping versus friction massage on latent trigger points in the upper trapezius muscle. Fifty-eight male students enrolled with a stratified sampling method participated in this single-blind randomized clinical trial (Registration ID: IRCT2016080126674N3) in 2016. Pressure pain threshold was recorded with a pressure algometer and grip strength was recorded with a Collin dynamometer. The participants were randomly assigned to two different treatment groups: kinesiotape or friction massage. Friction massage was performed daily for 3 sessions and kinesiotape was used for 72 h. One hour after the last session of friction massage or removal of the kinesiotape, pressure pain threshold and grip strength were evaluated again. Pressure pain threshold decreased significantly after both friction massage (2.66 ± 0.89 to 2.25 ± 0.76; P  = 0.02) and kinesiotaping (2.00 ± 0.74 to 1.71 ± 0.65; P  = 0.01). Grip strength increased significantly after friction massage (40.78 ± 9.55 to 42.17 ± 10.68; P  = 0.03); however there was no significant change in the kinesiotape group (39.72 ± 6.42 to 40.65 ± 7.3; P  = 0.197). There were no significant differences in pressure pain threshold (2.10 ± 0.11 & 1.87 ± 0.11; P  = 0.66) or grip strength (42.17 ± 10.68 & 40.65 ± 7.3; P  = 0.53) between the two study groups. Friction massage and kinesiotaping had identical short-term effects on latent trigger points in the upper trapezius. Three sessions of either of these two interventions did not improve latent trigger points. Registration ID in IRCT: IRCT2016080126674N3.

A novel anti-alpha-fetoprotein single-chain variable fragment displays anti-tumor effects in HepG2 cells as a single agent or in combination with paclitaxel.

Science.gov (United States)

Ji, Xiaonan; Shen, Yanli; Sun, Hao; Gao, Xiangdong

2016-08-01

Human hepatocellular carcinoma (HCC) has a high rate of tumor recurrence and metastasis, resulting in shortened survival time. The function of alpha-fetoprotein (AFP) as a regulatory factor in the growth of HCC cells has been well defined. The aim of this study was to investigate the use of a novel AFP-specific single-chain variable fragment that blocked AFP and inhibited HCC cell growth. The results indicated that the anti-AFP single-chain variable fragment (scFv) induced growth inhibition of AFP-expressing HCC cell lines in vitro through induction of G1 cell cycle arrest and apoptosis. The mechanism of apoptosis probably involved with blocking AFP internalization and regulation of the PTEN/PI3K/Akt signaling network. Moreover, the anti-AFP-scFv also effectively sensitized the HepG2 cells to paclitaxel (PTX) at a lower concentration. The combination effect of PTX and anti-AFP-scFv displayed a synergistic effect on HepG2 cells both in vitro and in vivo. Our results demonstrated that targeting AFP by specific antibodies has potential immunotherapeutic efficacy in human HCC.

VARIABEL LATEN SEBAGAI MODERATOR DAN MEDIATOR DALAM HUBUNGAN KAUSAL

Directory of Open Access Journals (Sweden)

I KOMANG GEDE ANTARA

2014-01-01

Full Text Available Latent variables are variables that can not be measured directly. In analysis of causal relationship involving three latent variables, one latent variable can be a moderator or mediator variables. Goodness of Fit moderation and mediation model of latent variables is affected by the value of the canonical correlation between moderator/mediator latent variables with the independent latent variables and dependent latent variables. If the value of both canonical correlation is well , so the Goodness of Fit models of mediation is getting better, while the opposite Goodness of Fit models will be better moderation.

VARIABEL LATEN SEBAGAI MODERATOR DAN MEDIATOR DALAM HUBUNGAN KAUSAL

Directory of Open Access Journals (Sweden)

I KOMANG GEDE ANTARA

2013-11-01

Full Text Available Latent variables are variables that can not be measured directly. In analysis of causal relationship involving three latent variables, one latent variable can be a moderator or mediator variables. Goodness of Fit moderation and mediation model of latent variables is affected by the value of the canonical correlation between moderator/mediator latent variables with the independent latent variables and dependent latent variables. If the value of both canonical correlation is well , so the Goodness of Fit models of mediation is getting better, while the opposite Goodness of Fit models will be better moderation.

A Latent Class Regression Analysis of Men's Conformity to Masculine Norms and Psychological Distress

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Wong, Y. Joel; Owen, Jesse; Shea, Munyi

2012-01-01

How are specific dimensions of masculinity related to psychological distress in specific groups of men? To address this question, the authors used latent class regression to assess the optimal number of latent classes that explained differential relationships between conformity to masculine norms and psychological distress in a racially diverse…

Convective and Stratiform Precipitation Processes and their Relationship to Latent Heating

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Tao, Wei-Kuo; Lang, Steve; Zeng, Xiping; Shige, Shoichi; Takayabu, Yukari

2009-01-01

The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of its formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the Tropics. Associated with this rainfall is a vast amount of heat, which is known as latent heat. It arises mainly due to the phase change of water vapor condensing into liquid droplets; three-fourths of the total heat energy available to the Earth's atmosphere comes from tropical rainfall. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. An improved convective -stratiform heating (CSH) algorithm has been developed to obtain the 3D structure of cloud heating over the Tropics based on two sources of information: 1) rainfall information, namely its amount and the fraction due to light rain intensity, observed directly from the Precipitation Radar (PR) on board the TRMM satellite and 2) synthetic cloud physics information obtained from cloud-resolving model (CRM) simulations of cloud systems. The cloud simulations provide details on cloud processes, specifically latent heating, eddy heat flux convergence and radiative heating/cooling, that. are not directly observable by satellite. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. One of the major differences between new and old algorithms is that the level of maximum cloud heating occurs 1 to 1.5 km lower in the atmosphere in the new algorithm. This can effect the structure of the implied air currents associated with the general circulation of the atmosphere in the Tropics. The new CSH algorithm will be used provide retrieved heating data to other heating algorithms to supplement their performance.

Examination of emotion-induced changes in eating: A latent profile analysis of the Emotional Appetite Questionnaire.

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Bourdier, L; Morvan, Y; Kotbagi, G; Kern, L; Romo, L; Berthoz, S

2018-04-01

It is now recognized that emotions can influence food intake. While some people report eating less when distressed, others report either no change of eating or eating more in the same condition. The question whether this interindividual variability also occurs in response to positive emotions has been overlooked in most studies on Emotional Eating (EE). Using the Emotional Appetite Questionnaire (EMAQ) and Latent Profile Analysis, this study aimed to examine the existence of latent emotion-induced changes in eating profiles, and explore how these profiles differ by testing their relations with 1) age and sex, 2) BMI and risk for eating disorders (ED) and 3) factors that are known to be associated with EE such as perceived positive/negative feelings, depression, anxiety, stress symptoms and impulsivity. Among 401 university students (245 females) who completed the EMAQ, 3 profiles emerged (P1:11.2%, P2:60.1%, P3:28.7%), with distinct patterns of eating behaviors in response to negative emotions and situations but few differences regarding positive ones. Negative emotional overeaters (P1) and negative emotional undereaters (P3) reported similar levels of emotional distress and positive feelings, and were at greater risk for ED. However, the people in the former profile i) reported decreasing their food intake in a positive context, ii) were in majority females, iii) had higher BMI and iv) were more prone to report acting rashly when experiencing negative emotions. Our findings suggest that a person-centred analysis of the EMAQ scores offers a promising way to capture the inter-individual variability of emotionally-driven eating behaviors. These observations also add to the growing literature underscoring the importance of further investigating the role of different facets of impulsivity in triggering overeating and to develop more targeted interventions of EE. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effect of acycloguanosine treatment of acute and latent herpes simplex infections in mice.

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Field, H J; Bell, S E; Elion, G B; Nash, A A; Wildy, P

1979-04-01

Systemic treatment of mice with the nucleoside analog 9-(2-hydroxyethoxymethyl)guanine (acycloguanosine [aciclovir]) was found to be highly effective against acute type 1 herpes simplex virus infection of the pinna. The drug ablated clinical signs and reduced virus replication both in tissue local to the inoculation site and within the nervous system. Provided that moderate-sized virus inocula were used, acycloguanosine treatment reduced or prevented the establishment of a latent infection in the dorsal root ganglia relating to the sensory nerve supply of the ear. However, although it aborted artificially produced infections in dorsal root ganglia, acycloguanosine was found not to be effective against the latent infection once established. This finding strongly indicated that latent herpes simplex virus in mice can exist in a nonreplicating form.

A Framework for Reproducible Latent Fingerprint Enhancements.

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Carasso, Alfred S

2014-01-01

Photoshop processing of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology.

Latent heat of traffic moving from rest

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Farzad Ahmadi, S.; Berrier, Austin S.; Doty, William M.; Greer, Pat G.; Habibi, Mohammad; Morgan, Hunter A.; Waterman, Josam H. C.; Abaid, Nicole; Boreyko, Jonathan B.

2017-11-01

Contrary to traditional thinking and driver intuition, here we show that there is no benefit to ground vehicles increasing their packing density at stoppages. By systematically controlling the packing density of vehicles queued at a traffic light on a Smart Road, drone footage revealed that the benefit of an initial increase in displacement for close-packed vehicles is completely offset by the lag time inherent to changing back into a ‘liquid phase’ when flow resumes. This lag is analogous to the thermodynamic concept of the latent heat of fusion, as the ‘temperature’ (kinetic energy) of the vehicles cannot increase until the traffic ‘melts’ into the liquid phase. These findings suggest that in situations where gridlock is not an issue, drivers should not decrease their spacing during stoppages in order to lessen the likelihood of collisions with no loss in flow efficiency. In contrast, motion capture experiments of a line of people walking from rest showed higher flow efficiency with increased packing densities, indicating that the importance of latent heat becomes trivial for slower moving systems.

When do latent class models overstate accuracy for diagnostic and other classifiers in the absence of a gold standard?

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Spencer, Bruce D

2012-06-01

Latent class models are increasingly used to assess the accuracy of medical diagnostic tests and other classifications when no gold standard is available and the true state is unknown. When the latent class is treated as the true class, the latent class models provide measures of components of accuracy including specificity and sensitivity and their complements, type I and type II error rates. The error rates according to the latent class model differ from the true error rates, however, and empirical comparisons with a gold standard suggest the true error rates often are larger. We investigate conditions under which the true type I and type II error rates are larger than those provided by the latent class models. Results from Uebersax (1988, Psychological Bulletin 104, 405-416) are extended to accommodate random effects and covariates affecting the responses. The results are important for interpreting the results of latent class analyses. An error decomposition is presented that incorporates an error component from invalidity of the latent class model. © 2011, The International Biometric Society.

Latent tuberculosis in HIV positive, diagnosed by the M. tuberculosis specific interferon-gamma test

DEFF Research Database (Denmark)

Brock, Inger; Ruhwald, Morten; Lundgren, Bettina

2006-01-01

Although tuberculosis (TB) is a minor problem in Denmark, severe and complicated cases occur in HIV positive. Since the new M. tuberculosis specific test for latent TB, the QuantiFERON-TB In-Tube test (QFT-IT) became available the patients in our clinic have been screened for the presence of latent...

Recovery of latent fingerprints and DNA on human skin.

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Färber, Doris; Seul, Andrea; Weisser, Hans-Joachim; Bohnert, Michael

2010-11-01

The project "Latent Fingerprints and DNA on Human Skin" was the first systematic research in Europe dealing with detection of fingerprints and DNA left by offenders on the skin of corpses. One thousand samples gave results that allow general statements on the materials and methods used. The tests were carried out according to a uniform trial structure. Fingerprints were deposited by natural donors on corpses. The latent fingerprints were treated with magnetic powder or black fingerprint powder. Afterward, they were lifted with silicone casting material (Isomark(®)) or gelatine foil. All lifts were swabbed to recover DNA. It was possible to visualize comparable and identifiable fingerprints on the skin of corpses (16%). In the same categories, magnetic powder (18.4%) yielded better results than black fingerprint powder (13.6%). The number of comparable and identifiable fingerprints decreased on the lifts (12.7%). Isomark(®) (14.9%) was the better lifting material in comparison with gelatine foil (10.1%). In one-third of the samples, DNA could be extracted from the powdered and lifted latents. Black fingerprint powder delivered the better result with a rate of 2.2% for full DNA profiles and profiles useful for exclusion in comparison with 1.8% for the magnetic powder traces. Isomark(®) (3.1%) yielded better results than gelatine foil (0.6%). © 2010 American Academy of Forensic Sciences.

Latent cooling and microphysics effects in deep convection

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Fernández-González, S.; Wang, P. K.; Gascón, E.; Valero, F.; Sánchez, J. L.

2016-11-01

Water phase changes within a storm are responsible for the enhancement of convection and therefore the elongation of its lifespan. Specifically, latent cooling absorbed during evaporation, melting and sublimation is considered the main cause of the intensification of downdrafts. In order to know more accurately the consequences of latent cooling caused by each of these processes (together with microphysical effects that they induce), four simulations were developed with the Wisconsin Dynamical and Microphysical Model (WISCDYMM): one with all the microphysical processes; other without sublimation; melting was suppressed in the third simulation; and evaporation was disabled in the fourth. The results show that sublimation cooling is not essential to maintain the vertical currents of the storm. This is demonstrated by the fact that in the simulation without sublimation, maximum updrafts are in the same range as in the control simulation, and the storm lifespan is similar or even longer. However, melting was of vital importance. The storm in the simulation without melting dissipated prematurely, demonstrating that melting is indispensable to the enhancement of downdrafts below the freezing level and for avoiding the collapse of low level updrafts. Perhaps the most important finding is the crucial influence of evaporative cooling above the freezing level that maintains and enhances mid-level downdrafts in the storm. It is believed that this latent cooling comes from the evaporation of supercooled liquid water connected with the Bergeron-Findeisen process. Therefore, besides its influence at low levels (which was already well known), this evaporative cooling is essential to strengthen mid-level downdrafts and ultimately achieve a quasi-steady state.

Coupled Effects of non-Newtonian Rheology and Aperture Variability on Flow in a Single Fracture

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Di Federico, V.; Felisa, G.; Lauriola, I.; Longo, S.

2017-12-01

Modeling of non-Newtonian flow in fractured media is essential in hydraulic fracturing and drilling operations, EOR, environmental remediation, and to understand magma intrusions. An important step in the modeling effort is a detailed understanding of flow in a single fracture, as the fracture aperture is spatially variable. A large bibliography exists on Newtonian and non-Newtonian flow in variable aperture fractures. Ultimately, stochastic or deterministic modeling leads to the flowrate under a given pressure gradient as a function of the parameters describing the aperture variability and the fluid rheology. Typically, analytical or numerical studies are performed adopting a power-law (Oswald-de Waele) model. Yet the power-law model, routinely used e.g. for hydro-fracturing modeling, does not characterize real fluids at low and high shear rates. A more appropriate rheological model is provided by e.g. the four-parameter Carreau constitutive equation, which is in turn approximated by the more tractable truncated power-law model. Moreover, fluids of interest may exhibit yield stress, which requires the Bingham or Herschel-Bulkely model. This study employs different rheological models in the context of flow in variable aperture fractures, with the aim of understanding the coupled effect of rheology and aperture spatial variability with a simplified model. The aperture variation, modeled within a stochastic or deterministic framework, is taken to be one-dimensional and i) perpendicular; ii) parallel to the flow direction; for stochastic modeling, the influence of different distribution functions is examined. Results for the different rheological models are compared with those obtained for the pure power-law. The adoption of the latter model leads to overestimation of the flowrate, more so for large aperture variability. The presence of yield stress also induces significant changes in the resulting flowrate for assigned external pressure gradient.

Managerial performance and cost efficiency of Japanese local public hospitals: a latent class stochastic frontier model.

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Besstremyannaya, Galina

2011-09-01

The paper explores the link between managerial performance and cost efficiency of 617 Japanese general local public hospitals in 1999-2007. Treating managerial performance as unobservable heterogeneity, the paper employs a panel data stochastic cost frontier model with latent classes. Financial parameters associated with better managerial performance are found to be positively significant in explaining the probability of belonging to the more efficient latent class. The analysis of latent class membership was consistent with the conjecture that unobservable technological heterogeneity reflected in the existence of the latent classes is related to managerial performance. The findings may support the cause for raising efficiency of Japanese local public hospitals by enhancing the quality of management. Copyright © 2011 John Wiley & Sons, Ltd.

Upper atmosphere tidal oscillations due to latent heat release in the tropical troposphere

Directory of Open Access Journals (Sweden)

J. M. Forbes

1997-09-01

Full Text Available Latent heat release associated with tropical deep convective activity is investigated as a source for migrating (sun-synchronous diurnal and semidiurnal tidal oscillations in the 80–150-km height region. Satellite-based cloud brightness temperature measurements made between 1988 and 1994 and averaged into 3-h bins are used to determine the annual- and longitude-average local-time distribution of rainfall rate, and hence latent heating, between ±40° latitude. Regional average rainfall rates are shown to be in good agreement with climatological values derived from surface rain gauge data. A global linearized wave model is used to estimate the corresponding atmospheric perturbations in the mesosphere/lower thermosphere (80–150 km resulting from upward-propagating tidal components excited by the latent heating. The annual-average migrating diurnal and semidiurnal components achieve velocity and temperature amplitudes of order 10–20 m s–1 and 5–10 K, respectively, which represent substantial contributions to the dynamics of the region. The latent heat forcing also shifts the phase (local solar time of maximum of the semidiurnal surface pressure oscillation from 0912 to 0936 h, much closer to the observed value of 0944 h.

Detection of latent prints by Raman imaging

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Lewis, Linda Anne [Andersonville, TN; Connatser, Raynella Magdalene [Knoxville, TN; Lewis, Sr., Samuel Arthur

2011-01-11

The present invention relates to a method for detecting a print on a surface, the method comprising: (a) contacting the print with a Raman surface-enhancing agent to produce a Raman-enhanced print; and (b) detecting the Raman-enhanced print using a Raman spectroscopic method. The invention is particularly directed to the imaging of latent fingerprints.

Proliferation of latently infected CD4+ T cells carrying replication-competent HIV-1: Potential role in latent reservoir dynamics

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