Sample records for sample hierarchical linear

  1. Managing Clustered Data Using Hierarchical Linear Modeling

    ERIC Educational Resources Information Center

    Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

    2012-01-01

    Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

  2. The Advantages of Hierarchical Linear Modeling. ERIC/AE Digest.

    ERIC Educational Resources Information Center

    Osborne, Jason W.

    This digest introduces hierarchical data structure, describes how hierarchical models work, and presents three approaches to analyzing hierarchical data. Hierarchical, or nested data, present several problems for analysis. People or creatures that exist within hierarchies tend to be more similar to each other than people randomly sampled from the…

  3. Exploring the Effects of Congruence and Holland's Personality Codes on Job Satisfaction: An Application of Hierarchical Linear Modeling Techniques

    ERIC Educational Resources Information Center

    Ishitani, Terry T.

    2010-01-01

    This study applied hierarchical linear modeling to investigate the effect of congruence on intrinsic and extrinsic aspects of job satisfaction. Particular focus was given to differences in job satisfaction by gender and by Holland's first-letter codes. The study sample included nationally represented 1462 female and 1280 male college graduates who…

  4. Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning

    PubMed Central

    Fu, QiMing

    2016-01-01

    To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2-regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency. PMID:27795704

  5. Efficient Actor-Critic Algorithm with Hierarchical Model Learning and Planning.

    PubMed

    Zhong, Shan; Liu, Quan; Fu, QiMing

    2016-01-01

    To improve the convergence rate and the sample efficiency, two efficient learning methods AC-HMLP and RAC-HMLP (AC-HMLP with ℓ 2 -regularization) are proposed by combining actor-critic algorithm with hierarchical model learning and planning. The hierarchical models consisting of the local and the global models, which are learned at the same time during learning of the value function and the policy, are approximated by local linear regression (LLR) and linear function approximation (LFA), respectively. Both the local model and the global model are applied to generate samples for planning; the former is used only if the state-prediction error does not surpass the threshold at each time step, while the latter is utilized at the end of each episode. The purpose of taking both models is to improve the sample efficiency and accelerate the convergence rate of the whole algorithm through fully utilizing the local and global information. Experimentally, AC-HMLP and RAC-HMLP are compared with three representative algorithms on two Reinforcement Learning (RL) benchmark problems. The results demonstrate that they perform best in terms of convergence rate and sample efficiency.

  6. Hierarchical Bayesian sparse image reconstruction with application to MRFM.

    PubMed

    Dobigeon, Nicolas; Hero, Alfred O; Tourneret, Jean-Yves

    2009-09-01

    This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hierarchical Bayes model is well suited to such naturally sparse image applications as it seamlessly accounts for properties such as sparsity and positivity of the image via appropriate Bayes priors. We propose a prior that is based on a weighted mixture of a positive exponential distribution and a mass at zero. The prior has hyperparameters that are tuned automatically by marginalization over the hierarchical Bayesian model. To overcome the complexity of the posterior distribution, a Gibbs sampling strategy is proposed. The Gibbs samples can be used to estimate the image to be recovered, e.g., by maximizing the estimated posterior distribution. In our fully Bayesian approach, the posteriors of all the parameters are available. Thus, our algorithm provides more information than other previously proposed sparse reconstruction methods that only give a point estimate. The performance of the proposed hierarchical Bayesian sparse reconstruction method is illustrated on synthetic data and real data collected from a tobacco virus sample using a prototype MRFM instrument.

  7. Clinical time series prediction: Toward a hierarchical dynamical system framework.

    PubMed

    Liu, Zitao; Hauskrecht, Milos

    2015-09-01

    Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey

    USGS Publications Warehouse

    Sauer, John R.; Zimmerman, Guthrie S.; Klimstra, Jon D.; Link, William A.

    2014-01-01

    We used log-linear hierarchical models to analyze data from the Atlantic Flyway Breeding Waterfowl Survey. The survey has been conducted by state biologists each year since 1989 in the northeastern United States from Virginia north to New Hampshire and Vermont. Although yearly population estimates from the survey are used by the United States Fish and Wildlife Service for estimating regional waterfowl population status for mallards (Anas platyrhynchos), black ducks (Anas rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis), they are not routinely adjusted to control for time of day effects and other survey design issues. The hierarchical model analysis permits estimation of year effects and population change while accommodating the repeated sampling of plots and controlling for time of day effects in counting. We compared population estimates from the current stratified random sample analysis to population estimates from hierarchical models with alternative model structures that describe year to year changes as random year effects, a trend with random year effects, or year effects modeled as 1-year differences. Patterns of population change from the hierarchical model results generally were similar to the patterns described by stratified random sample estimates, but significant visibility differences occurred between twilight to midday counts in all species. Controlling for the effects of time of day resulted in larger population estimates for all species in the hierarchical model analysis relative to the stratified random sample analysis. The hierarchical models also provided a convenient means of estimating population trend as derived statistics from the analysis. We detected significant declines in mallard and American black ducks and significant increases in wood ducks and Canada geese, a trend that had not been significant for 3 of these 4 species in the prior analysis. We recommend using hierarchical models for analysis of the Atlantic Flyway Breeding Waterfowl Survey.

  9. Collective Socialization and Child Conduct Problems: A Multilevel Analysis with an African American Sample

    ERIC Educational Resources Information Center

    Simons, Leslie Gordon; Simons, Ronald L.; Conger, Rand D.; Brody, Gene H.

    2004-01-01

    This article uses hierarchical linear modeling with a sample of African American children and their primary caregivers to examine the association between various community factors and child conduct problems. The analysis revealed a rather strong inverse association between level of collective socialization and conduct problems. This relationship…

  10. Reasons for Hierarchical Linear Modeling: A Reminder.

    ERIC Educational Resources Information Center

    Wang, Jianjun

    1999-01-01

    Uses examples of hierarchical linear modeling (HLM) at local and national levels to illustrate proper applications of HLM and dummy variable regression. Raises cautions about the circumstances under which hierarchical data do not need HLM. (SLD)

  11. Analyzing Multilevel Data: An Empirical Comparison of Parameter Estimates of Hierarchical Linear Modeling and Ordinary Least Squares Regression

    ERIC Educational Resources Information Center

    Rocconi, Louis M.

    2011-01-01

    Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…

  12. A Longitudinal Study of Depressive Symptoms and Marijuana Use in a Sample of Inner-City African Americans

    ERIC Educational Resources Information Center

    Repetto, Paula B.; Zimmerman, Marc A.; Caldwell, Cleopatra H.

    2008-01-01

    The association between marijuana use and depressive symptoms was examined longitudinally in a sample of 622 African American youth, interviewed on six occasions, using hierarchical linear modeling (HLM). We considered whether depressive symptoms predicted changes in marijuana use and vice versa from high school through the transition into young…

  13. Micro-Raman spectroscopy of natural and synthetic indigo samples.

    PubMed

    Vandenabeele, Peter; Moens, Luc

    2003-02-01

    In this work indigo samples from three different sources are studied by using Raman spectroscopy: the synthetic pigment and pigments from the woad (Isatis tinctoria) and the indigo plant (Indigofera tinctoria). 21 samples were obtained from 8 suppliers; for each sample 5 Raman spectra were recorded and used for further chemometrical analysis. Principal components analysis (PCA) was performed as data reduction method before applying hierarchical cluster analysis. Linear discriminant analysis (LDA) was implemented as a non-hierarchical supervised pattern recognition method to build a classification model. In order to avoid broad-shaped interferences from the fluorescence background, the influence of 1st and 2nd derivatives on the classification was studied by using cross-validation. Although chemically identical, it is shown that Raman spectroscopy in combination with suitable chemometric methods has the potential to discriminate between synthetic and natural indigo samples.

  14. Clinical time series prediction: towards a hierarchical dynamical system framework

    PubMed Central

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. PMID:25534671

  15. Multilevel modelling: Beyond the basic applications.

    PubMed

    Wright, Daniel B; London, Kamala

    2009-05-01

    Over the last 30 years statistical algorithms have been developed to analyse datasets that have a hierarchical/multilevel structure. Particularly within developmental and educational psychology these techniques have become common where the sample has an obvious hierarchical structure, like pupils nested within a classroom. We describe two areas beyond the basic applications of multilevel modelling that are important to psychology: modelling the covariance structure in longitudinal designs and using generalized linear multilevel modelling as an alternative to methods from signal detection theory (SDT). Detailed code for all analyses is described using packages for the freeware R.

  16. Hierarchical and non-hierarchical {lambda} elements for one dimensional problems with unknown strength of singularity

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

    Wong, K.K.; Surana, K.S.

    1996-10-01

    This paper presents a new and general procedure for designing hierarchical and non-hierarchical special elements called {lambda} elements for one dimensional singular problems where the strength of the singularity is unknown. The {lambda} element formulations presented here permit correct numerical simulation of linear as well as non-linear singular problems without a priori knowledge of the strength of the singularity. A procedure is also presented for determining the exact strength of the singularity using the converged solution. It is shown that in special instances, the general formulation of {lambda} elements can also be made hierarchical. The {lambda} elements presented here aremore » of type C{sup 0} and provide C{sup 0} inter-element continuity with p-version elements. One dimensional steady state radial flow of an upper convected Maxwell fluid is considered as a sample problem. Since in this case {lambda}{sub i} are known, this problem provides a good example for investigating the performance of the formulation proposed here. Least squares approach (or Least Squares Finite Element Formulation: LSFEF) is used to construct the integral form (error functional I) from the differential equations. Numerical studies are presented for radially inward flow of an upper convected Maxwell fluid with inner radius r{sub i} = .1 and .01 etc. and Deborah number De = 2.« less

  17. Scale of association: hierarchical linear models and the measurement of ecological systems

    Treesearch

    Sean M. McMahon; Jeffrey M. Diez

    2007-01-01

    A fundamental challenge to understanding patterns in ecological systems lies in employing methods that can analyse, test and draw inference from measured associations between variables across scales. Hierarchical linear models (HLM) use advanced estimation algorithms to measure regression relationships and variance-covariance parameters in hierarchically structured...

  18. Exploring Growth Trajectories of Problem Behavior in Young Children

    ERIC Educational Resources Information Center

    McCaffrey, Bethany L.

    2012-01-01

    Given the negative outcomes associated with problem behavior and the heightened risk for children with disabilities to display problematic behavior, the current study implemented hierarchical linear modeling to explore the growth trajectories of problem behavior in a nationally representative sample of preschool children with disabilities. Results…

  19. Application of Hierarchical Linear Models/Linear Mixed-Effects Models in School Effectiveness Research

    ERIC Educational Resources Information Center

    Ker, H. W.

    2014-01-01

    Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

  20. Contributions of Child's Physiology and Maternal Behavior to Children's Trajectories of Temperamental Reactivity

    ERIC Educational Resources Information Center

    Blandon, Alysia Y.; Calkins, Susan D.; Keane, Susan P.; O'brien, Marion

    2010-01-01

    Trajectories of children's temperamental reactivity (negative affectivity and surgency) were examined in a community sample of 370 children across the ages of 4 to 7 with hierarchical linear modeling. Children's physiological reactivity (respiratory sinus arrhythmia [RSA]), physiological regulation ([delta]RSA), and maternal parenting behavior…

  1. Predicting Children's Depressive Symptoms from Community and Individual Risk Factors

    ERIC Educational Resources Information Center

    Dallaire, Danielle H.; Cole, David A.; Smith, Thomas M.; Ciesla, Jeffrey A.; LaGrange, Beth; Jacquez, Farrah M.; Pineda, Ashley Q.; Truss, Alanna E.; Folmer, Amy S.

    2008-01-01

    Community, demographic, familial, and personal risk factors of childhood depressive symptoms were examined from an ecological theoretical approach using hierarchical linear modeling. Individual-level data were collected from an ethnically diverse (73% African-American) community sample of 197 children and their parents; community-level data were…

  2. Predicting Successful Mathematics Remediation among Latina/o Students

    ERIC Educational Resources Information Center

    Crisp, Gloria; Reyes, Nicole Alia Salis; Doran, Erin

    2017-01-01

    This study examines Latina/o students' remedial math needs and outcomes. Data were drawn from a national sample of Latina/o students. Hierarchical generalized linear modeling techniques were used to predict three successful remediation outcomes. Results highlight the importance of providing financial aid and academic support to Latina/o students,…

  3. To Aggregate or Not and Potentially Better Questions for Clustered Data: The Need for Hierarchical Linear Modeling in CTE Research

    ERIC Educational Resources Information Center

    Nimon, Kim

    2012-01-01

    Using state achievement data that are openly accessible, this paper demonstrates the application of hierarchical linear modeling within the context of career technical education research. Three prominent approaches to analyzing clustered data (i.e., modeling aggregated data, modeling disaggregated data, modeling hierarchical data) are discussed…

  4. An Analysis of Turkey's PISA 2015 Results Using Two-Level Hierarchical Linear Modelling

    ERIC Educational Resources Information Center

    Atas, Dogu; Karadag, Özge

    2017-01-01

    In the field of education, most of the data collected are multi-level structured. Cities, city based schools, school based classes and finally students in the classrooms constitute a hierarchical structure. Hierarchical linear models give more accurate results compared to standard models when the data set has a structure going far as individuals,…

  5. Exclusionary Discipline of Students with Disabilities: Student and School Characteristics Predicting Suspension

    ERIC Educational Resources Information Center

    Sullivan, Amanda L.; Van Norman, Ethan R.; Klingbeil, David A.

    2014-01-01

    Given the negative outcomes associated with suspension, scholars and practitioners are concerned with discipline disparities. This study explored patterns and predictors of suspension in a sample of 2,750 students with disabilities in 39 schools in a Midwestern district. Hierarchical generalized linear modeling demonstrated that disability type,…

  6. Motivations and Benefits for Attaining HR Certifications

    ERIC Educational Resources Information Center

    Lester, Scott W.; Dwyer, Dale J.

    2012-01-01

    Purpose: The aim of this paper is to examine the motivations and benefits for pursuing or not pursuing the PHR and SPHR. Design/methodology/approach: Using a sample of 1,862 participants, the study used multinomial logistic and hierarchical linear regression to test six hypotheses. Findings: Participants pursuing SPHR were more likely to report…

  7. Injunctive and Descriptive Peer Group Norms and the Academic Adjustment of Rural Early Adolescents

    ERIC Educational Resources Information Center

    Hamm, Jill V.; Schmid, Lorrie; Farmer, Thomas W.; Locke, Belinda

    2011-01-01

    This study integrates diverse literatures on peer group influence by conceptualizing and examining the relationship of peer group injunctive norms to the academic adjustment of a large and ethnically diverse sample of rural early adolescents' academic adjustment. Results of three-level hierarchical linear modeling indicated that peer groups were…

  8. Early Childhood Family Structure and Mother-Child Interactions: Variation by Race and Ethnicity

    ERIC Educational Resources Information Center

    Gibson-Davis, Christina M.; Gassman-Pines, Anna

    2010-01-01

    With data from the Early Childhood Longitudinal Study-Birth Cohort (n = 6,449), a nationally representative sample of births in 2001, we used hierarchical linear modeling to analyze differences in observed interactions between married, cohabiting, never-married, and divorced mothers and their children. In contrast to previous studies, we…

  9. Factors Predicting Science Achievement of Immigrant and Non-Immigrant Students: A Multilevel Analysis

    ERIC Educational Resources Information Center

    Areepattamannil, Shaljan; Kaur, Berinderjeet

    2013-01-01

    This study, employing hierarchical linear modeling (HLM), sought to investigate the student-level and school-level factors associated with the science achievement of immigrant and non-immigrant students among a national sample of 22,646 students from 896 schools in Canada. While student background characteristics such as home language, family…

  10. Differential Relations of Constructivist and Didactic Instruction to Students' Cognition, Motivation, and Achievement

    ERIC Educational Resources Information Center

    Nie, Youyan; Lau, Shun

    2010-01-01

    This study examined how constructivist and didactic instruction was related to students' cognitive, motivational, and achievement outcomes in English classrooms, using a sample of 3000 Grade 9 students from 108 classrooms in 39 secondary schools in Singapore. Results of hierarchical linear modeling showed differential cross-level relations. After…

  11. Complementary Roles of Care and Behavioral Control in Classroom Management: The Self-Determination Theory Perspective

    ERIC Educational Resources Information Center

    Nie, Youyan; Lau, Shun

    2009-01-01

    This study examined how classroom management practices--care and behavioral control--were differentially associated with students' engagement, misbehavior, and satisfaction with school, using a large representative sample of 3196 Grade 9 students from 117 classes in Singapore. Results of hierarchical linear modeling showed differential relations.…

  12. Hierarchical Linear Modeling Meta-Analysis of Single-Subject Design Research

    ERIC Educational Resources Information Center

    Gage, Nicholas A.; Lewis, Timothy J.

    2014-01-01

    The identification of evidence-based practices continues to provoke issues of disagreement across multiple fields. One area of contention is the role of single-subject design (SSD) research in providing scientific evidence. The debate about SSD's utility centers on three issues: sample size, effect size, and serial dependence. One potential…

  13. Determining Predictor Importance in Hierarchical Linear Models Using Dominance Analysis

    ERIC Educational Resources Information Center

    Luo, Wen; Azen, Razia

    2013-01-01

    Dominance analysis (DA) is a method used to evaluate the relative importance of predictors that was originally proposed for linear regression models. This article proposes an extension of DA that allows researchers to determine the relative importance of predictors in hierarchical linear models (HLM). Commonly used measures of model adequacy in…

  14. Multicollinearity in hierarchical linear models.

    PubMed

    Yu, Han; Jiang, Shanhe; Land, Kenneth C

    2015-09-01

    This study investigates an ill-posed problem (multicollinearity) in Hierarchical Linear Models from both the data and the model perspectives. We propose an intuitive, effective approach to diagnosing the presence of multicollinearity and its remedies in this class of models. A simulation study demonstrates the impacts of multicollinearity on coefficient estimates, associated standard errors, and variance components at various levels of multicollinearity for finite sample sizes typical in social science studies. We further investigate the role multicollinearity plays at each level for estimation of coefficient parameters in terms of shrinkage. Based on these analyses, we recommend a top-down method for assessing multicollinearity in HLMs that first examines the contextual predictors (Level-2 in a two-level model) and then the individual predictors (Level-1) and uses the results for data collection, research problem redefinition, model re-specification, variable selection and estimation of a final model. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Individual Differences in Trajectories of Emotion Regulation Processes: The Effects of Maternal Depressive Symptomatology and Children's Physiological Regulation

    ERIC Educational Resources Information Center

    Blandon, Alysia Y.; Calkins, Susan D.; Keane, Susan P.; O'Brien, Marion

    2008-01-01

    Trajectories of emotion regulation processes were examined in a community sample of 269 children across the ages of 4 to 7 using hierarchical linear modeling. Maternal depressive symptomatology (Symptom Checklist-90) and children's physiological reactivity (respiratory sinus arrhythmia [RSA]) and vagal regulation ([delta]RSA) were explored as…

  16. High Achievers from Low Socioeconomic Backgrounds: The Critical Role of Disciplinary Climate and Grit

    ERIC Educational Resources Information Center

    Huang, Haigen; Zhu, Hao

    2017-01-01

    The purpose of this study was to examine whether school disciplinary climate and grit predicted low socioeconomic status (SES) students being high achievers in mathematics and science with a representative sample of 15-year-old students in the United States. Our analysis, using a two-level logistic hierarchical linear model (HLM), indicated both…

  17. Predicting Change in Parenting Stress across Early Childhood: Child and Maternal Factors

    ERIC Educational Resources Information Center

    Williford, Amanda P.; Calkins, Susan D.; Keane, Susan P.

    2007-01-01

    This study examined maternal parenting stress in a sample of 430 boys and girls including those at risk for externalizing behavior problems. Children and their mothers were assessed when the children were ages 2, 4, and 5. Hierarchical linear modeling (HLM) was used to examine stability of parenting stress across early childhood and to examine…

  18. Peer Victimization within the Ethnic Context of High School

    ERIC Educational Resources Information Center

    Felix, Erika D.; You, Sukkyung

    2011-01-01

    Risk for peer victimization varies by ethnicity, but few studies explore how the ethnic context of the school can affect this. Using a large sample of schools and high school students, we used hierarchical linear modeling to explore victimization risk by ethnicity within the ethnic context of the school. Models predicted total, physical, verbal,…

  19. Modeling Signal-Noise Processes Supports Student Construction of a Hierarchical Image of Sample

    ERIC Educational Resources Information Center

    Lehrer, Richard

    2017-01-01

    Grade 6 (modal age 11) students invented and revised models of the variability generated as each measured the perimeter of a table in their classroom. To construct models, students represented variability as a linear composite of true measure (signal) and multiple sources of random error. Students revised models by developing sampling…

  20. The Development of Internet Use for Communication among Undergraduate Students: A Multilevel Analysis

    ERIC Educational Resources Information Center

    Huang, Chiungjung

    2011-01-01

    As few studies utilized longitudinal design to examine the development of Internet use for communication, the purpose of this study was to examine the effects of gender and initial Internet use for communication on subsequent use. The study sample was 280 undergraduate students who were assessed at five time points. Hierarchical linear models were…

  1. The Role of Social Relationships in Predicting Loneliness: The National Social Life, Health, and Aging Project

    ERIC Educational Resources Information Center

    Shiovitz-Ezra, Sharon; Leitsch, Sara A.

    2010-01-01

    The authors explore associations between objective and subjective social network characteristics and loneliness in later life, using data from the National Social Life, Health, and Aging Project, a nationally representative sample of individuals ages 57 to 85 in the United States. Hierarchical linear regression was used to examine the associations…

  2. Testing the Adaptation to Poverty-Related Stress Model: Predicting Psychopathology Symptoms in Families Facing Economic Hardship

    ERIC Educational Resources Information Center

    Wadsworth, Martha E.; Raviv, Tali; Santiago, Catherine DeCarlo; Etter, Erica M.

    2011-01-01

    This study tested the Adaptation to Poverty-related Stress Model and its proposed relations between poverty-related stress, effortful and involuntary stress responses, and symptoms of psychopathology in an ethnically diverse sample of low-income children and their parents. Prospective Hierarchical Linear Modeling analyses conducted with 98…

  3. Test Scores, Dropout Rates, and Transfer Rates as Alternative Indicators of High School Performance

    ERIC Educational Resources Information Center

    Rumberger, Russell W.; Palardy, Gregory J.

    2005-01-01

    This study investigated the relationships among several different indicators of high school performance: test scores, dropout rates, transfer rates, and attrition rates. Hierarchical linear models were used to analyze panel data from a sample of 14,199 students who took part in the National Education Longitudinal Survey of 1988. The results…

  4. A Hierarchical Linear Model for Estimating Gender-Based Earnings Differentials.

    ERIC Educational Resources Information Center

    Haberfield, Yitchak; Semyonov, Moshe; Addi, Audrey

    1998-01-01

    Estimates of gender earnings inequality in data from 116,431 Jewish workers were compared using a hierarchical linear model (HLM) and ordinary least squares model. The HLM allows estimation of the extent to which earnings inequality depends on occupational characteristics. (SK)

  5. Understanding Disproportionate Representation in Special Education by Examining Group Differences in Behavior Ratings

    ERIC Educational Resources Information Center

    Peters, Christina D.; Kranzler, John H.; Algina, James; Smith, Stephen W.; Daunic, Ann P.

    2014-01-01

    The aim of the current study was to examine mean-group differences on behavior rating scales and variables that may predict such differences. Sixty-five teachers completed the Clinical Assessment of Behavior-Teacher Form (CAB-T) for a sample of 982 students. Four outcome variables from the CAB-T were assessed. Hierarchical linear modeling was used…

  6. Are Principal Background and School Processes Related to Teacher Job Satisfaction? A Multilevel Study Using Schools and Staffing Survey 2003-04

    ERIC Educational Resources Information Center

    Shen, Jianping; Leslie, Jeffrey M.; Spybrook, Jessaca K.; Ma, Xin

    2012-01-01

    Using nationally representative samples for public school teachers and principals, the authors inquired into whether principal background and school processes are related to teacher job satisfaction. Employing hierarchical linear modeling (HLM), the authors were able to control for background characteristics at both the teacher and school levels.…

  7. What Works after School? The Relationship between After-School Program Quality, Program Attendance, and Academic Outcomes

    ERIC Educational Resources Information Center

    Leos-Urbel, Jacob

    2015-01-01

    This article examines the relationship between after-school program quality, program attendance, and academic outcomes for a sample of low-income after-school program participants. Regression and hierarchical linear modeling analyses use a unique longitudinal data set including 29 after-school programs that served 5,108 students in Grades 4 to 8…

  8. Hierarchical Linear Modelling of Sixth-Grade Students' Socio-Economic Status and School Factors on Mathematics Achievement: Case Studies of Kenya and Zimbabwe

    ERIC Educational Resources Information Center

    Kanyongo, Gibbs Y.; Ayieko, Rachel

    2017-01-01

    This study investigated the relationship between socio-economic status, school-level variables and mathematics achievement of sixth graders in Kenya and Zimbabwe. The study is based on secondary data collected by the Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ III). SACMEQ employed cluster-sampling procedures…

  9. Hierarchical Linear Modelling of Student and School Effects on Academic Achievement.

    ERIC Educational Resources Information Center

    Ma, Xin; Klinger, Don A.

    2000-01-01

    Used hierarchical linear modeling with data from the New Brunswick School Climate Study (Canada) to examine student background, school context, and school climate effects on Grade 6 student achievement in mathematics, science, reading, and writing. Gender, socioeconomic status, and Native ethnicity were significant predictors of academic…

  10. Preparation of a Co-doped hierarchically porous carbon from Co/Zn-ZIF: An efficient adsorbent for the extraction of trizine herbicides from environment water and white gourd samples.

    PubMed

    Jiao, Caina; Li, Menghua; Ma, Ruiyang; Wang, Chun; Wu, Qiuhua; Wang, Zhi

    2016-05-15

    A Co-doped hierarchically porous carbon (Co/HPC) was synthesized through a facile carbonization process by using Co/ZIF-8 as the precursor. The textures of the Co/HPC were investigated by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, vibration sample magnetometry and nitrogen adsorption-desorption isotherms. The results showed that the Co/HPC is in good polyhedral shape with uniform size, sufficient magnetism, high surface area as well as hierarchical pores (micro-, meso- and macropores). To evaluate the extraction performance of the Co/HPC, it was applied as a magnetic adsorbent for the enrichment of triazine herbicides from environment water and white gourd samples prior to high performance liquid chromatographic analysis. The main parameters that affected the extraction efficiency were investigated. Under the optimum conditions, a good linearity for the four triazine herbicides was achieved with the correlation coefficients (r) higher than 0.9970. The limits of detection, based on S/N=3, were 0.02 ng/mL for water and 0.1-0.2 ng/g for white gourd samples, respectively. The recoveries of all the analytes for the method fell in the range from 80.3% to 120.6%. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Sampling-free Bayesian inversion with adaptive hierarchical tensor representations

    NASA Astrophysics Data System (ADS)

    Eigel, Martin; Marschall, Manuel; Schneider, Reinhold

    2018-03-01

    A sampling-free approach to Bayesian inversion with an explicit polynomial representation of the parameter densities is developed, based on an affine-parametric representation of a linear forward model. This becomes feasible due to the complete treatment in function spaces, which requires an efficient model reduction technique for numerical computations. The advocated perspective yields the crucial benefit that error bounds can be derived for all occuring approximations, leading to provable convergence subject to the discretization parameters. Moreover, it enables a fully adaptive a posteriori control with automatic problem-dependent adjustments of the employed discretizations. The method is discussed in the context of modern hierarchical tensor representations, which are used for the evaluation of a random PDE (the forward model) and the subsequent high-dimensional quadrature of the log-likelihood, alleviating the ‘curse of dimensionality’. Numerical experiments demonstrate the performance and confirm the theoretical results.

  12. A Bayesian hierarchical model with spatial variable selection: the effect of weather on insurance claims

    PubMed Central

    Scheel, Ida; Ferkingstad, Egil; Frigessi, Arnoldo; Haug, Ola; Hinnerichsen, Mikkel; Meze-Hausken, Elisabeth

    2013-01-01

    Climate change will affect the insurance industry. We develop a Bayesian hierarchical statistical approach to explain and predict insurance losses due to weather events at a local geographic scale. The number of weather-related insurance claims is modelled by combining generalized linear models with spatially smoothed variable selection. Using Gibbs sampling and reversible jump Markov chain Monte Carlo methods, this model is fitted on daily weather and insurance data from each of the 319 municipalities which constitute southern and central Norway for the period 1997–2006. Precise out-of-sample predictions validate the model. Our results show interesting regional patterns in the effect of different weather covariates. In addition to being useful for insurance pricing, our model can be used for short-term predictions based on weather forecasts and for long-term predictions based on downscaled climate models. PMID:23396890

  13. Power of Models in Longitudinal Study: Findings from a Full-Crossed Simulation Design

    ERIC Educational Resources Information Center

    Fang, Hua; Brooks, Gordon P.; Rizzo, Maria L.; Espy, Kimberly Andrews; Barcikowski, Robert S.

    2009-01-01

    Because the power properties of traditional repeated measures and hierarchical multivariate linear models have not been clearly determined in the balanced design for longitudinal studies in the literature, the authors present a power comparison study of traditional repeated measures and hierarchical multivariate linear models under 3…

  14. Meta-Analysis in Higher Education: An Illustrative Example Using Hierarchical Linear Modeling

    ERIC Educational Resources Information Center

    Denson, Nida; Seltzer, Michael H.

    2011-01-01

    The purpose of this article is to provide higher education researchers with an illustrative example of meta-analysis utilizing hierarchical linear modeling (HLM). This article demonstrates the step-by-step process of meta-analysis using a recently-published study examining the effects of curricular and co-curricular diversity activities on racial…

  15. Avoiding Boundary Estimates in Hierarchical Linear Models through Weakly Informative Priors

    ERIC Educational Resources Information Center

    Chung, Yeojin; Rabe-Hesketh, Sophia; Gelman, Andrew; Dorie, Vincent; Liu, Jinchen

    2012-01-01

    Hierarchical or multilevel linear models are widely used for longitudinal or cross-sectional data on students nested in classes and schools, and are particularly important for estimating treatment effects in cluster-randomized trials, multi-site trials, and meta-analyses. The models can allow for variation in treatment effects, as well as…

  16. The Aggregation of Single-Case Results Using Hierarchical Linear Models

    ERIC Educational Resources Information Center

    Van den Noortgate, Wim; Onghena, Patrick

    2007-01-01

    To investigate the generalizability of the results of single-case experimental studies, evaluating the effect of one or more treatments, in applied research various simultaneous and sequential replication strategies are used. We discuss one approach for aggregating the results for single-cases: the use of hierarchical linear models. This approach…

  17. Detecting a Change in School Performance: A Bayesian Analysis for a Multilevel Join Point Problem. CSE Technical Report 542.

    ERIC Educational Resources Information Center

    Thum, Yeow Meng; Bhattacharya, Suman Kumar

    To better describe individual behavior within a system, this paper uses a sample of longitudinal test scores from a large urban school system to consider hierarchical Bayes estimation of a multilevel linear regression model in which each individual regression slope of test score on time switches at some unknown point in time, "kj."…

  18. How Many Teachers Does It Take to Support a Student? Examining the Relationship between Teacher Support and Adverse Health Outcomes in High-Performing, Pressure-Cooker High Schools

    ERIC Educational Resources Information Center

    Conner, Jerusha O.; Miles, Sarah B.; Pope, Denise C.

    2014-01-01

    Although considerable research has demonstrated the importance of supportive teacher-student relationships to students' academic and nonacademic outcomes, few studies have explored these relationships in the context of high-performing high schools. Hierarchical linear modeling with a sample of 5,557 students from 14 different high-performing…

  19. Non-lethal assessment of freshwater mussel physiological response to changes in environmental factors

    USGS Publications Warehouse

    Fritts, Andrea K.; Peterson, James T.; Wisniewski, Jason M.; Bringolf, Robert B.

    2015-01-01

    The development of effective nonlethal biomonitoring techniques is imperative for the preservation of imperiled freshwater mussel populations. Changes in hemolymph chemistry profiles and tissue glycogen are potential biomarkers for nonlethally monitoring stress in mussels. We sampled three species in the Flint River Basin over 2 years to evaluate how these hemolymph and tissue biomarkers responded to environmental changes. We used hierarchical linear models to evaluate the relationships between variation in the biomarkers and environmental factors and found that the responses of the hemolymph and tissue parameters were strongly related to stream discharge. Shifts in alanine aminotransferase and glycogen showed the largest relations with discharge at the time of sampling, while magnesium levels were most explained by the discharge for 5 days prior to sampling. Aspartate aminotransferase, bicarbonate, and calcium showed the strongest relations with mean discharge for 15 days prior to sampling. The modeling results indicated that biomarker responses varied substantially among individuals of different size, sex, and species and illustrated the value of hierarchical modeling techniques to account for the inherent complexity of aquatic ecosystems.

  20. A Closer Look at Charter Schools Using Hierarchical Linear Modeling. NCES 2006-460

    ERIC Educational Resources Information Center

    Braun, Henry; Jenkins, Frank; Grigg, Wendy

    2006-01-01

    Charter schools are a relatively new, but fast-growing, phenomenon in American public education. As such, they merit the attention of all parties interested in the education of the nation's youth. The present report comprises two separate analyses. The first is a "combined analysis" in which hierarchical linear models (HLMs) were…

  1. A hierarchical linear model for tree height prediction.

    Treesearch

    Vicente J. Monleon

    2003-01-01

    Measuring tree height is a time-consuming process. Often, tree diameter is measured and height is estimated from a published regression model. Trees used to develop these models are clustered into stands, but this structure is ignored and independence is assumed. In this study, hierarchical linear models that account explicitly for the clustered structure of the data...

  2. Missing Data Treatments at the Second Level of Hierarchical Linear Models

    ERIC Educational Resources Information Center

    St. Clair, Suzanne W.

    2011-01-01

    The current study evaluated the performance of traditional versus modern MDTs in the estimation of fixed-effects and variance components for data missing at the second level of an hierarchical linear model (HLM) model across 24 different study conditions. Variables manipulated in the analysis included, (a) number of Level-2 variables with missing…

  3. Hierarchical Linear Modeling (HLM): An Introduction to Key Concepts within Cross-Sectional and Growth Modeling Frameworks. Technical Report #1308

    ERIC Educational Resources Information Center

    Anderson, Daniel

    2012-01-01

    This manuscript provides an overview of hierarchical linear modeling (HLM), as part of a series of papers covering topics relevant to consumers of educational research. HLM is tremendously flexible, allowing researchers to specify relations across multiple "levels" of the educational system (e.g., students, classrooms, schools, etc.).…

  4. What Is Wrong with ANOVA and Multiple Regression? Analyzing Sentence Reading Times with Hierarchical Linear Models

    ERIC Educational Resources Information Center

    Richter, Tobias

    2006-01-01

    Most reading time studies using naturalistic texts yield data sets characterized by a multilevel structure: Sentences (sentence level) are nested within persons (person level). In contrast to analysis of variance and multiple regression techniques, hierarchical linear models take the multilevel structure of reading time data into account. They…

  5. Examining Factors Affecting Science Achievement of Hong Kong in PISA 2006 Using Hierarchical Linear Modeling

    ERIC Educational Resources Information Center

    Lam, Terence Yuk Ping; Lau, Kwok Chi

    2014-01-01

    This study uses hierarchical linear modeling to examine the influence of a range of factors on the science performances of Hong Kong students in PISA 2006. Hong Kong has been consistently ranked highly in international science assessments, such as Programme for International Student Assessment and Trends in International Mathematics and Science…

  6. Analyzing Multilevel Data: Comparing Findings from Hierarchical Linear Modeling and Ordinary Least Squares Regression

    ERIC Educational Resources Information Center

    Rocconi, Louis M.

    2013-01-01

    This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student…

  7. Relationships among Instructional Practices, Students' Motivational Beliefs and Science Achievement in Taiwan Using Hierarchical Linear Modelling

    ERIC Educational Resources Information Center

    Liou, Pey-Yan; Ho, Hsin-Ning Jessie

    2018-01-01

    The purpose of this study is to examine students' perceptions of instructional practices in the classroom, and to further investigate the relationships among instructional practices, motivational beliefs and science achievement. Hierarchical linear modelling was utilised to examine the Trends in International Mathematics and Science Study 2007…

  8. Measuring Teacher Effectiveness through Hierarchical Linear Models: Exploring Predictors of Student Achievement and Truancy

    ERIC Educational Resources Information Center

    Subedi, Bidya Raj; Reese, Nancy; Powell, Randy

    2015-01-01

    This study explored significant predictors of student's Grade Point Average (GPA) and truancy (days absent), and also determined teacher effectiveness based on proportion of variance explained at teacher level model. We employed a two-level hierarchical linear model (HLM) with student and teacher data at level-1 and level-2 models, respectively.…

  9. Predicting Longitudinal Change in Language Production and Comprehension in Individuals with Down Syndrome: Hierarchical Linear Modeling.

    ERIC Educational Resources Information Center

    Chapman, Robin S.; Hesketh, Linda J.; Kistler, Doris J.

    2002-01-01

    Longitudinal change in syntax comprehension and production skill, measured over six years, was modeled in 31 individuals (ages 5-20) with Down syndrome. The best fitting Hierarchical Linear Modeling model of comprehension uses age and visual and auditory short-term memory as predictors of initial status, and age for growth trajectory. (Contains…

  10. Applying Hierarchical Linear Models (HLM) to Estimate the School and Children's Effects on Reading Achievement

    ERIC Educational Resources Information Center

    Liu, Xing

    2008-01-01

    The purpose of this study was to illustrate the use of Hierarchical Linear Models (HLM) to investigate the effects of school and children's attributes on children' reading achievement. In particular, this study was designed to: (1) develop the HLM models to determine the effects of school-level and child-level variables on children's reading…

  11. Parameter Recovery for the 1-P HGLLM with Non-Normally Distributed Level-3 Residuals

    ERIC Educational Resources Information Center

    Kara, Yusuf; Kamata, Akihito

    2017-01-01

    A multilevel Rasch model using a hierarchical generalized linear model is one approach to multilevel item response theory (IRT) modeling and is referred to as a one-parameter hierarchical generalized linear logistic model (1-P HGLLM). Although it has the flexibility to model nested structure of data with covariates, the model assumes the normality…

  12. Multilevel Mixture Kalman Filter

    NASA Astrophysics Data System (ADS)

    Guo, Dong; Wang, Xiaodong; Chen, Rong

    2004-12-01

    The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS) and integrates out the linear and Gaussian state variables conditioned on these indicators. Due to the marginalization process, the complexity of the mixture Kalman filter is quite high if the dimension of the indicator sampling space is high. In this paper, we address this difficulty by developing a new Monte Carlo sampling scheme, namely, the multilevel mixture Kalman filter. The basic idea is to make use of the multilevel or hierarchical structure of the space from which the indicator variables take values. That is, we draw samples in a multilevel fashion, beginning with sampling from the highest-level sampling space and then draw samples from the associate subspace of the newly drawn samples in a lower-level sampling space, until reaching the desired sampling space. Such a multilevel sampling scheme can be used in conjunction with the delayed estimation method, such as the delayed-sample method, resulting in delayed multilevel mixture Kalman filter. Examples in wireless communication, specifically the coherent and noncoherent 16-QAM over flat-fading channels, are provided to demonstrate the performance of the proposed multilevel mixture Kalman filter.

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

    PubMed

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

    2015-05-01

    We show how the hierarchical model for responses and response times as developed by van der Linden (2007), Fox, Klein Entink, and van der Linden (2007), Klein Entink, Fox, and van der Linden (2009), and Glas and van der Linden (2010) can be simplified to a generalized linear factor model with only the mild restriction that there is no hierarchical model at the item side. This result is valuable as it enables all well-developed modelling tools and extensions that come with these methods. We show that the restriction we impose on the hierarchical model does not influence parameter recovery under realistic circumstances. In addition, we present two illustrative real data analyses to demonstrate the practical benefits of our approach. © 2014 The British Psychological Society.

  14. A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

    PubMed Central

    Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence

    2013-01-01

    Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011

  15. The Effects Of Gender, Engineering Identification, and Engineering Program Expectancy On Engineering Career Intentions: Applying Hierarchical Linear Modeling (HLM) In Engineering Education Research

    ERIC Educational Resources Information Center

    Tendhar, Chosang; Paretti, Marie C.; Jones, Brett D.

    2017-01-01

    This study had three purposes and four hypotheses were tested. Three purposes: (1) To use hierarchical linear modeling (HLM) to investigate whether students' perceptions of their engineering career intentions changed over time; (2) To use HLM to test the effects of gender, engineering identification (the degree to which an individual values a…

  16. A Comprehensive Meta-Analysis of Triple P-Positive Parenting Program Using Hierarchical Linear Modeling: Effectiveness and Moderating Variables

    ERIC Educational Resources Information Center

    Nowak, Christoph; Heinrichs, Nina

    2008-01-01

    A meta-analysis encompassing all studies evaluating the impact of the Triple P-Positive Parenting Program on parent and child outcome measures was conducted in an effort to identify variables that moderate the program's effectiveness. Hierarchical linear models (HLM) with three levels of data were employed to analyze effect sizes. The results (N =…

  17. Complex Applications of HLM in Studies of Science and Mathematics Achievement: Cross-Classified Random Effects Models

    ERIC Educational Resources Information Center

    Moreno, Mario; Harwell, Michael; Guzey, S. Selcen; Phillips, Alison; Moore, Tamara J.

    2016-01-01

    Hierarchical linear models have become a familiar method for accounting for a hierarchical data structure in studies of science and mathematics achievement. This paper illustrates the use of cross-classified random effects models (CCREMs), which are likely less familiar. The defining characteristic of CCREMs is a hierarchical data structure…

  18. Will They Catch Up? The Role of Age at Cochlear Implantation in the Spoken Language Development of Children with Severe to Profound Hearing Loss

    ERIC Educational Resources Information Center

    Nicholas, Johanna Grant; Geers, Ann E.

    2007-01-01

    Purpose: The authors examined the benefits of younger cochlear implantation, longer cochlear implant use, and greater pre-implant aided hearing to spoken language at 3.5 and 4.5 years of age. Method: Language samples were obtained at ages 3.5 and 4.5 years from 76 children who received an implant by their 3rd birthday. Hierarchical linear modeling…

  19. The analysis of thin walled composite laminated helicopter rotor with hierarchical warping functions and finite element method

    NASA Astrophysics Data System (ADS)

    Zhu, Dechao; Deng, Zhongmin; Wang, Xingwei

    2001-08-01

    In the present paper, a series of hierarchical warping functions is developed to analyze the static and dynamic problems of thin walled composite laminated helicopter rotors composed of several layers with single closed cell. This method is the development and extension of the traditional constrained warping theory of thin walled metallic beams, which had been proved very successful since 1940s. The warping distribution along the perimeter of each layer is expanded into a series of successively corrective warping functions with the traditional warping function caused by free torsion or free bending as the first term, and is assumed to be piecewise linear along the thickness direction of layers. The governing equations are derived based upon the variational principle of minimum potential energy for static analysis and Rayleigh Quotient for free vibration analysis. Then the hierarchical finite element method is introduced to form a numerical algorithm. Both static and natural vibration problems of sample box beams are analyzed with the present method to show the main mechanical behavior of the thin walled composite laminated helicopter rotor.

  20. The Asian clam Corbicula fluminea as a biomonitor of trace element contamination: Accounting for different sources of variation using an hierarchical linear model

    USGS Publications Warehouse

    Shoults-Wilson, W. A.; Peterson, J.T.; Unrine, J.M.; Rickard, J.; Black, M.C.

    2009-01-01

    In the present study, specimens of the invasive clam, Corbicula fluminea, were collected above and below possible sources of potentially toxic trace elements (As, Cd, Cr, Cu, Hg, Pb, and Zn) in the Altamaha River system (Georgia, USA). Bioaccumulation of these elements was quantified, along with environmental (water and sediment) concentrations. Hierarchical linear models were used to account for variability in tissue concentrations related to environmental (site water chemistry and sediment characteristics) and individual (growth metrics) variables while identifying the strongest relations between these variables and trace element accumulation. The present study found significantly elevated concentrations of Cd, Cu, and Hg downstream of the outfall of kaolin-processing facilities, Zn downstream of a tire cording facility, and Cr downstream of both a nuclear power plant and a paper pulp mill. Models of the present study indicated that variation in trace element accumulation was linked to distance upstream from the estuary, dissolved oxygen, percentage of silt and clay in the sediment, elemental concentrations in sediment, shell length, and bivalve condition index. By explicitly modeling environmental variability, the Hierarchical linear modeling procedure allowed the identification of sites showing increased accumulation of trace elements that may have been caused by human activity. Hierarchical linear modeling is a useful tool for accounting for environmental and individual sources of variation in bioaccumulation studies. ?? 2009 SETAC.

  1. Bayesian Hierarchical Random Intercept Model Based on Three Parameter Gamma Distribution

    NASA Astrophysics Data System (ADS)

    Wirawati, Ika; Iriawan, Nur; Irhamah

    2017-06-01

    Hierarchical data structures are common throughout many areas of research. Beforehand, the existence of this type of data was less noticed in the analysis. The appropriate statistical analysis to handle this type of data is the hierarchical linear model (HLM). This article will focus only on random intercept model (RIM), as a subclass of HLM. This model assumes that the intercept of models in the lowest level are varied among those models, and their slopes are fixed. The differences of intercepts were suspected affected by some variables in the upper level. These intercepts, therefore, are regressed against those upper level variables as predictors. The purpose of this paper would demonstrate a proven work of the proposed two level RIM of the modeling on per capita household expenditure in Maluku Utara, which has five characteristics in the first level and three characteristics of districts/cities in the second level. The per capita household expenditure data in the first level were captured by the three parameters Gamma distribution. The model, therefore, would be more complex due to interaction of many parameters for representing the hierarchical structure and distribution pattern of the data. To simplify the estimation processes of parameters, the computational Bayesian method couple with Markov Chain Monte Carlo (MCMC) algorithm and its Gibbs Sampling are employed.

  2. Hierarchical structure in sharply divided phase space for the piecewise linear map

    NASA Astrophysics Data System (ADS)

    Akaishi, Akira; Aoki, Kazuki; Shudo, Akira

    2017-05-01

    We have studied a two-dimensional piecewise linear map to examine how the hierarchical structure of stable regions affects the slow dynamics in Hamiltonian systems. In the phase space there are infinitely many stable regions, each of which is polygonal-shaped, and the rest is occupied by chaotic orbits. By using symbolic representation of stable regions, a procedure to compute the edges of the polygons is presented. The stable regions are hierarchically distributed in phase space and the edges of the stable regions show the marginal instability. The cumulative distribution of the recurrence time obeys a power law as ˜t-2 , the same as the one for the system with phase space, which is composed of a single stable region and chaotic components. By studying the symbol sequence of recurrence trajectories, we show that the hierarchical structure of stable regions has no significant effect on the power-law exponent and that only the marginal instability on the boundary of stable regions is responsible for determining the exponent. We also discuss the relevance of the hierarchical structure to those in more generic chaotic systems.

  3. When linearity prevails over hierarchy in syntax

    PubMed Central

    Willer Gold, Jana; Arsenijević, Boban; Batinić, Mia; Becker, Michael; Čordalija, Nermina; Kresić, Marijana; Leko, Nedžad; Marušič, Franc Lanko; Milićev, Tanja; Milićević, Nataša; Mitić, Ivana; Peti-Stantić, Anita; Stanković, Branimir; Šuligoj, Tina; Tušek, Jelena; Nevins, Andrew

    2018-01-01

    Hierarchical structure has been cherished as a grammatical universal. We use experimental methods to show where linear order is also a relevant syntactic relation. An identical methodology and design were used across six research sites on South Slavic languages. Experimental results show that in certain configurations, grammatical production can in fact favor linear order over hierarchical structure. However, these findings are limited to coordinate structures and distinct from the kind of production errors found with comparable configurations such as “attraction” errors. The results demonstrate that agreement morphology may be computed in a series of steps, one of which is partly independent from syntactic hierarchy. PMID:29288218

  4. A hierarchical model for estimating change in American Woodcock populations

    USGS Publications Warehouse

    Sauer, J.R.; Link, W.A.; Kendall, W.L.; Kelley, J.R.; Niven, D.K.

    2008-01-01

    The Singing-Ground Survey (SGS) is a primary source of information on population change for American woodcock (Scolopax minor). We analyzed the SGS using a hierarchical log-linear model and compared the estimates of change and annual indices of abundance to a route regression analysis of SGS data. We also grouped SGS routes into Bird Conservation Regions (BCRs) and estimated population change and annual indices using BCRs within states and provinces as strata. Based on the hierarchical model?based estimates, we concluded that woodcock populations were declining in North America between 1968 and 2006 (trend = -0.9%/yr, 95% credible interval: -1.2, -0.5). Singing-Ground Survey results are generally similar between analytical approaches, but the hierarchical model has several important advantages over the route regression. Hierarchical models better accommodate changes in survey efficiency over time and space by treating strata, years, and observers as random effects in the context of a log-linear model, providing trend estimates that are derived directly from the annual indices. We also conducted a hierarchical model analysis of woodcock data from the Christmas Bird Count and the North American Breeding Bird Survey. All surveys showed general consistency in patterns of population change, but the SGS had the shortest credible intervals. We suggest that population management and conservation planning for woodcock involving interpretation of the SGS use estimates provided by the hierarchical model.

  5. Social determinants of childhood asthma symptoms: an ecological study in urban Latin America.

    PubMed

    Fattore, Gisel L; Santos, Carlos A T; Barreto, Mauricio L

    2014-04-01

    Asthma is an important public health problem in urban Latin America. This study aimed to analyze the role of socioeconomic and environmental factors as potential determinants of asthma symptoms prevalence in children from Latin American (LA) urban centers. We selected 31 LA urban centers with complete data, and an ecological analysis was performed. According to our theoretical framework, the explanatory variables were classified in three levels: distal, intermediate, and proximate. The association between variables in the three levels and prevalence of asthma symptoms was examined by bivariate and multivariate linear regression analysis weighed by sample size. In a second stage, we fitted several linear regression models introducing sequentially the variables according to the predefined hierarchy. In the final hierarchical model Gini Index, crowding, sanitation, variation in infant mortality rates and homicide rates, explained great part of the variance in asthma prevalence between centers (R(2) = 75.0 %). We found a strong association between socioeconomic and environmental variables and prevalence of asthma symptoms in LA urban children, and according to our hierarchical framework and the results found we suggest that social inequalities (measured by the Gini Index) is a central determinant to explain high prevalence of asthma in LA.

  6. Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

    PubMed

    Yu, Wenxi; Liu, Yang; Ma, Zongwei; Bi, Jun

    2017-08-01

    Using satellite-based aerosol optical depth (AOD) measurements and statistical models to estimate ground-level PM 2.5 is a promising way to fill the areas that are not covered by ground PM 2.5 monitors. The statistical models used in previous studies are primarily Linear Mixed Effects (LME) and Geographically Weighted Regression (GWR) models. In this study, we developed a new regression model between PM 2.5 and AOD using Gaussian processes in a Bayesian hierarchical setting. Gaussian processes model the stochastic nature of the spatial random effects, where the mean surface and the covariance function is specified. The spatial stochastic process is incorporated under the Bayesian hierarchical framework to explain the variation of PM 2.5 concentrations together with other factors, such as AOD, spatial and non-spatial random effects. We evaluate the results of our model and compare them with those of other, conventional statistical models (GWR and LME) by within-sample model fitting and out-of-sample validation (cross validation, CV). The results show that our model possesses a CV result (R 2  = 0.81) that reflects higher accuracy than that of GWR and LME (0.74 and 0.48, respectively). Our results indicate that Gaussian process models have the potential to improve the accuracy of satellite-based PM 2.5 estimates.

  7. Bayesian Correction for Misclassification in Multilevel Count Data Models.

    PubMed

    Nelson, Tyler; Song, Joon Jin; Chin, Yoo-Mi; Stamey, James D

    2018-01-01

    Covariate misclassification is well known to yield biased estimates in single level regression models. The impact on hierarchical count models has been less studied. A fully Bayesian approach to modeling both the misclassified covariate and the hierarchical response is proposed. Models with a single diagnostic test and with multiple diagnostic tests are considered. Simulation studies show the ability of the proposed model to appropriately account for the misclassification by reducing bias and improving performance of interval estimators. A real data example further demonstrated the consequences of ignoring the misclassification. Ignoring misclassification yielded a model that indicated there was a significant, positive impact on the number of children of females who observed spousal abuse between their parents. When the misclassification was accounted for, the relationship switched to negative, but not significant. Ignoring misclassification in standard linear and generalized linear models is well known to lead to biased results. We provide an approach to extend misclassification modeling to the important area of hierarchical generalized linear models.

  8. Non-linear clustering in the cold plus hot dark matter model

    NASA Astrophysics Data System (ADS)

    Bonometto, Silvio A.; Borgani, Stefano; Ghigna, Sebastiano; Klypin, Anatoly; Primack, Joel R.

    1995-03-01

    The main aim of this work is to find out if hierarchical scaling, observed in galaxy clustering, can be dynamically explained by studying N-body simulations. Previous analyses of dark matter (DM) particle distributions indicated heavy distortions with respect to the hierarchical pattern. Here, we shall describe how such distortions are to be interpreted and why they can be fully reconciled with the observed galaxy clustering. This aim is achieved by using high-resolution (512^3 grid-points) particle-mesh (PM) N-body simulations to follow the development of non-linear clustering in a Omega=1 universe, dominated either by cold dark matter (CDM) or by a mixture of cold+hot dark matter (CHDM) with Omega_cold=0.6, and Omega_hot=0.3 and Omega_baryon=0.1 a simulation box of side 100 Mpc (h=0.5) is used. We analyse two CHDM realizations with biasing factor b=1.5 (COBE normalization), starting from different initial random numbers, and compare them with CDM simulations with b=1 (COBE-compatible) and b=1.5. We evaluate high-order correlation functions and the void probability function (VPF). Correlation functions are obtained from both counts in cells and counts of neighbours. The analysis is carried out for DM particles and for galaxies identified as massive haloes of the evolved density field. We confirm that clustering of DM particles systematically exhibits deviations from hierarchical scaling, although the deviation increases somewhat in redshift space. Deviations from the hierarchical scaling of DM particles are found to be related to the spectrum shape, in a way that indicates that such distortions arise from finite sampling effects. We identify galaxy positions in the simulations and show that, quite differently from the DM particle background, galaxies follow hierarchical scaling (S_q=xi_q/& xgr^q-1_2=consta nt) far more closely, with reduced skewness and kurtosis coefficients S_3~2.5 and S_4~7.5, in general agreement with observational results. Unlike DM, the scaling of galaxy clustering is must marginally affected by redshift distortions and is obtained for both CDM and CHDM models. Hierarchical scaling in simulations is confirmed by VPF analysis. Also in this case, we find substantial agreement with observational findings.

  9. Hierarchical tone mapping for high dynamic range image visualization

    NASA Astrophysics Data System (ADS)

    Qiu, Guoping; Duan, Jiang

    2005-07-01

    In this paper, we present a computationally efficient, practically easy to use tone mapping techniques for the visualization of high dynamic range (HDR) images in low dynamic range (LDR) reproduction devices. The new method, termed hierarchical nonlinear linear (HNL) tone-mapping operator maps the pixels in two hierarchical steps. The first step allocates appropriate numbers of LDR display levels to different HDR intensity intervals according to the pixel densities of the intervals. The second step linearly maps the HDR intensity intervals to theirs allocated LDR display levels. In the developed HNL scheme, the assignment of LDR display levels to HDR intensity intervals is controlled by a very simple and flexible formula with a single adjustable parameter. We also show that our new operators can be used for the effective enhancement of ordinary images.

  10. Sampling schemes and parameter estimation for nonlinear Bernoulli-Gaussian sparse models

    NASA Astrophysics Data System (ADS)

    Boudineau, Mégane; Carfantan, Hervé; Bourguignon, Sébastien; Bazot, Michael

    2016-06-01

    We address the sparse approximation problem in the case where the data are approximated by the linear combination of a small number of elementary signals, each of these signals depending non-linearly on additional parameters. Sparsity is explicitly expressed through a Bernoulli-Gaussian hierarchical model in a Bayesian framework. Posterior mean estimates are computed using Markov Chain Monte-Carlo algorithms. We generalize the partially marginalized Gibbs sampler proposed in the linear case in [1], and build an hybrid Hastings-within-Gibbs algorithm in order to account for the nonlinear parameters. All model parameters are then estimated in an unsupervised procedure. The resulting method is evaluated on a sparse spectral analysis problem. It is shown to converge more efficiently than the classical joint estimation procedure, with only a slight increase of the computational cost per iteration, consequently reducing the global cost of the estimation procedure.

  11. Modelling habitat associations with fingernail clam (Family: Sphaeriidae) counts at multiple spatial scales using hierarchical count models

    USGS Publications Warehouse

    Gray, B.R.; Haro, R.J.; Rogala, J.T.; Sauer, J.S.

    2005-01-01

    1. Macroinvertebrate count data often exhibit nested or hierarchical structure. Examples include multiple measurements along each of a set of streams, and multiple synoptic measurements from each of a set of ponds. With data exhibiting hierarchical structure, outcomes at both sampling (e.g. Within stream) and aggregated (e.g. Stream) scales are often of interest. Unfortunately, methods for modelling hierarchical count data have received little attention in the ecological literature. 2. We demonstrate the use of hierarchical count models using fingernail clam (Family: Sphaeriidae) count data and habitat predictors derived from sampling and aggregated spatial scales. The sampling scale corresponded to that of a standard Ponar grab (0.052 m(2)) and the aggregated scale to impounded and backwater regions within 38-197 km reaches of the Upper Mississippi River. Impounded and backwater regions were resampled annually for 10 years. Consequently, measurements on clams were nested within years. Counts were treated as negative binomial random variates, and means from each resampling event as random departures from the impounded and backwater region grand means. 3. Clam models were improved by the addition of covariates that varied at both the sampling and regional scales. Substrate composition varied at the sampling scale and was associated with model improvements, and reductions (for a given mean) in variance at the sampling scale. Inorganic suspended solids (ISS) levels, measured in the summer preceding sampling, also yielded model improvements and were associated with reductions in variances at the regional rather than sampling scales. ISS levels were negatively associated with mean clam counts. 4. Hierarchical models allow hierarchically structured data to be modelled without ignoring information specific to levels of the hierarchy. In addition, information at each hierarchical level may be modelled as functions of covariates that themselves vary by and within levels. As a result, hierarchical models provide researchers and resource managers with a method for modelling hierarchical data that explicitly recognises both the sampling design and the information contained in the corresponding data.

  12. Unpacking the Complexity of Linear Equations from a Cognitive Load Theory Perspective

    ERIC Educational Resources Information Center

    Ngu, Bing Hiong; Phan, Huy P.

    2016-01-01

    The degree of element interactivity determines the complexity and therefore the intrinsic cognitive load of linear equations. The unpacking of linear equations at the level of operational and relational lines allows the classification of linear equations in a hierarchical level of complexity. Mapping similar operational and relational lines across…

  13. Libraries for Software Use on Peregrine | High-Performance Computing | NREL

    Science.gov Websites

    -specific libraries. Libraries List Name Description BLAS Basic Linear Algebra Subroutines, libraries only managing hierarchically structured data. LAPACK Standard Netlib offering for computational linear algebra

  14. Linear SFM: A hierarchical approach to solving structure-from-motion problems by decoupling the linear and nonlinear components

    NASA Astrophysics Data System (ADS)

    Zhao, Liang; Huang, Shoudong; Dissanayake, Gamini

    2018-07-01

    This paper presents a novel hierarchical approach to solving structure-from-motion (SFM) problems. The algorithm begins with small local reconstructions based on nonlinear bundle adjustment (BA). These are then joined in a hierarchical manner using a strategy that requires solving a linear least squares optimization problem followed by a nonlinear transform. The algorithm can handle ordered monocular and stereo image sequences. Two stereo images or three monocular images are adequate for building each initial reconstruction. The bulk of the computation involves solving a linear least squares problem and, therefore, the proposed algorithm avoids three major issues associated with most of the nonlinear optimization algorithms currently used for SFM: the need for a reasonably accurate initial estimate, the need for iterations, and the possibility of being trapped in a local minimum. Also, by summarizing all the original observations into the small local reconstructions with associated information matrices, the proposed Linear SFM manages to preserve all the information contained in the observations. The paper also demonstrates that the proposed problem formulation results in a sparse structure that leads to an efficient numerical implementation. The experimental results using publicly available datasets show that the proposed algorithm yields solutions that are very close to those obtained using a global BA starting with an accurate initial estimate. The C/C++ source code of the proposed algorithm is publicly available at https://github.com/LiangZhaoPKUImperial/LinearSFM.

  15. Problem Behaviors among Israeli Undergraduate Students: Applying Jessor’s Problem Behavior Theory among Young Adult Students

    PubMed Central

    Korn, Liat; Shaked, Yael; Fogel-Grinvald, Haya

    2014-01-01

    Purpose: The current study tested the applicability of Jessor’s problem behavior theory (PBT) in Ariel University. Methods: A structured, self-reported, anonymous questionnaire was administered to undergraduate students. The final study sample included 1,360 participants (882 females and 478 males, mean age 25, SD = 2.9, range = 17). Results: Findings indicated that the PBT was replicated in this sample. As shown from the hierarchal linear regression model, religiosity and high-academic achievements were found to be strong and significant protective factors that reduce risk behaviors. Among young and religious students, the personal vulnerability has almost no impact on involvement in risk behaviors. Conclusion: The PBT finds empirical support in this young adult undergraduate Israeli sample. PMID:25566519

  16. Multistep hierarchical self-assembly of chiral nanopore arrays

    PubMed Central

    Kim, Hanim; Lee, Sunhee; Shin, Tae Joo; Korblova, Eva; Walba, David M.; Clark, Noel A.; Lee, Sang Bok; Yoon, Dong Ki

    2014-01-01

    A series of simple hierarchical self-assembly steps achieve self-organization from the centimeter to the subnanometer-length scales in the form of square-centimeter arrays of linear nanopores, each one having a single chiral helical nanofilament of large internal surface area and interfacial interactions based on chiral crystalline molecular arrangements. PMID:25246585

  17. Hierarchical LiFePO4 with a controllable growth of the (010) facet for lithium-ion batteries.

    PubMed

    Guo, Binbin; Ruan, Hongcheng; Zheng, Cheng; Fei, Hailong; Wei, Mingdeng

    2013-09-27

    Hierarchically structured LiFePO4 was successfully synthesized by ionic liquid solvothermal method. These hierarchically structured LiFePO4 samples were constructed from nanostructured platelets with their (010) facets mainly exposed. To the best of our knowledge, facet control of a hierarchical LiFePO4 crystal has not been reported yet. Based on a series of experimental results, a tentative mechanism for the formation of these hierarchical structures was proposed. After these hierarchically structured LiFePO4 samples were coated with a thin carbon layer and used as cathode materials for lithium-ion batteries, they exhibited excellent high-rate discharge capability and cycling stability. For instance, a capacity of 95% can be maintained for the LiFePO4 sample at a rate as high as 20 C, even after 1000 cycles.

  18. STABILITY OF FMRI STRIATAL RESPONSE TO ALCOHOL CUES: A HIERARCHICAL LINEAR MODELING APPROACH

    PubMed Central

    Schacht, Joseph P.; Anton, Raymond F.; Randall, Patrick K.; Li, Xingbao; Henderson, Scott; Myrick, Hugh

    2011-01-01

    In functional magnetic resonance imaging (fMRI) studies of alcohol-dependent individuals, alcohol cues elicit activation of the ventral and dorsal aspects of the striatum (VS and DS), which are believed to underlie aspects of reward learning critical to the initiation and maintenance of alcohol dependence. Cue-elicited striatal activation may represent a biological substrate through which treatment efficacy may be measured. However, to be useful for this purpose, VS or DS activation must first demonstrate stability across time. Using hierarchical linear modeling (HLM), this study tested the stability of cue-elicited activation in anatomically and functionally defined regions of interest in bilateral VS and DS. Nine non-treatment-seeking alcohol-dependent participants twice completed an alcohol cue reactivity task during two fMRI scans separated by 14 days. HLM analyses demonstrated that, across all participants, alcohol cues elicited significant activation in each of the regions of interest. At the group level, these activations attenuated slightly between scans, but session-wise differences were not significant. Within-participants stability was best in the anatomically defined right VS and DS and in a functionally defined region that encompassed right caudate and putamen (intraclass correlation coefficients of .75, .81, and .76, respectively). Thus, within this small sample, alcohol cue-elicited fMRI activation had good reliability in the right striatum, though a larger sample is necessary to ensure generalizability and further evaluate stability. This study also demonstrates the utility of HLM analytic techniques for serial fMRI studies, in which separating within-participants variance (individual changes in activation) from between-participants factors (time or treatment) is critical. PMID:21316465

  19. Deep Hashing for Scalable Image Search.

    PubMed

    Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

    2017-05-01

    In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.

  20. Mental and Physical Health Correlates among Family Caregivers of Patients with Newly-Diagnosed Incurable Cancer: A Hierarchical Linear Regression Analysis

    PubMed Central

    Shaffer, Kelly M.; Jacobs, Jamie M.; Nipp, Ryan D.; Carr, Alaina; Jackson, Vicki A.; Park, Elyse R.; Pirl, William F.; El-Jawahri, Areej; Gallagher, Emily R.; Greer, Joseph A.; Temel, Jennifer S.

    2016-01-01

    Purpose Caregiver, relational, and patient factors have been associated with the health of family members and friends providing care to patients with early-stage cancer. Little research has examined whether findings extend to family caregivers of patients with incurable cancer, who experience unique and substantial caregiving burdens. We examined correlates of mental and physical health among caregivers of patients with newly-diagnosed incurable lung or non-colorectal gastrointestinal cancer. Methods At baseline for a trial of early palliative care, caregivers of participating patients (N=275) reported their mental and physical health (Medical Outcome Survey-Short Form-36); patients reported their quality of life (Functional Assessment of Cancer Therapy-General). Analyses used hierarchical linear regression with two-tailed significance tests. Results Caregivers’ mental health was worse than the U.S. national population (M=44.31, p<.001), yet their physical health was better (M=56.20, p<.001). Hierarchical regression analyses testing caregiver, relational, and patient factors simultaneously revealed that younger (B=0.31, p=.001), spousal caregivers (B=−8.70, p=.003), who cared for patients reporting low emotional well-being (B=0.51, p=.01) reported worse mental health; older (B=−0.17, p=.01) caregivers with low educational attainment (B=4.36, p<.001) who cared for patients reporting low social well-being (B=0.35, p=.05) reported worse physical health. Conclusions In this large sample of family caregivers of patients with incurable cancer, caregiver demographics, relational factors, and patient-specific factors were all related to caregiver mental health, while caregiver demographics were primarily associated with caregiver physical health. These findings help identify characteristics of family caregivers at highest risk of poor mental and physical health who may benefit from greater supportive care. PMID:27866337

  1. Abstract Linguistic Structure Correlates with Temporal Activity during Naturalistic Comprehension

    PubMed Central

    Brennan, Jonathan R.; Stabler, Edward P.; Van Wagenen, Sarah E.; Luh, Wen-Ming; Hale, John T.

    2016-01-01

    Neurolinguistic accounts of sentence comprehension identify a network of relevant brain regions, but do not detail the information flowing through them. We investigate syntactic information. Does brain activity implicate a computation over hierarchical grammars or does it simply reflect linear order, as in a Markov chain? To address this question, we quantify the cognitive states implied by alternative parsing models. We compare processing-complexity predictions from these states against fMRI timecourses from regions that have been implicated in sentence comprehension. We find that hierarchical grammars independently predict timecourses from left anterior and posterior temporal lobe. Markov models are predictive in these regions and across a broader network that includes the inferior frontal gyrus. These results suggest that while linear effects are wide-spread across the language network, certain areas in the left temporal lobe deal with abstract, hierarchical syntactic representations. PMID:27208858

  2. Improved Convergence and Robustness of USM3D Solutions on Mixed-Element Grids

    NASA Technical Reports Server (NTRS)

    Pandya, Mohagna J.; Diskin, Boris; Thomas, James L.; Frink, Neal T.

    2016-01-01

    Several improvements to the mixed-element USM3D discretization and defect-correction schemes have been made. A new methodology for nonlinear iterations, called the Hierarchical Adaptive Nonlinear Iteration Method, has been developed and implemented. The Hierarchical Adaptive Nonlinear Iteration Method provides two additional hierarchies around a simple and approximate preconditioner of USM3D. The hierarchies are a matrix-free linear solver for the exact linearization of Reynolds-averaged Navier-Stokes equations and a nonlinear control of the solution update. Two variants of the Hierarchical Adaptive Nonlinear Iteration Method are assessed on four benchmark cases, namely, a zero-pressure-gradient flat plate, a bump-in-channel configuration, the NACA 0012 airfoil, and a NASA Common Research Model configuration. The new methodology provides a convergence acceleration factor of 1.4 to 13 over the preconditioner-alone method representing the baseline solver technology.

  3. Improved Convergence and Robustness of USM3D Solutions on Mixed-Element Grids

    NASA Technical Reports Server (NTRS)

    Pandya, Mohagna J.; Diskin, Boris; Thomas, James L.; Frinks, Neal T.

    2016-01-01

    Several improvements to the mixed-elementUSM3Ddiscretization and defect-correction schemes have been made. A new methodology for nonlinear iterations, called the Hierarchical Adaptive Nonlinear Iteration Method, has been developed and implemented. The Hierarchical Adaptive Nonlinear Iteration Method provides two additional hierarchies around a simple and approximate preconditioner of USM3D. The hierarchies are a matrix-free linear solver for the exact linearization of Reynolds-averaged Navier-Stokes equations and a nonlinear control of the solution update. Two variants of the Hierarchical Adaptive Nonlinear Iteration Method are assessed on four benchmark cases, namely, a zero-pressure-gradient flat plate, a bump-in-channel configuration, the NACA 0012 airfoil, and a NASA Common Research Model configuration. The new methodology provides a convergence acceleration factor of 1.4 to 13 over the preconditioner-alone method representing the baseline solver technology.

  4. Hierarchical Bayes approach for subgroup analysis.

    PubMed

    Hsu, Yu-Yi; Zalkikar, Jyoti; Tiwari, Ram C

    2017-01-01

    In clinical data analysis, both treatment effect estimation and consistency assessment are important for a better understanding of the drug efficacy for the benefit of subjects in individual subgroups. The linear mixed-effects model has been used for subgroup analysis to describe treatment differences among subgroups with great flexibility. The hierarchical Bayes approach has been applied to linear mixed-effects model to derive the posterior distributions of overall and subgroup treatment effects. In this article, we discuss the prior selection for variance components in hierarchical Bayes, estimation and decision making of the overall treatment effect, as well as consistency assessment of the treatment effects across the subgroups based on the posterior predictive p-value. Decision procedures are suggested using either the posterior probability or the Bayes factor. These decision procedures and their properties are illustrated using a simulated example with normally distributed response and repeated measurements.

  5. Hierarchical Rhetorical Sentence Categorization for Scientific Papers

    NASA Astrophysics Data System (ADS)

    Rachman, G. H.; Khodra, M. L.; Widyantoro, D. H.

    2018-03-01

    Important information in scientific papers can be composed of rhetorical sentences that is structured from certain categories. To get this information, text categorization should be conducted. Actually, some works in this task have been completed by employing word frequency, semantic similarity words, hierarchical classification, and the others. Therefore, this paper aims to present the rhetorical sentence categorization from scientific paper by employing TF-IDF and Word2Vec to capture word frequency and semantic similarity words and employing hierarchical classification. Every experiment is tested in two classifiers, namely Naïve Bayes and SVM Linear. This paper shows that hierarchical classifier is better than flat classifier employing either TF-IDF or Word2Vec, although it increases only almost 2% from 27.82% when using flat classifier until 29.61% when using hierarchical classifier. It shows also different learning model for child-category can be built by hierarchical classifier.

  6. Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

    PubMed

    Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

    In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

  7. Sample size in psychological research over the past 30 years.

    PubMed

    Marszalek, Jacob M; Barber, Carolyn; Kohlhart, Julie; Holmes, Cooper B

    2011-04-01

    The American Psychological Association (APA) Task Force on Statistical Inference was formed in 1996 in response to a growing body of research demonstrating methodological issues that threatened the credibility of psychological research, and made recommendations to address them. One issue was the small, even dramatically inadequate, size of samples used in studies published by leading journals. The present study assessed the progress made since the Task Force's final report in 1999. Sample sizes reported in four leading APA journals in 1955, 1977, 1995, and 2006 were compared using nonparametric statistics, while data from the last two waves were fit to a hierarchical generalized linear growth model for more in-depth analysis. Overall, results indicate that the recommendations for increasing sample sizes have not been integrated in core psychological research, although results slightly vary by field. This and other implications are discussed in the context of current methodological critique and practice.

  8. Trimethylamine Sensors Based on Au-Modified Hierarchical Porous Single-Crystalline ZnO Nanosheets.

    PubMed

    Meng, Fanli; Zheng, Hanxiong; Sun, Yufeng; Li, Minqiang; Liu, Jinhuai

    2017-06-22

    It is of great significance for dynamic monitoring of foods in storage or during the transportation process through on-line detecting trimethylamine (TMA). Here, TMA were sensitively detected by Au-modified hierarchical porous single-crystalline ZnO nanosheets (HPSCZNs)-based sensors. The HPSCZNs were synthesized through a one-pot wet-chemical method followed by an annealing treatment. Polyethyleneimine (PEI) was used to modify the surface of the HPSCZNs, and then the PEI-modified samples were mixed with Au nanoparticles (NPs) sol solution. Electrostatic interactions drive Au nanoparticles loading onto the surface of the HPSCZNs. The Au-modified HPSCZNs were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and energy dispersive spectrum (EDS), respectively. The results show that Au-modified HPSCZNs-based sensors exhibit a high response to TMA. The linear range is from 10 to 300 ppb; while the detection limit is 10 ppb, which is the lowest value to our knowledge.

  9. Trimethylamine Sensors Based on Au-Modified Hierarchical Porous Single-Crystalline ZnO Nanosheets

    PubMed Central

    Zheng, Hanxiong; Sun, Yufeng; Li, Minqiang; Liu, Jinhuai

    2017-01-01

    It is of great significance for dynamic monitoring of foods in storage or during the transportation process through on-line detecting trimethylamine (TMA). Here, TMA were sensitively detected by Au-modified hierarchical porous single-crystalline ZnO nanosheets (HPSCZNs)-based sensors. The HPSCZNs were synthesized through a one-pot wet-chemical method followed by an annealing treatment. Polyethyleneimine (PEI) was used to modify the surface of the HPSCZNs, and then the PEI-modified samples were mixed with Au nanoparticles (NPs) sol solution. Electrostatic interactions drive Au nanoparticles loading onto the surface of the HPSCZNs. The Au-modified HPSCZNs were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and energy dispersive spectrum (EDS), respectively. The results show that Au-modified HPSCZNs-based sensors exhibit a high response to TMA. The linear range is from 10 to 300 ppb; while the detection limit is 10 ppb, which is the lowest value to our knowledge. PMID:28640226

  10. Hypertext comprehension of deaf and hard-of-hearing students and students with specific language impairment.

    PubMed

    Blom, Helen; Segers, Eliane; Hermans, Daan; Knoors, Harry; Verhoeven, Ludo

    2017-02-01

    This paper provides insight into the reading comprehension of hierarchically structured hypertexts within D/HH students and students with SLI. To our knowledge, it is the first study on hypertext comprehension in D/HH students and students with SLI, and it also considers the role of working memory. We compared hypertext versus linear text comprehension in D/HH students and students with SLI versus younger students without language problems who had a similar level of decoding and vocabulary. The results demonstrated no difference in text comprehension between the hierarchically structured hypertext and the linear text. Text comprehension of D/HH students and students with SLI was comparable to that of the students without language problems. In addition, there was a similar positive predictive value of visuospatial and not verbal working memory on hypertext comprehension for all three groups. The findings implicate that educational settings can make use of hierarchically structured hypertexts as well as linear texts and that children can navigate in the digital world from young age on, even if language or working memory problems are present. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

    ERIC Educational Resources Information Center

    Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

    2006-01-01

    Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

  12. Hierarchical drivers of reef-fish metacommunity structure.

    PubMed

    MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P

    2009-01-01

    Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at multiple spatial scales; and (3) inter-atoll connectedness was poorly correlated with the nonrandom clustering of reef-fish species. These results demonstrate the importance of modeling hierarchical data and processes in understanding reef-fish metacommunity structure.

  13. Evaluating the Impacts of ICT Use: A Multi-Level Analysis with Hierarchical Linear Modeling

    ERIC Educational Resources Information Center

    Song, Hae-Deok; Kang, Taehoon

    2012-01-01

    The purpose of this study is to evaluate the impacts of ICT use on achievements by considering not only ICT use, but also the process and background variables that influence ICT use at both the student- and school-level. This study was conducted using data from the 2010 Survey of Seoul Education Longitudinal Research. A Hierarchical Linear…

  14. An adaptive sparse-grid high-order stochastic collocation method for Bayesian inference in groundwater reactive transport modeling

    NASA Astrophysics Data System (ADS)

    Zhang, Guannan; Lu, Dan; Ye, Ming; Gunzburger, Max; Webster, Clayton

    2013-10-01

    Bayesian analysis has become vital to uncertainty quantification in groundwater modeling, but its application has been hindered by the computational cost associated with numerous model executions required by exploring the posterior probability density function (PPDF) of model parameters. This is particularly the case when the PPDF is estimated using Markov Chain Monte Carlo (MCMC) sampling. In this study, a new approach is developed to improve the computational efficiency of Bayesian inference by constructing a surrogate of the PPDF, using an adaptive sparse-grid high-order stochastic collocation (aSG-hSC) method. Unlike previous works using first-order hierarchical basis, this paper utilizes a compactly supported higher-order hierarchical basis to construct the surrogate system, resulting in a significant reduction in the number of required model executions. In addition, using the hierarchical surplus as an error indicator allows locally adaptive refinement of sparse grids in the parameter space, which further improves computational efficiency. To efficiently build the surrogate system for the PPDF with multiple significant modes, optimization techniques are used to identify the modes, for which high-probability regions are defined and components of the aSG-hSC approximation are constructed. After the surrogate is determined, the PPDF can be evaluated by sampling the surrogate system directly without model execution, resulting in improved efficiency of the surrogate-based MCMC compared with conventional MCMC. The developed method is evaluated using two synthetic groundwater reactive transport models. The first example involves coupled linear reactions and demonstrates the accuracy of our high-order hierarchical basis approach in approximating high-dimensional posteriori distribution. The second example is highly nonlinear because of the reactions of uranium surface complexation, and demonstrates how the iterative aSG-hSC method is able to capture multimodal and non-Gaussian features of PPDF caused by model nonlinearity. Both experiments show that aSG-hSC is an effective and efficient tool for Bayesian inference.

  15. The Relationship Between Reported Sleep Quality and Sleep Hygiene in Italian and American Adolescents

    PubMed Central

    LeBourgeois, Monique K.; Giannotti, Flavia; Cortesi, Flavia; Wolfson, Amy R.; Harsh, John

    2014-01-01

    Objective The purpose of the study was to examine the relationship between self-reported sleep quality and sleep hygiene in Italian and American adolescents and to assess whether sleep-hygiene practices mediate the relationship between culture and sleep quality. Methods Two nonprobability samples were collected from public schools in Rome, Italy, and Hattiesburg, Mississippi. Students completed the following self-report measures: Adolescent Sleep-Wake Scale, Adolescent Sleep Hygiene Scale, Pubertal Developmental Scale, and Morningness/Eveningness Scale. Results The final sample included 776 Italian and 572 American adolescents 12 to 17 years old. Italian adolescents reported much better sleep hygiene and substantially better sleep quality than American adolescents. A moderate-to-strong linear relationship was found between sleep hygiene and sleep quality in both samples. Separate hierarchical multiple regression analyses were performed on both samples. Demographic and individual characteristics explained a significant proportion of the variance in sleep quality (Italians: 18%; Americans: 25%), and the addition of sleep-hygiene domains explained significantly more variance in sleep quality (Italians: 17%; Americans: 16%). A final hierarchical multiple regression analysis with both samples combined showed that culture (Italy versus United States) only explained 0.8% of the variance in sleep quality after controlling for sleep hygiene and all other variables. Conclusions Cross-cultural differences in sleep quality, for the most part, were due to differences in sleep-hygiene practices. Sleep hygiene is an important predictor of sleep quality in Italian and American adolescents, thus supporting the implementation and evaluation of educational programs on good sleep-hygiene practices. PMID:15866860

  16. The Effect of the Presence of Others on Caloric Intake in Homebound Older Adults

    PubMed Central

    Locher, Julie L.; Robinson, Caroline O.; Roth, David L.; Ritchie, Christine S.; Burgio, Kathryn L.

    2008-01-01

    Background Undernutrition in homebound older adults is a significant problem. The purpose of this study was to investigate the effect of the presence of others, both within the household and during meals, on caloric intake in homebound older adults. Methods In-depth interviews and three 24-hour dietary recalls were obtained from 50 older adults who were receiving home health services. Descriptive statistics were used to characterize participants, and hierarchical linear modeling was performed to evaluate predictors of caloric intake per meal. Results Participants’ mean age was 77. Females composed 65% and African Americans composed 42% of the sample. Analyses are based on 553 meal observations. The majority (84%) of participants consumed all meals for each of the 3 days of data collection; however, they consumed an average of only 1305 calories per day. Hierarchical linear modeling analysis indicated that persons who had others present during meals consumed an average of 114.0 calories more per meal than those who ate alone (p = .009) and that women consumed 76.7 fewer calories per meal than did men (p = .045). The presence of others within the household had no effect on caloric intake. Conclusion This research suggests that a simple and inexpensive way to increase caloric intake in homebound older adults is to make arrangements for family members or caregivers to eat with them. PMID:16339337

  17. Personalized Medicine Enrichment Design for DHA Supplementation Clinical Trial.

    PubMed

    Lei, Yang; Mayo, Matthew S; Carlson, Susan E; Gajewski, Byron J

    2017-03-01

    Personalized medicine aims to match patient subpopulation to the most beneficial treatment. The purpose of this study is to design a prospective clinical trial in which we hope to achieve the highest level of confirmation in identifying and making treatment recommendations for subgroups, when the risk levels in the control arm can be ordered. This study was motivated by our goal to identify subgroups in a DHA (docosahexaenoic acid) supplementation trial to reduce preterm birth (gestational age<37 weeks) rate. We performed a meta-analysis to obtain informative prior distributions and simulated operating characteristics to ensure that overall Type I error rate was close to 0.05 in designs with three different models: independent, hierarchical, and dynamic linear models. We performed simulations and sensitivity analysis to examine the subgroup power of models and compared results to a chi-square test. We performed simulations under two hypotheses: a large overall treatment effect and a small overall treatment effect. Within each hypothesis, we designed three different subgroup effects scenarios where resulting subgroup rates are linear, flat, or nonlinear. When the resulting subgroup rates are linear or flat, dynamic linear model appeared to be the most powerful method to identify the subgroups with a treatment effect. It also outperformed other methods when resulting subgroup rates are nonlinear and the overall treatment effect is big. When the resulting subgroup rates are nonlinear and the overall treatment effect is small, hierarchical model and chi-square test did better. Compared to independent and hierarchical models, dynamic linear model tends to be relatively robust and powerful when the control arm has ordinal risk subgroups.

  18. School system evaluation by value added analysis under endogeneity.

    PubMed

    Manzi, Jorge; San Martín, Ernesto; Van Bellegem, Sébastien

    2014-01-01

    Value added is a common tool in educational research on effectiveness. It is often modeled as a (prediction of a) random effect in a specific hierarchical linear model. This paper shows that this modeling strategy is not valid when endogeneity is present. Endogeneity stems, for instance, from a correlation between the random effect in the hierarchical model and some of its covariates. This paper shows that this phenomenon is far from exceptional and can even be a generic problem when the covariates contain the prior score attainments, a typical situation in value added modeling. Starting from a general, model-free definition of value added, the paper derives an explicit expression of the value added in an endogeneous hierarchical linear Gaussian model. Inference on value added is proposed using an instrumental variable approach. The impact of endogeneity on the value added and the estimated value added is calculated accurately. This is also illustrated on a large data set of individual scores of about 200,000 students in Chile.

  19. [Fast optimization of stepwise gradient conditions for ternary mobile phase in reversed-phase high performance liquid chromatography].

    PubMed

    Shan, Yi-chu; Zhang, Yu-kui; Zhao, Rui-huan

    2002-07-01

    In high performance liquid chromatography, it is necessary to apply multi-composition gradient elution for the separation of complex samples such as environmental and biological samples. Multivariate stepwise gradient elution is one of the most efficient elution modes, because it combines the high selectivity of multi-composition mobile phase and shorter analysis time of gradient elution. In practical separations, the separation selectivity of samples can be effectively adjusted by using ternary mobile phase. For the optimization of these parameters, the retention equation of samples must be obtained at first. Traditionally, several isocratic experiments are used to get the retention equation of solute. However, it is time consuming especially for the separation of complex samples with a wide range of polarity. A new method for the fast optimization of ternary stepwise gradient elution was proposed based on the migration rule of solute in column. First, the coefficients of retention equation of solute are obtained by running several linear gradient experiments, then the optimal separation conditions are searched according to the hierarchical chromatography response function which acts as the optimization criterion. For each kind of organic modifier, two initial linear gradient experiments are used to obtain the primary coefficients of retention equation of each solute. For ternary mobile phase, only four linear gradient runs are needed to get the coefficients of retention equation. Then the retention times of solutes under arbitrary mobile phase composition can be predicted. The initial optimal mobile phase composition is obtained by resolution mapping for all of the solutes. A hierarchical chromatography response function is used to evaluate the separation efficiencies and search the optimal elution conditions. In subsequent optimization, the migrating distance of solute in the column is considered to decide the mobile phase composition and sustaining time of the latter steps until all the solutes are eluted out. Thus the first stepwise gradient elution conditions are predicted. If the resolution of samples under the predicted optimal separation conditions is satisfactory, the optimization procedure is stopped; otherwise, the coefficients of retention equation are adjusted according to the experimental results under the previously predicted elution conditions. Then the new stepwise gradient elution conditions are predicted repeatedly until satisfactory resolution is obtained. Normally, the satisfactory separation conditions can be found only after six experiments by using the proposed method. In comparison with the traditional optimization method, the time needed to finish the optimization procedure can be greatly reduced. The method has been validated by its application to the separation of several samples such as amino acid derivatives, aromatic amines, in which satisfactory separations were obtained with predicted resolution.

  20. Coevolution of dependency distance, hierarchical structure and word order. Comment on "Dependency distance: a new perspective on syntactic patterns in natural languages" by Haitao Liu et al.

    NASA Astrophysics Data System (ADS)

    Jing, Yingqi

    2017-07-01

    Exploring the relationships between structural rules and their linearization constraints have been a central issue in formal syntax and linguistic typology [1]. Liu et al. give a historical overview of the investigation of dependency distance minimization (DDM) in various fields, and specify its potential connections with the graphic patterns of syntactic structure and the linear ordering of words and constituents in real sentences [2]. This comment focuses on discussing the relations between dependency distance (DD), hierarchical structure and word order, and advocates further study on the coevolution of these traits in language histories.

  1. Measuring the hierarchy of feedforward networks

    NASA Astrophysics Data System (ADS)

    Corominas-Murtra, Bernat; Rodríguez-Caso, Carlos; Goñi, Joaquín; Solé, Ricard

    2011-03-01

    In this paper we explore the concept of hierarchy as a quantifiable descriptor of ordered structures, departing from the definition of three conditions to be satisfied for a hierarchical structure: order, predictability, and pyramidal structure. According to these principles, we define a hierarchical index taking concepts from graph and information theory. This estimator allows to quantify the hierarchical character of any system susceptible to be abstracted in a feedforward causal graph, i.e., a directed acyclic graph defined in a single connected structure. Our hierarchical index is a balance between this predictability and pyramidal condition by the definition of two entropies: one attending the onward flow and the other for the backward reversion. We show how this index allows to identify hierarchical, antihierarchical, and nonhierarchical structures. Our formalism reveals that departing from the defined conditions for a hierarchical structure, feedforward trees and the inverted tree graphs emerge as the only causal structures of maximal hierarchical and antihierarchical systems respectively. Conversely, null values of the hierarchical index are attributed to a number of different configuration networks; from linear chains, due to their lack of pyramid structure, to full-connected feedforward graphs where the diversity of onward pathways is canceled by the uncertainty (lack of predictability) when going backward. Some illustrative examples are provided for the distinction among these three types of hierarchical causal graphs.

  2. A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

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

    Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter

    In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

  3. A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

    DOE PAGES

    Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter; ...

    2016-06-30

    In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

  4. The Joker: A Custom Monte Carlo Sampler for Binary-star and Exoplanet Radial Velocity Data

    NASA Astrophysics Data System (ADS)

    Price-Whelan, Adrian M.; Hogg, David W.; Foreman-Mackey, Daniel; Rix, Hans-Walter

    2017-03-01

    Given sparse or low-quality radial velocity measurements of a star, there are often many qualitatively different stellar or exoplanet companion orbit models that are consistent with the data. The consequent multimodality of the likelihood function leads to extremely challenging search, optimization, and Markov chain Monte Carlo (MCMC) posterior sampling over the orbital parameters. Here we create a custom Monte Carlo sampler for sparse or noisy radial velocity measurements of two-body systems that can produce posterior samples for orbital parameters even when the likelihood function is poorly behaved. The six standard orbital parameters for a binary system can be split into four nonlinear parameters (period, eccentricity, argument of pericenter, phase) and two linear parameters (velocity amplitude, barycenter velocity). We capitalize on this by building a sampling method in which we densely sample the prior probability density function (pdf) in the nonlinear parameters and perform rejection sampling using a likelihood function marginalized over the linear parameters. With sparse or uninformative data, the sampling obtained by this rejection sampling is generally multimodal and dense. With informative data, the sampling becomes effectively unimodal but too sparse: in these cases we follow the rejection sampling with standard MCMC. The method produces correct samplings in orbital parameters for data that include as few as three epochs. The Joker can therefore be used to produce proper samplings of multimodal pdfs, which are still informative and can be used in hierarchical (population) modeling. We give some examples that show how the posterior pdf depends sensitively on the number and time coverage of the observations and their uncertainties.

  5. The swan-song phenomenon: last-works effects for 172 classical composers.

    PubMed

    Simonton, D K

    1989-03-01

    Creative individuals approaching their final years of life may undergo a transformation in outlook that is reflected in their last works. This hypothesized effect was quantitatively assessed for an extensive sample of 1,919 works by 172 classical composers. The works were independently gauged on seven aesthetic attributes (melodic originality, melodic variation, repertoire popularity, aesthetic significance, listener accessibility, performance duration, and thematic size), and potential last-works effects were operationally defined two separate ways (linearly and exponentially). Statistical controls were introduced for both longitudinal changes (linear, quadratic, and cubic age functions) and individual differences (eminence and lifetime productivity). Hierarchical regression analyses indicated that composers' swan songs tend to score lower in melodic originality and performance duration but higher in repertoire popularity and aesthetic significance. These last-works effects survive control for total compositional output, eminence, and most significantly, the composer's age when the last works were created.

  6. Understanding the Positive Role of Neighborhood Socioeconomic Advantage in Achievement: The Contribution of the Home, Child Care and School Environments

    PubMed Central

    Dupéré, Véronique; Leventhal, Tama; Crosnoe, Robert; Dion, Éric

    2011-01-01

    The goal of this study was to examine the mechanisms underlying associations between neighborhood socioeconomic advantage and children’s achievement trajectories between 54 months and 15 years old. Results of hierarchical linear growth models based on a diverse sample of 1,364 children indicate that neighborhood socioeconomic advantage was non-linearly associated with youths’ initial vocabulary and reading scores, such that the presence of educated, affluent professionals in the neighborhood had a favorable association with children’s achievement among those in less advantaged neighborhoods until it leveled off at moderate levels of advantage. A similar tendency was observed for math achievement. The quality of the home and child care environments as well as school advantage partially explained these associations. The findings suggest that multiple environments need to be considered simultaneously for understanding neighborhood-achievement links. PMID:20822235

  7. Nonexpansiveness of a linearized augmented Lagrangian operator for hierarchical convex optimization

    NASA Astrophysics Data System (ADS)

    Yamagishi, Masao; Yamada, Isao

    2017-04-01

    Hierarchical convex optimization concerns two-stage optimization problems: the first stage problem is a convex optimization; the second stage problem is the minimization of a convex function over the solution set of the first stage problem. For the hierarchical convex optimization, the hybrid steepest descent method (HSDM) can be applied, where the solution set of the first stage problem must be expressed as the fixed point set of a certain nonexpansive operator. In this paper, we propose a nonexpansive operator that yields a computationally efficient update when it is plugged into the HSDM. The proposed operator is inspired by the update of the linearized augmented Lagrangian method. It is applicable to characterize the solution set of recent sophisticated convex optimization problems found in the context of inverse problems, where the sum of multiple proximable convex functions involving linear operators must be minimized to incorporate preferable properties into the minimizers. For such a problem formulation, there has not yet been reported any nonexpansive operator that yields an update free from the inversions of linear operators in cases where it is utilized in the HSDM. Unlike previously known nonexpansive operators, the proposed operator yields an inversion-free update in such cases. As an application of the proposed operator plugged into the HSDM, we also present, in the context of the so-called superiorization, an algorithmic solution to a convex optimization problem over the generalized convex feasible set where the intersection of the hard constraints is not necessarily simple.

  8. Diagnostics for generalized linear hierarchical models in network meta-analysis.

    PubMed

    Zhao, Hong; Hodges, James S; Carlin, Bradley P

    2017-09-01

    Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's substantive conclusions. In this paper, we examine such discrepancies from a diagnostic point of view. Our methods seek to detect influential and outlying observations in NMA at a trial-by-arm level. These observations may have a large effect on the parameter estimates in NMA, or they may deviate markedly from other observations. We develop formal diagnostics for a Bayesian hierarchical model to check the effect of deleting any observation. Diagnostics are specified for generalized linear hierarchical NMA models and investigated for both published and simulated datasets. Results from our example dataset using either contrast- or arm-based models and from the simulated datasets indicate that the sources of inconsistency in NMA tend not to be influential, though results from the example dataset suggest that they are likely to be outliers. This mimics a familiar result from linear model theory, in which outliers with low leverage are not influential. Future extensions include incorporating baseline covariates and individual-level patient data. Copyright © 2017 John Wiley & Sons, Ltd.

  9. Hierarchical clustering in chameleon f(R) gravity

    NASA Astrophysics Data System (ADS)

    Hellwing, Wojciech A.; Li, Baojiu; Frenk, Carlos S.; Cole, Shaun

    2013-11-01

    We use a suite of high-resolution state-of-the-art N-body dark matter simulations of chameleon f(R) gravity to study the higher order volume-averaged correlation functions overline{ξ _n} together with the hierarchical nth-order correlation amplitudes S_n=overline{ξ }_n/overline{ξ }_2^{n-1} and density distribution functions (PDF). We show that under the non-linear modifications of gravity the hierarchical scaling of the reduced cumulants is preserved. This is however characterized by significant changes in the values of both overline{ξ _n} and Sn and their scale dependence with respect to General Relativity gravity (GR). In addition, we measure a significant increase of the non-linear σ8 parameter reaching 14, 5 and 0.5 per cent in excess of the GR value for the three flavours of our f(R) models. We further note that the values of the reduced cumulants up to order n = 9 are significantly increased in f(R) gravity for all our models at small scales R ≲ 30 h-1 Mpc. In contrast, the values of the hierarchical amplitudes, Sn, are smaller in f(R) indicating that the modified gravity density distribution functions are deviating from the GR case. Furthermore, we find that the redshift evolution of relative deviations of the f(R) hierarchical correlation amplitudes is fastest at high and moderate redshifts 1 ≤ z ≤ 4. The growth of these deviations significantly slows down in the low-redshift universe. We also compute the PDFs and show that for scales below ˜20 h-1 Mpc, they are significantly shifted in f(R) gravity towards the low densities. Finally, we discuss the implications of our theoretical predictions for measurements of the hierarchical clustering in galaxy redshift surveys, including the important problems of the galaxy biasing and redshift space distortions.

  10. A hierarchical preconditioner for the electric field integral equation on unstructured meshes based on primal and dual Haar bases

    NASA Astrophysics Data System (ADS)

    Adrian, S. B.; Andriulli, F. P.; Eibert, T. F.

    2017-02-01

    A new hierarchical basis preconditioner for the electric field integral equation (EFIE) operator is introduced. In contrast to existing hierarchical basis preconditioners, it works on arbitrary meshes and preconditions both the vector and the scalar potential within the EFIE operator. This is obtained by taking into account that the vector and the scalar potential discretized with loop-star basis functions are related to the hypersingular and the single layer operator (i.e., the well known integral operators from acoustics). For the single layer operator discretized with piecewise constant functions, a hierarchical preconditioner can easily be constructed. Thus the strategy we propose in this work for preconditioning the EFIE is the transformation of the scalar and the vector potential into operators equivalent to the single layer operator and to its inverse. More specifically, when the scalar potential is discretized with star functions as source and testing functions, the resulting matrix is a single layer operator discretized with piecewise constant functions and multiplied left and right with two additional graph Laplacian matrices. By inverting these graph Laplacian matrices, the discretized single layer operator is obtained, which can be preconditioned with the hierarchical basis. Dually, when the vector potential is discretized with loop functions, the resulting matrix can be interpreted as a hypersingular operator discretized with piecewise linear functions. By leveraging on a scalar Calderón identity, we can interpret this operator as spectrally equivalent to the inverse single layer operator. Then we use a linear-in-complexity, closed-form inverse of the dual hierarchical basis to precondition the hypersingular operator. The numerical results show the effectiveness of the proposed preconditioner and the practical impact of theoretical developments in real case scenarios.

  11. What predicts recovery orientation in county departments of mental health? A pilot study.

    PubMed

    Brown, Timothy T; Mahoney, Christine B; Adams, Neal; Felton, Mistique; Pareja, Candy

    2010-09-01

    In this pilot study we examined the determinants of recovery orientation among employees and influential stakeholders in a sample of 12 county departments of mental health in California. A two-level hierarchical linear model with random intercepts was estimated. Analyses show that recovery orientation has a U-shaped relationship with the age of staff/influential stakeholders and is negatively related to the difference between the desired level of adhocracy and the current level of adhocracy. Recovery orientation is positively related to the education level of staff/influential stakeholders, satisfying transformational leadership outcomes, and larger mental health budgets per capita. Policy implications are discussed.

  12. Identifying organizational cultures that promote patient safety.

    PubMed

    Singer, Sara J; Falwell, Alyson; Gaba, David M; Meterko, Mark; Rosen, Amy; Hartmann, Christine W; Baker, Laurence

    2009-01-01

    Safety climate refers to shared perceptions of what an organization is like with regard to safety, whereas safety culture refers to employees' fundamental ideology and orientation and explains why safety is pursued in the manner exhibited within a particular organization. Although research has sought to identify opportunities for improving safety outcomes by studying patterns of variation in safety climate, few empirical studies have examined the impact of organizational characteristics such as culture on hospital safety climate. This study explored how aspects of general organizational culture relate to hospital patient safety climate. In a stratified sample of 92 U.S. hospitals, we sampled 100% of senior managers and physicians and 10% of other hospital workers. The Patient Safety Climate in Healthcare Organizations and the Zammuto and Krakower organizational culture surveys measured safety climate and group, entrepreneurial, hierarchical, and production orientation of hospitals' culture, respectively. We administered safety climate surveys to 18,361 personnel and organizational culture surveys to a 5,894 random subsample between March 2004 and May 2005. Secondary data came from the 2004 American Hospital Association Annual Hospital Survey and Dun & Bradstreet. Hierarchical linear regressions assessed relationships between organizational culture and safety climate measures. Aspects of general organizational culture were strongly related to safety climate. A higher level of group culture correlated with a higher level of safety climate, but more hierarchical culture was associated with lower safety climate. Aspects of organizational culture accounted for more than threefold improvement in measures of model fit compared with models with controls alone. A mix of culture types, emphasizing group culture, seemed optimal for safety climate. Safety climate and organizational culture are positively related. Results support strategies that promote group orientation and reduced hierarchy, including use of multidisciplinary team training, continuous quality improvement tools, and human resource practices and policies.

  13. LIMO EEG: a toolbox for hierarchical LInear MOdeling of ElectroEncephaloGraphic data.

    PubMed

    Pernet, Cyril R; Chauveau, Nicolas; Gaspar, Carl; Rousselet, Guillaume A

    2011-01-01

    Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses.

  14. LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data

    PubMed Central

    Pernet, Cyril R.; Chauveau, Nicolas; Gaspar, Carl; Rousselet, Guillaume A.

    2011-01-01

    Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses. PMID:21403915

  15. Towards Stability Analysis of Jump Linear Systems with State-Dependent and Stochastic Switching

    NASA Technical Reports Server (NTRS)

    Tejada, Arturo; Gonzalez, Oscar R.; Gray, W. Steven

    2004-01-01

    This paper analyzes the stability of hierarchical jump linear systems where the supervisor is driven by a Markovian stochastic process and by the values of the supervised jump linear system s states. The stability framework for this class of systems is developed over infinite and finite time horizons. The framework is then used to derive sufficient stability conditions for a specific class of hybrid jump linear systems with performance supervision. New sufficient stochastic stability conditions for discrete-time jump linear systems are also presented.

  16. Technique for fast and efficient hierarchical clustering

    DOEpatents

    Stork, Christopher

    2013-10-08

    A fast and efficient technique for hierarchical clustering of samples in a dataset includes compressing the dataset to reduce a number of variables within each of the samples of the dataset. A nearest neighbor matrix is generated to identify nearest neighbor pairs between the samples based on differences between the variables of the samples. The samples are arranged into a hierarchy that groups the samples based on the nearest neighbor matrix. The hierarchy is rendered to a display to graphically illustrate similarities or differences between the samples.

  17. Simultaneous determination of 19 flavonoids in commercial trollflowers by using high-performance liquid chromatography and classification of samples by hierarchical clustering analysis.

    PubMed

    Song, Zhiling; Hashi, Yuki; Sun, Hongyang; Liang, Yi; Lan, Yuexiang; Wang, Hong; Chen, Shizhong

    2013-12-01

    The flowers of Trollius species, named Jin Lianhua in Chinese, are widely used traditional Chinese herbs with vital biological activity that has been used for several decades in China to treat upper respiratory infections, pharyngitis, tonsillitis, and bronchitis. We developed a rapid and reliable method for simultaneous quantitative analysis of 19 flavonoids in trollflowers by using high-performance liquid chromatography (HPLC). Chromatography was performed on Inertsil ODS-3 C18 column, with gradient elution methanol-acetonitrile-water with 0.02% (v/v) formic acid. Content determination was used to evaluate the quality of commercial trollflowers from different regions in China, while three Trollius species (Trollius chinensis Bunge, Trollius ledebouri Reichb, Trollius buddae Schipcz) were explicitly distinguished by using hierarchical clustering analysis. The linearity, precision, accuracy, limit of detection, and limit of quantification were validated for the quantification method, which proved sensitive, accurate and reproducible indicating that the proposed approach was applicable for the routine analysis and quality control of trollflowers. © 2013.

  18. Facile preparation of branched hierarchical ZnO nanowire arrays with enhanced photocatalytic activity: A photodegradation kinetic model

    NASA Astrophysics Data System (ADS)

    Ebrahimi, M.; Yousefzadeh, S.; Samadi, M.; Dong, Chunyang; Zhang, Jinlong; Moshfegh, A. Z.

    2018-03-01

    Branched hierarchical zinc oxide nanowires (BH-ZnO NWs) were fabricated successfully by a facile and rapid synthesis using two-step growth process. Initially, ZnO NWs have been prepared by anodizing zinc foil at room temperature and followed by annealing treatment. Then, the BH- ZnO NWs were grown on the ZnO NWs by a solution based method at very low temperature (31 oC). The BH- ZnO NWs with different aspect ratio were obtained by varying reaction time (0.5, 2, 5, 10 h). Photocatalytic activity of the samples was studied under both UV and visible light. The results indicated that the optimized BH-ZnO NWs (5 h) as a photocatalyst exhibited the highest photoactivity with about 3 times higher than the ZnO NWs under UV light. In addition, it was also determined that photodegradation rate constant (k) for the BH- ZnO NWs surface obeys a linear function with the branch length (l) and their correlation was described by using a proposed kinetic model.

  19. In Which Ways and to What Extent Do English and Shanghai Students Understand Linear Function?

    ERIC Educational Resources Information Center

    Wang, Yuqian; Barmby, Patrick; Bolden, David

    2017-01-01

    This study investigates how students in England and Shanghai understand linear function. Understanding is defined theoretically in terms of five hierarchical levels: Dependent Relationship; Connecting Representations; Property Noticing; Object Analysis; and Inventising. A pilot study instrument presented a set of problems to both cohorts, showing…

  20. Posterior propriety for hierarchical models with log-likelihoods that have norm bounds

    DOE PAGES

    Michalak, Sarah E.; Morris, Carl N.

    2015-07-17

    Statisticians often use improper priors to express ignorance or to provide good frequency properties, requiring that posterior propriety be verified. Our paper addresses generalized linear mixed models, GLMMs, when Level I parameters have Normal distributions, with many commonly-used hyperpriors. It provides easy-to-verify sufficient posterior propriety conditions based on dimensions, matrix ranks, and exponentiated norm bounds, ENBs, for the Level I likelihood. Since many familiar likelihoods have ENBs, which is often verifiable via log-concavity and MLE finiteness, our novel use of ENBs permits unification of posterior propriety results and posterior MGF/moment results for many useful Level I distributions, including those commonlymore » used with multilevel generalized linear models, e.g., GLMMs and hierarchical generalized linear models, HGLMs. Furthermore, those who need to verify existence of posterior distributions or of posterior MGFs/moments for a multilevel generalized linear model given a proper or improper multivariate F prior as in Section 1 should find the required results in Sections 1 and 2 and Theorem 3 (GLMMs), Theorem 4 (HGLMs), or Theorem 5 (posterior MGFs/moments).« less

  1. Leadership styles across hierarchical levels in nursing departments.

    PubMed

    Stordeur, S; Vandenberghe, C; D'hoore, W

    2000-01-01

    Some researchers have reported on the cascading effect of transformational leadership across hierarchical levels. One study examined this effect in nursing, but it was limited to a single hospital. To examine the cascading effect of leadership styles across hierarchical levels in a sample of nursing departments and to investigate the effect of hierarchical level on the relationships between leadership styles and various work outcomes. Based on a sample of eight hospitals, the cascading effect was tested using correlation analysis. The main sources of variation among leadership scores were determined with analyses of variance (ANOVA), and the interaction effect of hierarchical level and leadership styles on criterion variables was tested with moderated regression analysis. No support was found for a cascading effect of leadership across hierarchical levels. Rather, the variation of leadership scores was explained primarily by the organizational context. Transformational leadership had a stronger impact on criterion variables than transactional leadership. Interaction effects between leadership styles and hierarchical level were observed only for perceived unit effectiveness. The hospital's structure and culture are major determinants of leadership styles.

  2. Asymptotic analysis of hierarchical martensitic microstructure

    NASA Astrophysics Data System (ADS)

    Cesana, Pierluigi; Porta, Marcel; Lookman, Turab

    2014-12-01

    We consider a hierarchical nested microstructure, which also contains a point of singularity (disclination) at the origin, observed in lead orthovanadate. We show how to exactly compute the energy cost and associated displacement field within linearized elasticity by enforcing geometric compatibility of strains across interfaces of the three-phase mixture of distortions (variants) in the microstructure. We prove that the mechanical deformation is purely elastic and discuss the behavior of the system close to the origin.

  3. Mental and physical health correlates among family caregivers of patients with newly-diagnosed incurable cancer: a hierarchical linear regression analysis.

    PubMed

    Shaffer, Kelly M; Jacobs, Jamie M; Nipp, Ryan D; Carr, Alaina; Jackson, Vicki A; Park, Elyse R; Pirl, William F; El-Jawahri, Areej; Gallagher, Emily R; Greer, Joseph A; Temel, Jennifer S

    2017-03-01

    Caregiver, relational, and patient factors have been associated with the health of family members and friends providing care to patients with early-stage cancer. Little research has examined whether findings extend to family caregivers of patients with incurable cancer, who experience unique and substantial caregiving burdens. We examined correlates of mental and physical health among caregivers of patients with newly-diagnosed incurable lung or non-colorectal gastrointestinal cancer. At baseline for a trial of early palliative care, caregivers of participating patients (N = 275) reported their mental and physical health (Medical Outcome Survey-Short Form-36); patients reported their quality of life (Functional Assessment of Cancer Therapy-General). Analyses used hierarchical linear regression with two-tailed significance tests. Caregivers' mental health was worse than the U.S. national population (M = 44.31, p < .001), yet their physical health was better (M = 56.20, p < .001). Hierarchical regression analyses testing caregiver, relational, and patient factors simultaneously revealed that younger (B = 0.31, p = .001), spousal caregivers (B = -8.70, p = .003), who cared for patients reporting low emotional well-being (B = 0.51, p = .01) reported worse mental health; older (B = -0.17, p = .01) caregivers with low educational attainment (B = 4.36, p < .001) who cared for patients reporting low social well-being (B = 0.35, p = .05) reported worse physical health. In this large sample of family caregivers of patients with incurable cancer, caregiver demographics, relational factors, and patient-specific factors were all related to caregiver mental health, while caregiver demographics were primarily associated with caregiver physical health. These findings help identify characteristics of family caregivers at highest risk of poor mental and physical health who may benefit from greater supportive care.

  4. Estimation of river and stream temperature trends under haphazard sampling

    USGS Publications Warehouse

    Gray, Brian R.; Lyubchich, Vyacheslav; Gel, Yulia R.; Rogala, James T.; Robertson, Dale M.; Wei, Xiaoqiao

    2015-01-01

    Long-term temporal trends in water temperature in rivers and streams are typically estimated under the assumption of evenly-spaced space-time measurements. However, sampling times and dates associated with historical water temperature datasets and some sampling designs may be haphazard. As a result, trends in temperature may be confounded with trends in time or space of sampling which, in turn, may yield biased trend estimators and thus unreliable conclusions. We address this concern using multilevel (hierarchical) linear models, where time effects are allowed to vary randomly by day and date effects by year. We evaluate the proposed approach by Monte Carlo simulations with imbalance, sparse data and confounding by trend in time and date of sampling. Simulation results indicate unbiased trend estimators while results from a case study of temperature data from the Illinois River, USA conform to river thermal assumptions. We also propose a new nonparametric bootstrap inference on multilevel models that allows for a relatively flexible and distribution-free quantification of uncertainties. The proposed multilevel modeling approach may be elaborated to accommodate nonlinearities within days and years when sampling times or dates typically span temperature extremes.

  5. Hierarchical flexural strength of enamel: transition from brittle to damage-tolerant behaviour

    PubMed Central

    Bechtle, Sabine; Özcoban, Hüseyin; Lilleodden, Erica T.; Huber, Norbert; Schreyer, Andreas; Swain, Michael V.; Schneider, Gerold A.

    2012-01-01

    Hard, biological materials are generally hierarchically structured from the nano- to the macro-scale in a somewhat self-similar manner consisting of mineral units surrounded by a soft protein shell. Considerable efforts are underway to mimic such materials because of their structurally optimized mechanical functionality of being hard and stiff as well as damage-tolerant. However, it is unclear how different hierarchical levels interact to achieve this performance. In this study, we consider dental enamel as a representative, biological hierarchical structure and determine its flexural strength and elastic modulus at three levels of hierarchy using focused ion beam (FIB) prepared cantilevers of micrometre size. The results are compared and analysed using a theoretical model proposed by Jäger and Fratzl and developed by Gao and co-workers. Both properties decrease with increasing hierarchical dimension along with a switch in mechanical behaviour from linear-elastic to elastic-inelastic. We found Gao's model matched the results very well. PMID:22031729

  6. Bayesian hierarchical piecewise regression models: a tool to detect trajectory divergence between groups in long-term observational studies.

    PubMed

    Buscot, Marie-Jeanne; Wotherspoon, Simon S; Magnussen, Costan G; Juonala, Markus; Sabin, Matthew A; Burgner, David P; Lehtimäki, Terho; Viikari, Jorma S A; Hutri-Kähönen, Nina; Raitakari, Olli T; Thomson, Russell J

    2017-06-06

    Bayesian hierarchical piecewise regression (BHPR) modeling has not been previously formulated to detect and characterise the mechanism of trajectory divergence between groups of participants that have longitudinal responses with distinct developmental phases. These models are useful when participants in a prospective cohort study are grouped according to a distal dichotomous health outcome. Indeed, a refined understanding of how deleterious risk factor profiles develop across the life-course may help inform early-life interventions. Previous techniques to determine between-group differences in risk factors at each age may result in biased estimate of the age at divergence. We demonstrate the use of Bayesian hierarchical piecewise regression (BHPR) to generate a point estimate and credible interval for the age at which trajectories diverge between groups for continuous outcome measures that exhibit non-linear within-person response profiles over time. We illustrate our approach by modeling the divergence in childhood-to-adulthood body mass index (BMI) trajectories between two groups of adults with/without type 2 diabetes mellitus (T2DM) in the Cardiovascular Risk in Young Finns Study (YFS). Using the proposed BHPR approach, we estimated the BMI profiles of participants with T2DM diverged from healthy participants at age 16 years for males (95% credible interval (CI):13.5-18 years) and 21 years for females (95% CI: 19.5-23 years). These data suggest that a critical window for weight management intervention in preventing T2DM might exist before the age when BMI growth rate is naturally expected to decrease. Simulation showed that when using pairwise comparison of least-square means from categorical mixed models, smaller sample sizes tended to conclude a later age of divergence. In contrast, the point estimate of the divergence time is not biased by sample size when using the proposed BHPR method. BHPR is a powerful analytic tool to model long-term non-linear longitudinal outcomes, enabling the identification of the age at which risk factor trajectories diverge between groups of participants. The method is suitable for the analysis of unbalanced longitudinal data, with only a limited number of repeated measures per participants and where the time-related outcome is typically marked by transitional changes or by distinct phases of change over time.

  7. Control Strategies for Guided Collective Motion

    DTIC Science & Technology

    2015-02-27

    Rorres and H. Anton , “ Elementary linear algebra applications version,” 9th Edition, Wiley India Pvt. Ltd., 2011. [20] S.H. Strogatz, “From Kuramoto to... linear cyclic pursuit in which an agent pursues its leader with an angle of deviation. The sufficient conditions for the stability of such systems are...Generalized Hierarchical Cyclic Pursuit 6. D. Mukherjee and D. Ghose: Deviated Linear Cyclic Pursuit 7. D. Mukherjee and D. Ghose; On Synchronous and

  8. Multiscale Hierarchical Design of a Flexible Piezoresistive Pressure Sensor with High Sensitivity and Wide Linearity Range.

    PubMed

    Shi, Jidong; Wang, Liu; Dai, Zhaohe; Zhao, Lingyu; Du, Mingde; Li, Hongbian; Fang, Ying

    2018-05-30

    Flexible piezoresistive pressure sensors have been attracting wide attention for applications in health monitoring and human-machine interfaces because of their simple device structure and easy-readout signals. For practical applications, flexible pressure sensors with both high sensitivity and wide linearity range are highly desirable. Herein, a simple and low-cost method for the fabrication of a flexible piezoresistive pressure sensor with a hierarchical structure over large areas is presented. The piezoresistive pressure sensor consists of arrays of microscale papillae with nanoscale roughness produced by replicating the lotus leaf's surface and spray-coating of graphene ink. Finite element analysis (FEA) shows that the hierarchical structure governs the deformation behavior and pressure distribution at the contact interface, leading to a quick and steady increase in contact area with loads. As a result, the piezoresistive pressure sensor demonstrates a high sensitivity of 1.2 kPa -1 and a wide linearity range from 0 to 25 kPa. The flexible pressure sensor is applied for sensitive monitoring of small vibrations, including wrist pulse and acoustic waves. Moreover, a piezoresistive pressure sensor array is fabricated for mapping the spatial distribution of pressure. These results highlight the potential applications of the flexible piezoresistive pressure sensor for health monitoring and electronic skin. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. A Spreadsheet for a 2 x 3 x 2 Log-Linear Analysis. AIR 1991 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Saupe, Joe L.

    This paper describes a personal computer spreadsheet set up to carry out hierarchical log-linear analyses, a type of analysis useful for institutional research into multidimensional frequency tables formed from categorical variables such as faculty rank, student class level, gender, or retention status. The spreadsheet provides a concrete vehicle…

  10. The Impact of Historically Black Colleges and Universities on the Academic Success of African-American Students

    ERIC Educational Resources Information Center

    Kim, Mikyong Minsun; Conrad, Clifton F.

    2006-01-01

    Anchored in national longitudinal data analyzed through hierarchical linear and non-linear modeling, this study found that African-American students have a similar probability of obtaining a BA degree whether they attended a historically Black college or university (HBCU) or a historically White college or university (HWCU). Among…

  11. Correlates of Persistent Smoking in Bars Subject to Smokefree Workplace Policy

    PubMed Central

    Moore, Roland S.; Lee, Juliet P.; Martin, Scott E.; Todd, Michael; Chu, Bong Chul

    2009-01-01

    This study’s goal was to characterize physical and social environments of stand-alone bars associated with indoor smoking despite California’s smokefree workplace law. In a random sample of 121 stand-alone bars in San Francisco, trained observers collected data on patrons, staff, neighborhood, indoor settings and smoking behaviors. Using bivariate (chi-square) and hierarchical linear modeling analyses, we identified four correlates of patrons’ indoor smoking: 1) bars serving predominantly Asian or Irish patrons, 2) ashtrays, 3) bartender smoking, and 4) female bartenders. Public health officials charged with enforcement of smokefree bar policies may need to attend to social practices within bars, and heighten perceptions of consistent enforcement of smokefree workplace laws. PMID:19440522

  12. The relationship between victimization and mental health functioning in homeless youth and adults.

    PubMed

    Rattelade, Stephanie; Farrell, Susan; Aubry, Tim; Klodawsky, Fran

    2014-06-01

    This study examined the relationship between victimization and mental health functioning in homeless individuals. Homeless populations experience higher levels of victimization than the general population, which in turn have a detrimental effect on their mental health. A sample of 304 homeless adults and youth completed one-on-one interviews, answering questions on mental health, past victimization, and recent victimization experiences. A hierarchical linear regression showed that experiences of childhood sexual abuse predicted lower mental health functioning after controlling for the sex and age of individuals. The study findings are applicable to current support programs for victims in the homeless population and are relevant to future research on homelessness and victimization.

  13. Depression, Control, and Climate: An Examination of Factors Impacting Teaching Quality in Preschool Classrooms.

    PubMed

    Sandilos, Lia E; Cycyk, Lauren M; Hammer, Carol Scheffner; Sawyer, Brook E; López, Lisa; Blair, Clancy

    This study investigated the relationship of preschool teachers' self-reported depressive symptomatology, perception of classroom control, and perception of school climate to classroom quality as measured by the Classroom Assessment Scoring System Pre-K. The sample consisted of 59 urban preschool classrooms serving low-income and linguistically diverse students in the northeastern and southeastern United States. Results of hierarchical linear modeling revealed that teachers' individual reports of depressive symptomatology were significantly and negatively predictive of the observed quality of their instructional support and classroom organization. The findings of this study have implications for increasing access to mental health supports for teachers in an effort to minimize depressive symptoms and potentially improve classroom quality.

  14. Social Influences on Abstinence Self-Efficacy among Justice-Involved Persons

    PubMed Central

    Majer, John M.; Callahan, Sarah; Stevick, Kate; Jason, Leonard A.

    2016-01-01

    Social influences (social support for alcohol/drug use and social support for abstinence) were examined in relation to abstinence self-efficacy among a sample of 250 justice involved persons exiting inpatient treatment for substance use disorders. Hierarchical linear regression was used to examine social influences in relation to abstinence self-efficacy. Social influences were significantly related to abstinence self-efficacy when examined independently. However, only social support for alcohol/drug use was significant when both social influences were entered into the model. Findings suggest social support for alcohol/drug use compromises abstinence social support, particularly among justice involved persons who are early in their recovery from substance use disorders. PMID:27594810

  15. Multilevel Higher-Order Item Response Theory Models

    ERIC Educational Resources Information Center

    Huang, Hung-Yu; Wang, Wen-Chung

    2014-01-01

    In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

  16. Testing higher-order Lagrangian perturbation theory against numerical simulation. 1: Pancake models

    NASA Technical Reports Server (NTRS)

    Buchert, T.; Melott, A. L.; Weiss, A. G.

    1993-01-01

    We present results showing an improvement of the accuracy of perturbation theory as applied to cosmological structure formation for a useful range of quasi-linear scales. The Lagrangian theory of gravitational instability of an Einstein-de Sitter dust cosmogony investigated and solved up to the third order is compared with numerical simulations. In this paper we study the dynamics of pancake models as a first step. In previous work the accuracy of several analytical approximations for the modeling of large-scale structure in the mildly non-linear regime was analyzed in the same way, allowing for direct comparison of the accuracy of various approximations. In particular, the Zel'dovich approximation (hereafter ZA) as a subclass of the first-order Lagrangian perturbation solutions was found to provide an excellent approximation to the density field in the mildly non-linear regime (i.e. up to a linear r.m.s. density contrast of sigma is approximately 2). The performance of ZA in hierarchical clustering models can be greatly improved by truncating the initial power spectrum (smoothing the initial data). We here explore whether this approximation can be further improved with higher-order corrections in the displacement mapping from homogeneity. We study a single pancake model (truncated power-spectrum with power-spectrum with power-index n = -1) using cross-correlation statistics employed in previous work. We found that for all statistical methods used the higher-order corrections improve the results obtained for the first-order solution up to the stage when sigma (linear theory) is approximately 1. While this improvement can be seen for all spatial scales, later stages retain this feature only above a certain scale which is increasing with time. However, third-order is not much improvement over second-order at any stage. The total breakdown of the perturbation approach is observed at the stage, where sigma (linear theory) is approximately 2, which corresponds to the onset of hierarchical clustering. This success is found at a considerable higher non-linearity than is usual for perturbation theory. Whether a truncation of the initial power-spectrum in hierarchical models retains this improvement will be analyzed in a forthcoming work.

  17. Microfluidic Droplet-Facilitated Hierarchical Assembly for Dual Cargo Loading and Synergistic Delivery.

    PubMed

    Yu, Ziyi; Zheng, Yu; Parker, Richard M; Lan, Yang; Wu, Yuchao; Coulston, Roger J; Zhang, Jing; Scherman, Oren A; Abell, Chris

    2016-04-06

    Bottom-up hierarchical assembly has emerged as an elaborate and energy-efficient strategy for the fabrication of smart materials. Herein, we present a hierarchical assembly process, whereby linear amphiphilic block copolymers are self-assembled into micelles, which in turn are accommodated at the interface of microfluidic droplets via cucurbit[8]uril-mediated host-guest chemistry to form supramolecular microcapsules. The monodisperse microcapsules can be used for simultaneous carriage of both organic (Nile Red) and aqueous-soluble (fluorescein isothiocyanate-dextran) cargo. Furthermore, the well-defined compartmentalized structure benefits from the dynamic nature of the supramolecular interaction and offers synergistic delivery of cargos with triggered release or through photocontrolled porosity. This demonstration of premeditated hierarchical assembly, where interactions from the molecular to microscale are designed, illustrates the power of this route toward accessing the next generation of functional materials and encapsulation strategies.

  18. Global/local processing of hierarchical visual stimuli in a conflict-choice task by capuchin monkeys (Sapajus spp.).

    PubMed

    Truppa, Valentina; Carducci, Paola; De Simone, Diego Antonio; Bisazza, Angelo; De Lillo, Carlo

    2017-03-01

    In the last two decades, comparative research has addressed the issue of how the global and local levels of structure of visual stimuli are processed by different species, using Navon-type hierarchical figures, i.e. smaller local elements that form larger global configurations. Determining whether or not the variety of procedures adopted to test different species with hierarchical figures are equivalent is of crucial importance to ensure comparability of results. Among non-human species, global/local processing has been extensively studied in tufted capuchin monkeys using matching-to-sample tasks with hierarchical patterns. Local dominance has emerged consistently in these New World primates. In the present study, we assessed capuchins' processing of hierarchical stimuli with a method frequently adopted in studies of global/local processing in non-primate species: the conflict-choice task. Different from the matching-to-sample procedure, this task involved processing local and global information retained in long-term memory. Capuchins were trained to discriminate between consistent hierarchical stimuli (similar global and local shape) and then tested with inconsistent hierarchical stimuli (different global and local shapes). We found that capuchins preferred the hierarchical stimuli featuring the correct local elements rather than those with the correct global configuration. This finding confirms that capuchins' local dominance, typically observed using matching-to-sample procedures, is also expressed as a local preference in the conflict-choice task. Our study adds to the growing body of comparative studies on visual grouping functions by demonstrating that the methods most frequently used in the literature on global/local processing produce analogous results irrespective of extent of the involvement of memory processes.

  19. Kinetic Rate Kernels via Hierarchical Liouville-Space Projection Operator Approach.

    PubMed

    Zhang, Hou-Dao; Yan, YiJing

    2016-05-19

    Kinetic rate kernels in general multisite systems are formulated on the basis of a nonperturbative quantum dissipation theory, the hierarchical equations of motion (HEOM) formalism, together with the Nakajima-Zwanzig projection operator technique. The present approach exploits the HEOM-space linear algebra. The quantum non-Markovian site-to-site transfer rate can be faithfully evaluated via projected HEOM dynamics. The developed method is exact, as evident by the comparison to the direct HEOM evaluation results on the population evolution.

  20. Patterning of ultrathin polymethylmethacrylate films by in-situ photodirecting of the Marangoni flow

    NASA Astrophysics Data System (ADS)

    Elashnikov, Roman; Fitl, Premysl; Svorcik, Vaclav; Lyutakov, Oleksiy

    2017-02-01

    Laser heating and Marangoni flow result in the formation of surface structures with different geometries and shape on thin polymer films. By laser beam irradiation combined with a sample movement the solid polymethylmethacrylate (PMMA) films are heated and undergo phase transition which leads to a material flow. Since the laser beam has a non-linear distribution of energy, the PMMA film is heated inhomogeneously and a surface tension gradient in a lateral direction is introduced. During this procedure additional phenomena such as "reversible" or cyclic polymer flow also take place. The careful choice of experimental conditions enables the preparation of patterns with sophisticated geometries and with hierarchical pattern organization. Depending on initial PMMA film thickness and speed of the sample movement line arrays are created, which can subsequently be transformed into the crimped lines or system of circular holes. In addition, the introduction of a constant acceleration in the sample movement or a laser beam distortion enables the preparation of regularly crimped lines, ordered hexagonal holes or overlapped plates.

  1. Template-free fabrication of hierarchically flower-like tungsten trioxide assemblies with enhanced visible-light-driven photocatalytic activity.

    PubMed

    Yu, Jiaguo; Qi, Lifang

    2009-09-30

    Hierarchically flower-like tungsten trioxide assemblies were fabricated on a large scale by a simple hydrothermal treatment of sodium tungstate in aqueous solution of nitric acid. The as-prepared samples were characterized by X-ray diffraction, scanning electron microscopy and N(2) adsorption-desorption measurements. The photocatalytic activity was evaluated by photocatalytic decolorization of rhodamine B aqueous solution under visible-light irradiation. It was found that the three-dimensional tungsten trioxide assemblies were constructed from two-dimensional layers, which were further composed of a large number of interconnected lathy nanoplates with different sizes. Such flower-like assemblies exhibited hierarchically porous structure and higher visible-light photocatalytic activity than the samples without such hierarchical structures due to their specific hierarchical pores that served as the transport paths for light and reactants. After five recycles for the photodegradation of RhB, the catalyst did not exhibit any great loss in activity, confirming hierarchically flower-like tungsten trioxide was stability and not photocorroded. This study may provide new insight into environmentally benign preparation and design of novel photocatalytic materials and enhancement of photocatalytic activity.

  2. Social structure in a family group of Guanaco (Lama guanicoe, Ungulate): is female hierarchy based on 'prior attributes' or 'social dynamics'?

    PubMed

    Correa, Loreto A; Zapata, Beatriz; Samaniego, Horacio; Soto-Gamboa, Mauricio

    2013-09-01

    Social life involves costs and benefits mostly associated with how individuals interact with each other. The formation of hierarchies inside social groups has evolved as a common strategy to avoid high costs stemming from social interactions. Hierarchical relationships seem to be associated with different features such as body size, body condition and/or age, which determine dominance ability ('prior attributes' hypothesis). In contrast, the 'social dynamic' hypothesis suggests that an initial social context is a determinant in the formation of the hierarchy, more so than specific individual attributes. Hierarchical rank places individuals in higher positions, which presumably increases resource accessibility to their benefit, including opportunities for reproduction. We evaluate the maintenance of hierarchy in a family group of guanacos (Lama guanicoe) and evaluate the possible mechanisms involved in the stability of these interactions and their consequences. We estimate the linearity of social hierarchy and their dynamics. We find evidence of the formation of a highly linear hierarchy among females with males positioned at the bottom of the hierarchy. This hierarchy is not affected by physical characteristics or age, suggesting that it is established only through intra-group interactions. Rank is not related with calves' weight gain either; however, subordinated females, with lower rank, exhibit higher rates of allosuckling. We found no evidence of hierarchical structure in calves suggesting that hierarchical relationship in guanacos could be established during the formation of the family group. Hence, our results suggest that hierarchical dynamics could be related more to social dynamics than to prior attributes. We finally discuss the importance of hierarchies established by dominance and their role in minimizing social costs of interactions. Copyright © 2013 Elsevier B.V. All rights reserved.

  3. Ultrasensitive non-enzymatic glucose sensor based on three-dimensional network of ZnO-CuO hierarchical nanocomposites by electrospinning

    PubMed Central

    Zhou, Chunyang; Xu, Lin; Song, Jian; Xing, Ruiqing; Xu, Sai; Liu, Dali; Song, Hongwei

    2014-01-01

    Three-dimensional (3D) porous ZnO–CuO hierarchical nanocomposites (HNCs) nonenzymatic glucose electrodes with different thicknesses were fabricated by coelectrospinning and compared with 3D mixed ZnO/CuO nanowires (NWs) and pure CuO NWs electrodes. The structural characterization revealed that the ZnO–CuO HNCs were composed of the ZnO and CuO mixed NWs trunk (~200 nm), whose outer surface was attached with small CuO nanoparticles (NPs). Moreover, a good synergetic effect between CuO and ZnO was confirmed. The nonenzymatic biosensing properties of as prepared 3D porous electrodes based on fluorine doped tin oxide (FTO) were studied and the results indicated that the sensing properties of 3D porous ZnO–CuO HNCs electrodes were significantly improved and depended strongly on the thickness of the HNCs. At an applied potential of + 0.7 V, the optimum ZnO–CuO HNCs electrode presented a high sensitivity of 3066.4 μAmM−1cm−2, the linear range up to 1.6 mM, and low practical detection limit of 0.21 μM. It also showed outstanding long term stability, good reproducibility, excellent selectivity and accurate measurement in real serum sample. The formation of special hierarchical heterojunction and the well-constructed 3D structure were the main reasons for the enhanced nonenzymatic biosensing behavior. PMID:25488502

  4. Differentiation of Students' Reasoning on Linear and Quadratic Geometric Number Patterns

    ERIC Educational Resources Information Center

    Lin, Fou-Lai; Yang, Kai-Lin

    2004-01-01

    There are two purposes in this study. One is to compare how 7th and 8th graders reason on linear and quadratic geometric number patterns when they have not learned this kind of tasks in school. The other is to explore the hierarchical relations among the four components of reasoning on geometric number patterns: understanding, generalizing,…

  5. Adulteration and cultivation region identification of American ginseng using HPLC coupled with multivariate analysis

    PubMed Central

    Yu, Chunhao; Wang, Chong-Zhi; Zhou, Chun-Jie; Wang, Bin; Han, Lide; Zhang, Chun-Feng; Wu, Xiao-Hui; Yuan, Chun-Su

    2014-01-01

    American ginseng (Panax quinquefolius) is originally grown in North America. Due to price difference and supply shortage, American ginseng recently has been cultivated in northern China. Further, in the market, some Asian ginsengs are labeled as American ginseng. In this study, forty-three American ginseng samples cultivated in the USA, Canada or China were collected and 14 ginseng saponins were determined using HPLC. HPLC coupled with hierarchical cluster analysis and principal component analysis was developed to identify the species. Subsequently, an HPLC-linear discriminant analysis was established to discriminate cultivation regions of American ginseng. This method was successfully applied to identify the sources of 6 commercial American ginseng samples. Two of them were identified as Asian ginseng, while 4 others were identified as American ginseng, which were cultivated in the USA (3) and China (1). Our newly developed method can be used to identify American ginseng with different cultivation regions. PMID:25044150

  6. A genetically informed study of the association between harsh punishment and offspring behavioral problems.

    PubMed

    Lynch, Stacy K; Turkheimer, Eric; D'Onofrio, Brian M; Mendle, Jane; Emery, Robert E; Slutske, Wendy S; Martin, Nicholas G

    2006-06-01

    Conclusions about the effects of harsh parenting on children have been limited by research designs that cannot control for genetic or shared environmental confounds. The present study used a sample of children of twins and a hierarchical linear modeling statistical approach to analyze the consequences of varying levels of punishment while controlling for many confounding influences. The sample of 887 twin pairs and 2,554 children came from the Australian Twin Registry. Although corporal punishment per se did not have significant associations with negative childhood outcomes, harsher forms of physical punishment did appear to have specific and significant effects. The observed association between harsh physical punishment and negative outcomes in children survived a relatively rigorous test of its causal status, thereby increasing the authors' conviction that harsh physical punishment is a serious risk factor for children. ((c) 2006 APA, all rights reserved).

  7. The Role of Structural Barriers in Risky Sexual Behavior, Victimization and Readiness to Change HIV/STI-Related Risk Behavior Among Transgender Women.

    PubMed

    Raiford, Jerris L; Hall, Grace J; Taylor, Raekiela D; Bimbi, David S; Parsons, Jeffrey T

    2016-10-01

    This study examines the role of structural barriers experienced by a community-based sample of 63 HIV-positive and negative transgender women that may elevate HIV infection and transmission risks. Separate hierarchical linear multiple regression analyses tested the association between structural barriers (e.g., unemployment, lack of food, shelter) and condomless anal sex acts, abuse, and readiness to change risk behavior, while controlling for other related factors. Among this primarily Hispanic and African-American sample, HIV-positive and negative transgender women experienced a similar number of structural barriers and experiencing structural barriers was significantly associated with an increased number of condomless anal sex acts (p = .002), victimization (p = .000) and a decreased readiness to change HIV-related risk behavior (p = .014). Structural-level interventions are needed to address this elevated risk among this underserved and hard-to-reach population.

  8. Subjective effect of September 11, 2001 among pregnant women: is cumulative history of interpersonal violence important?

    PubMed

    Lewis, Marilyn W; Cavanagh, Paul K; Ahn, Grace; Yoshioka, Marianne R

    2008-06-01

    Prior history of trauma may sensitize individuals to subsequent trauma, including terrorist attacks. Using a convenience sample of secondary, cross-sectional data, pregnant women were grouped based on lifetime interpersonal violence history. Cumulative risk theory was used to evaluate the association of lifetime interpersonal violence history and subjective impact of the September 11, 2001 (9/11) terrorists attacks. Using hierarchical linear regression, cumulative risk theory was partially supported. Women with a history of only one type of interpfersonal violence reported greater effect of 9/11 than did women without a history, but women with both types of violence did not report a greater effect of 9/11 compared to women endorsing history of one type. These data corroborate the literature in that level of exposure to terrorist-related trauma predicts subjective reaction to the attacks. Future research with a larger sample and standardized instruments is warranted.

  9. Organizational justice and mental health: a multi-level test of justice interactions.

    PubMed

    Fischer, Ronald; Abubakar, Amina; Arasa, Josephine Nyaboke

    2014-04-01

    We examine main and interaction effects of organizational justice at the individual and the organizational levels on general health in a Kenyan sample. We theoretically differentiate between two different interaction patterns of justice effects: buffering mechanisms based on trust versus intensifying explanations of justice interactions that involve psychological contract violations. Using a two-level hierarchical linear model with responses from 427 employees in 29 organizations, only interpersonal justice at level 1 demonstrated a significant main effect. Interactions between distributive and interpersonal justice at both the individual and the collective levels were found. The intensifying hypothesis was supported: the relationship between distributive justice and mental health problems was strongest when interpersonal justice was high. This contrasts with buffering patterns described in Western samples. We argue that justice interaction patterns shift depending on the economic conditions and sociocultural characteristics of employees studied. © 2013 International Union of Psychological Science.

  10. A Genetically Informed Study of the Association Between Harsh Punishment and Offspring Behavioral Problems

    PubMed Central

    Lynch, Stacy K.; Turkheimer, Eric; D’Onofrio, Brian M.; Mendle, Jane; Emery, Robert E.; Slutske, Wendy S.; Martin, Nicholas G.

    2010-01-01

    Conclusions about the effects of harsh parenting on children have been limited by research designs that cannot control for genetic or shared environmental confounds. The present study used a sample of children of twins and a hierarchical linear modeling statistical approach to analyze the consequences of varying levels of punishment while controlling for many confounding influences. The sample of 887 twin pairs and 2,554 children came from the Australian Twin Registry. Although corporal punishment per se did not have significant associations with negative childhood outcomes, harsher forms of physical punishment did appear to have specific and significant effects. The observed association between harsh physical punishment and negative outcomes in children survived a relatively rigorous test of its causal status, thereby increasing the authors’ conviction that harsh physical punishment is a serious risk factor for children. PMID:16756394

  11. Loneliness mediates the relationship between emotion dysregulation and bulimia nervosa/binge eating disorder psychopathology in a clinical sample

    PubMed Central

    Christensen, Kara A.; Fettich, Karla C.; Weissman, Jessica; Berona, Johnny; Chen, Eunice Y.

    2017-01-01

    Emotion dysregulation has been linked to binge eating disorder (BED) and bulimia nervosa (BN) although the mechanisms by which it affects BN/BED psychopathology are unclear. This study tested loneliness as a mediator between emotion dysregulation and BN/BED psychopathology. A treatment-seeking sample of 107 women with BN or BED was assessed for loneliness (UCLA Loneliness Scale), emotion dysregulation (Difficulties in Emotion Regulation Scale), and BN/BED psychopathology (Eating Disorder Examination) before treatment. Hierarchical linear regressions and bootstrapping mediation models were run. Greater overall emotion dysregulation was associated with greater BN/BED psychopathology, mediated by loneliness (95 % CI 0.03, 0.09). Emotion dysregulation, however, did not mediate between loneliness and BN/BED psychopathology (95 % CI −0.01, 0.01). Targeting loneliness may effectively treat emotional aspects of BN/BED in women. PMID:24235091

  12. Cosmological parameters, shear maps and power spectra from CFHTLenS using Bayesian hierarchical inference

    NASA Astrophysics Data System (ADS)

    Alsing, Justin; Heavens, Alan; Jaffe, Andrew H.

    2017-04-01

    We apply two Bayesian hierarchical inference schemes to infer shear power spectra, shear maps and cosmological parameters from the Canada-France-Hawaii Telescope (CFHTLenS) weak lensing survey - the first application of this method to data. In the first approach, we sample the joint posterior distribution of the shear maps and power spectra by Gibbs sampling, with minimal model assumptions. In the second approach, we sample the joint posterior of the shear maps and cosmological parameters, providing a new, accurate and principled approach to cosmological parameter inference from cosmic shear data. As a first demonstration on data, we perform a two-bin tomographic analysis to constrain cosmological parameters and investigate the possibility of photometric redshift bias in the CFHTLenS data. Under the baseline ΛCDM (Λ cold dark matter) model, we constrain S_8 = σ _8(Ω _m/0.3)^{0.5} = 0.67+0.03-0.03 (68 per cent), consistent with previous CFHTLenS analyses but in tension with Planck. Adding neutrino mass as a free parameter, we are able to constrain ∑mν < 4.6 eV (95 per cent) using CFHTLenS data alone. Including a linear redshift-dependent photo-z bias Δz = p2(z - p1), we find p_1=-0.25+0.53-0.60 and p_2 = -0.15+0.17-0.15, and tension with Planck is only alleviated under very conservative prior assumptions. Neither the non-minimal neutrino mass nor photo-z bias models are significantly preferred by the CFHTLenS (two-bin tomography) data.

  13. Testing higher-order Lagrangian perturbation theory against numerical simulations. 2: Hierarchical models

    NASA Technical Reports Server (NTRS)

    Melott, A. L.; Buchert, T.; Weib, A. G.

    1995-01-01

    We present results showing an improvement of the accuracy of perturbation theory as applied to cosmological structure formation for a useful range of scales. The Lagrangian theory of gravitational instability of Friedmann-Lemaitre cosmogonies is compared with numerical simulations. We study the dynamics of hierarchical models as a second step. In the first step we analyzed the performance of the Lagrangian schemes for pancake models, the difference being that in the latter models the initial power spectrum is truncated. This work probed the quasi-linear and weakly non-linear regimes. We here explore whether the results found for pancake models carry over to hierarchical models which are evolved deeply into the non-linear regime. We smooth the initial data by using a variety of filter types and filter scales in order to determine the optimal performance of the analytical models, as has been done for the 'Zel'dovich-approximation' - hereafter TZA - in previous work. We find that for spectra with negative power-index the second-order scheme performs considerably better than TZA in terms of statistics which probe the dynamics, and slightly better in terms of low-order statistics like the power-spectrum. However, in contrast to the results found for pancake models, where the higher-order schemes get worse than TZA at late non-linear stages and on small scales, we here find that the second-order model is as robust as TZA, retaining the improvement at later stages and on smaller scales. In view of these results we expect that the second-order truncated Lagrangian model is especially useful for the modelling of standard dark matter models such as Hot-, Cold-, and Mixed-Dark-Matter.

  14. In silico screening of drug-membrane thermodynamics reveals linear relations between bulk partitioning and the potential of mean force

    NASA Astrophysics Data System (ADS)

    Menichetti, Roberto; Kanekal, Kiran H.; Kremer, Kurt; Bereau, Tristan

    2017-09-01

    The partitioning of small molecules in cell membranes—a key parameter for pharmaceutical applications—typically relies on experimentally available bulk partitioning coefficients. Computer simulations provide a structural resolution of the insertion thermodynamics via the potential of mean force but require significant sampling at the atomistic level. Here, we introduce high-throughput coarse-grained molecular dynamics simulations to screen thermodynamic properties. This application of physics-based models in a large-scale study of small molecules establishes linear relationships between partitioning coefficients and key features of the potential of mean force. This allows us to predict the structure of the insertion from bulk experimental measurements for more than 400 000 compounds. The potential of mean force hereby becomes an easily accessible quantity—already recognized for its high predictability of certain properties, e.g., passive permeation. Further, we demonstrate how coarse graining helps reduce the size of chemical space, enabling a hierarchical approach to screening small molecules.

  15. The impact of different DNA extraction kits and laboratories upon the assessment of human gut microbiota composition by 16S rRNA gene sequencing.

    PubMed

    Kennedy, Nicholas A; Walker, Alan W; Berry, Susan H; Duncan, Sylvia H; Farquarson, Freda M; Louis, Petra; Thomson, John M; Satsangi, Jack; Flint, Harry J; Parkhill, Julian; Lees, Charlie W; Hold, Georgina L

    2014-01-01

    Determining bacterial community structure in fecal samples through DNA sequencing is an important facet of intestinal health research. The impact of different commercially available DNA extraction kits upon bacterial community structures has received relatively little attention. The aim of this study was to analyze bacterial communities in volunteer and inflammatory bowel disease (IBD) patient fecal samples extracted using widely used DNA extraction kits in established gastrointestinal research laboratories. Fecal samples from two healthy volunteers (H3 and H4) and two relapsing IBD patients (I1 and I2) were investigated. DNA extraction was undertaken using MoBio Powersoil and MP Biomedicals FastDNA SPIN Kit for Soil DNA extraction kits. PCR amplification for pyrosequencing of bacterial 16S rRNA genes was performed in both laboratories on all samples. Hierarchical clustering of sequencing data was done using the Yue and Clayton similarity coefficient. DNA extracted using the FastDNA kit and the MoBio kit gave median DNA concentrations of 475 (interquartile range 228-561) and 22 (IQR 9-36) ng/µL respectively (p<0.0001). Hierarchical clustering of sequence data by Yue and Clayton coefficient revealed four clusters. Samples from individuals H3 and I2 clustered by patient; however, samples from patient I1 extracted with the MoBio kit clustered with samples from patient H4 rather than the other I1 samples. Linear modelling on relative abundance of common bacterial families revealed significant differences between kits; samples extracted with MoBio Powersoil showed significantly increased Bacteroidaceae, Ruminococcaceae and Porphyromonadaceae, and lower Enterobacteriaceae, Lachnospiraceae, Clostridiaceae, and Erysipelotrichaceae (p<0.05). This study demonstrates significant differences in DNA yield and bacterial DNA composition when comparing DNA extracted from the same fecal sample with different extraction kits. This highlights the importance of ensuring that samples in a study are prepared with the same method, and the need for caution when cross-comparing studies that use different methods.

  16. A new fast direct solver for the boundary element method

    NASA Astrophysics Data System (ADS)

    Huang, S.; Liu, Y. J.

    2017-09-01

    A new fast direct linear equation solver for the boundary element method (BEM) is presented in this paper. The idea of the new fast direct solver stems from the concept of the hierarchical off-diagonal low-rank matrix. The hierarchical off-diagonal low-rank matrix can be decomposed into the multiplication of several diagonal block matrices. The inverse of the hierarchical off-diagonal low-rank matrix can be calculated efficiently with the Sherman-Morrison-Woodbury formula. In this paper, a more general and efficient approach to approximate the coefficient matrix of the BEM with the hierarchical off-diagonal low-rank matrix is proposed. Compared to the current fast direct solver based on the hierarchical off-diagonal low-rank matrix, the proposed method is suitable for solving general 3-D boundary element models. Several numerical examples of 3-D potential problems with the total number of unknowns up to above 200,000 are presented. The results show that the new fast direct solver can be applied to solve large 3-D BEM models accurately and with better efficiency compared with the conventional BEM.

  17. Hierarchical Linear Modeling Analyses of NEO-PI-R Scales In the Baltimore Longitudinal Study of Aging

    PubMed Central

    Terracciano, Antonio; McCrae, Robert R.; Brant, Larry J.; Costa, Paul T.

    2009-01-01

    We examined age trends in the five factors and 30 facets assessed by the Revised NEO Personality Inventory in Baltimore Longitudinal Study of Aging data (N = 1,944; 5,027 assessments) collected between 1989 and 2004. Consistent with cross-sectional results, Hierarchical Linear Modeling analyses showed gradual personality changes in adulthood: a decline up to age 80 in Neuroticism, stability and then decline in Extraversion, decline in Openness, increase in Agreeableness, and increase up to age 70 in Conscientiousness. Some facets showed different curves from the factor they define. Birth cohort effects were modest, and there were no consistent Gender × Age interactions. Significant non-normative changes were found for all five factors; they were not explained by attrition but might be due to genetic factors, disease, or life experience. PMID:16248708

  18. Linear-scaling density-functional simulations of charged point defects in Al2O3 using hierarchical sparse matrix algebra.

    PubMed

    Hine, N D M; Haynes, P D; Mostofi, A A; Payne, M C

    2010-09-21

    We present calculations of formation energies of defects in an ionic solid (Al(2)O(3)) extrapolated to the dilute limit, corresponding to a simulation cell of infinite size. The large-scale calculations required for this extrapolation are enabled by developments in the approach to parallel sparse matrix algebra operations, which are central to linear-scaling density-functional theory calculations. The computational cost of manipulating sparse matrices, whose sizes are determined by the large number of basis functions present, is greatly improved with this new approach. We present details of the sparse algebra scheme implemented in the ONETEP code using hierarchical sparsity patterns, and demonstrate its use in calculations on a wide range of systems, involving thousands of atoms on hundreds to thousands of parallel processes.

  19. Positive affect predicts avoidance goals in social interaction anxiety: testing a hierarchical model of social goals.

    PubMed

    Trew, Jennifer L; Alden, Lynn E

    2012-01-01

    Models of self-regulation suggest that social goals may contribute to interpersonal and affective difficulties, yet little research has addressed this issue in the context of social anxiety. The present studies evaluated a hierarchical model of approach and avoidance in the context of social interaction anxiety, with affect as a mediating factor in the relationship between motivational tendencies and social goals. This model was refined in one undergraduate sample (N = 186) and cross-validated in a second sample (N = 195). The findings support hierarchical relationships between motivational tendencies, social interaction anxiety, affect, and social goals, with higher positive affect predicting fewer avoidance goals in both samples. Implications for the treatment of social interaction anxiety are discussed.

  20. The identification of credit card encoders by hierarchical cluster analysis of the jitters of magnetic stripes.

    PubMed

    Leung, S C; Fung, W K; Wong, K H

    1999-01-01

    The relative bit density variation graphs of 207 specimen credit cards processed by 12 encoding machines were examined first visually, and then classified by means of hierarchical cluster analysis. Twenty-nine credit cards being treated as 'questioned' samples were tested by way of cluster analysis against 'controls' derived from known encoders. It was found that hierarchical cluster analysis provided a high accuracy of identification with all 29 'questioned' samples classified correctly. On the other hand, although visual comparison of jitter graphs was less discriminating, it was nevertheless capable of giving a reasonably accurate result.

  1. Factors Associated with Job Satisfaction among University Teachers in Northeastern Region of China: A Cross-Sectional Study.

    PubMed

    Pan, Bochen; Shen, Xue; Liu, Li; Yang, Yilong; Wang, Lie

    2015-10-14

    Teachers' job satisfaction is one of the key factors in institutional dynamics and is generally considered to be the primary variable by which the effectiveness of an organization's human resource is evaluated. The objectives of this study were to assess the level of job satisfaction among university teachers and to clarify the associated factors. A cross-sectional study was conducted between November 2013 and January 2014. Teachers from six universities in Shenyang, China were randomly sampled. The job satisfaction scale Minnesota Satisfaction Questionnaire (MSQ), perceived organizational support (POS), psychological capital questionnaire (PCQ-24), and effort-reward imbalance scale (ERI) together with questions about demographic and working factors were administered in questionnaires distributed to 1500 university teachers. Hierarchical linear regression analyses were performed to explore the related factors. 1210 effective responses were obtained (effective respondent rate 80.7%). The average score of overall job satisfaction was 69.71. Hierarchical linear regression analysis revealed that turnover intention, occupational stress and chronic disease all had negative impacts on job satisfaction, whereas perceived organizational support, psychological capital and higher monthly income were positively associated with job satisfaction among the university teachers. Age was also linked to the level of job satisfaction. All the variables explained 60.7% of the variance in job satisfaction. Chinese university teachers had a moderate level of job satisfaction. Demographic and working characteristics were associated factors for job satisfaction. Perceived organizational support showed the strongest association with job satisfaction. RESULTS of the study indicate that improving the perceived organizational support may increase the level of job satisfaction for university teachers.

  2. Temperament and job stress in Japanese company employees.

    PubMed

    Sakai, Y; Akiyama, T; Miyake, Y; Kawamura, Y; Tsuda, H; Kurabayashi, L; Tominaga, M; Noda, T; Akiskal, K; Akiskal, H

    2005-03-01

    This study aims to demonstrate the relevance of temperament to job stress. The subjects were 848 male and 366 female Japanese company employees. Temperament Evaluation of Memphis, Pisa, Paris and San Diego-Autoquestionnaire version (TEMPS-A) and Munich Personality Test (MPT) were administered to assess temperaments, and the NIOSH Generic Job Stress Questionnaire (GJSQ) to assess job stress. We used hierarchical multiple linear regression analysis in order to demonstrate whether temperament variables added any unique variance after controlling the effects of other predictors such as gender, age and job rank. In all subscales of the GJSQ, temperament predicted a large share of the variance in job stress. Remarkably, for interpersonal relationship stressors, the temperament variables added greater variance than that predicted by gender, age and job rank. Summary of the hierarchical linear regression analysis showed that the irritable temperament was associated with the most prominent vulnerability, followed by cyclothymic and anxious temperaments. The schizoid temperament had difficulty in the area of social support. On the other hand, the hyperthymic temperament displayed significant robustness in facing most job stressors; the melancholic type showed a similar pattern to a lesser degree. The findings may be different in a clinical Japanese sample, or a cohort of healthy employees from a different cultural background. Temperament influences job stress significantly-indeed, it impacts on such stress with greater magnitude than age, gender and job rank in most areas examined. Temperament influences interpersonal relationship stressors more than workload-related stressors. Interestingly, in line with previous clinical and theoretical formulations, the hyperthymic and melancholic types actually appear to be "hyper-adapted" to the workplace.

  3. Three-Dimensional Hierarchical Plasmonic Nano-Architecture Enhanced Surface-Enhanced Raman Scattering Immuno-Sensor for Cancer Biomarker Detection in Blood Plasma

    PubMed Central

    Li, Ming; Cushing, Scott K.; Zhang, Jianming; Suri, Savan; Evans, Rebecca; Petros, William P.; Gibson, Laura F.; Ma, Dongling; Liu, Yuxin; Wu, Nianqiang

    2013-01-01

    A three-dimensional (3D) hierarchical plasmonic nano-architecture has been designed for a sensitive surface-enhanced Raman scattering (SERS) immuno-sensor for protein biomarker detection. The capture antibody molecules are immobilized on a plasmonic gold triangle nano-array pattern. On the other hand, the detection antibody molecules are linked to the gold nano-star@Raman-reporter@silica sandwich nanoparticles. When protein biomarkers are present, the sandwich nanoparticles are captured over the gold triangle nano-array, forming a confined 3D plasmonic field, leading to the enhanced electromagnetic field in intensity and in 3D space. As a result, the Raman reporter molecules are exposed to a high density of “hot spots”, which amplifies the Raman signal remarkably, improving the sensitivity of the SERS immuno-sensor. This SERS immuno-sensor exhibits a wide linear range (0.1 pg/mL to 10 ng/mL), and a low limit of detection (7 fg/mL) toward human immunoglobulin G (IgG) protein in the buffer solution. This biosensor has been successfully used for detection of the vascular endothelial growth factor (VEGF) in the human blood plasma from clinical breast cancer patient samples. PMID:23659430

  4. Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials

    PubMed Central

    Hobbs, Brian P.; Carlin, Bradley P.; Mandrekar, Sumithra J.; Sargent, Daniel J.

    2011-01-01

    Summary Bayesian clinical trial designs offer the possibility of a substantially reduced sample size, increased statistical power, and reductions in cost and ethical hazard. However when prior and current information conflict, Bayesian methods can lead to higher than expected Type I error, as well as the possibility of a costlier and lengthier trial. This motivates an investigation of the feasibility of hierarchical Bayesian methods for incorporating historical data that are adaptively robust to prior information that reveals itself to be inconsistent with the accumulating experimental data. In this paper, we present several models that allow for the commensurability of the information in the historical and current data to determine how much historical information is used. A primary tool is elaborating the traditional power prior approach based upon a measure of commensurability for Gaussian data. We compare the frequentist performance of several methods using simulations, and close with an example of a colon cancer trial that illustrates a linear models extension of our adaptive borrowing approach. Our proposed methods produce more precise estimates of the model parameters, in particular conferring statistical significance to the observed reduction in tumor size for the experimental regimen as compared to the control regimen. PMID:21361892

  5. Multimedia Classifier

    NASA Astrophysics Data System (ADS)

    Costache, G. N.; Gavat, I.

    2004-09-01

    Along with the aggressive growing of the amount of digital data available (text, audio samples, digital photos and digital movies joined all in the multimedia domain) the need for classification, recognition and retrieval of this kind of data became very important. In this paper will be presented a system structure to handle multimedia data based on a recognition perspective. The main processing steps realized for the interesting multimedia objects are: first, the parameterization, by analysis, in order to obtain a description based on features, forming the parameter vector; second, a classification, generally with a hierarchical structure to make the necessary decisions. For audio signals, both speech and music, the derived perceptual features are the melcepstral (MFCC) and the perceptual linear predictive (PLP) coefficients. For images, the derived features are the geometric parameters of the speaker mouth. The hierarchical classifier consists generally in a clustering stage, based on the Kohonnen Self-Organizing Maps (SOM) and a final stage, based on a powerful classification algorithm called Support Vector Machines (SVM). The system, in specific variants, is applied with good results in two tasks: the first, is a bimodal speech recognition which uses features obtained from speech signal fused to features obtained from speaker's image and the second is a music retrieval from large music database.

  6. Linear regulator design for stochastic systems by a multiple time scales method

    NASA Technical Reports Server (NTRS)

    Teneketzis, D.; Sandell, N. R., Jr.

    1976-01-01

    A hierarchically-structured, suboptimal controller for a linear stochastic system composed of fast and slow subsystems is considered. The controller is optimal in the limit as the separation of time scales of the subsystems becomes infinite. The methodology is illustrated by design of a controller to suppress the phugoid and short period modes of the longitudinal dynamics of the F-8 aircraft.

  7. MATHEMATICAL MODELING OF PESTICIDES IN THE ENVIRONMENT: CURRENT AND FUTURE DEVELOPMENTS

    EPA Science Inventory

    Transport models, total ecosystem models with aggregated linear approximations, evaluative models, hierarchical models, and influence analysis methods are mathematical techniques that are particularly applicable to the problems encountered when characterizing pesticide chemicals ...

  8. A hierarchical model for spatial capture-recapture data

    USGS Publications Warehouse

    Royle, J. Andrew; Young, K.V.

    2008-01-01

    Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

  9. Depression, Control, and Climate: An Examination of Factors Impacting Teaching Quality in Preschool Classrooms

    PubMed Central

    Sandilos, Lia E.; Cycyk, Lauren M.; Hammer, Carol Scheffner; Sawyer, Brook E.; López, Lisa; Blair, Clancy

    2015-01-01

    Research Findings This study investigated the relationship of preschool teachers' self-reported depressive symptomatology, perception of classroom control, and perception of school climate to classroom quality as measured by the Classroom Assessment Scoring System Pre-K. The sample consisted of 59 urban preschool classrooms serving low-income and linguistically diverse students in the northeastern and southeastern United States. Results of hierarchical linear modeling revealed that teachers' individual reports of depressive symptomatology were significantly and negatively predictive of the observed quality of their instructional support and classroom organization. Practice or Policy The findings of this study have implications for increasing access to mental health supports for teachers in an effort to minimize depressive symptoms and potentially improve classroom quality. PMID:26924914

  10. Identification of indicator congeners and evaluation of emission pattern of polychlorinated naphthalenes in industrial stack gas emissions by statistical analyses.

    PubMed

    Liu, Guorui; Cai, Zongwei; Zheng, Minghui; Jiang, Xiaoxu; Nie, Zhiqiang; Wang, Mei

    2015-01-01

    Identifying marker congeners of unintentionally produced polychlorinated naphthalenes (PCNs) from industrial thermal sources might be useful for predicting total PCN (∑2-8PCN) emissions by the determination of only indicator congeners. In this study, potential indicator congeners were identified based on the PCN data in 122 stack gas samples from over 60 plants involved in more than ten industrial thermal sources reported in our previous case studies. Linear regression analyses identified that the concentrations of CN27/30, CN52/60, and CN66/67 correlated significantly with ∑2-8PCN (R(2)=0.77, 0.80, and 0.58, respectively; n=122, p<0.05), which might be good candidates for indicator congeners. Equations describing relationships between indicators and ∑2-8PCN were established. The linear regression analyses involving 122 samples showed that the relationships between the indicator congeners and ∑2-8PCN were not significantly affected by factors such as industry types, raw materials used, or operating conditions. Hierarchical cluster analysis and similarity calculations for the 122 stack gas samples were adopted to group those samples and evaluating their similarity and difference based on the PCN homolog distributions from different industrial thermal sources. Generally, the fractions of less chlorinated homologs comprised of di-, tri-, and tetra-homologs were much higher than that of more chlorinated homologs for up to 111 stack gas samples contained in group 1 and 2, which indicating the dominance of lower chlorinated homologs in stack gas from industrial thermal sources. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance

    USGS Publications Warehouse

    Fiske, Ian J.; Chandler, Richard B.

    2011-01-01

    Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.

  12. The traveling salesman problem: a hierarchical model.

    PubMed

    Graham, S M; Joshi, A; Pizlo, Z

    2000-10-01

    Our review of prior literature on spatial information processing in perception, attention, and memory indicates that these cognitive functions involve similar mechanisms based on a hierarchical architecture. The present study extends the application of hierarchical models to the area of problem solving. First, we report results of an experiment in which human subjects were tested on a Euclidean traveling salesman problem (TSP) with 6 to 30 cities. The subject's solutions were either optimal or near-optimal in length and were produced in a time that was, on average, a linear function of the number of cities. Next, the performance of the subjects is compared with that of five representative artificial intelligence and operations research algorithms, that produce approximate solutions for Euclidean problems. None of these algorithms was found to be an adequate psychological model. Finally, we present a new algorithm for solving the TSP, which is based on a hierarchical pyramid architecture. The performance of this new algorithm is quite similar to the performance of the subjects.

  13. Hierarchical 3-dimensional nickel-iron nanosheet arrays on carbon fiber paper as a novel electrode for non-enzymatic glucose sensing.

    PubMed

    Kannan, Palanisamy; Maiyalagan, Thandavarayan; Marsili, Enrico; Ghosh, Srabanti; Niedziolka-Jönsson, Joanna; Jönsson-Niedziolka, Martin

    2016-01-14

    Three-dimensional nickel-iron (3-D/Ni-Fe) nanostructures are exciting candidates for various applications because they produce more reaction-active sites than 1-D and 2-D nanostructured materials and exhibit attractive optical, electrical and catalytic properties. In this work, freestanding 3-D/Ni-Fe interconnected hierarchical nanosheets, hierarchical nanospheres, and porous nanospheres are directly grown on a flexible carbon fiber paper (CFP) substrate by a single-step hydrothermal process. Among the nanostructures, 3-D/Ni-Fe interconnected hierarchical nanosheets show excellent electrochemical properties because of its high conductivity, large specific active surface area, and mesopores on its walls (vide infra). The 3-D/Ni-Fe hierarchical nanosheet array modified CFP substrate is further explored as a novel electrode for electrochemical non-enzymatic glucose sensor application. The 3-D/Ni-Fe hierarchical nanosheet arrays exhibit significant catalytic activity towards the electrochemical oxidation of glucose, as compared to the 3-D/Ni-Fe hierarchical nanospheres, and porous nanospheres. The 3-D/Ni-Fe hierarchical nanosheet arrays can access a large amount of glucose molecules on their surface (mesopore walls) for an efficient electrocatalytic oxidation process. Moreover, 3-D/Ni-Fe hierarchical nanosheet arrays showed higher sensitivity (7.90 μA μM(-1) cm(-2)) with wide linear glucose concentration ranging from 0.05 μM to 0.2 mM, and the low detection limit (LOD) of 0.031 μM (S/N = 3) is achieved by the amperometry method. Further, the 3-D/Ni-Fe hierarchical nanosheet array modified CFP electrode can be demonstrated to have excellent selectivity towards the detection of glucose in the presence of 500-fold excess of major important interferents. All these results indicate that 3-D/Ni-Fe hierarchical nanosheet arrays are promising candidates for non-enzymatic glucose sensing.

  14. Estimation of annual energy production using dynamic wake meandering in combination with ambient CFD solutions

    NASA Astrophysics Data System (ADS)

    Hahn, S.; Machefaux, E.; Hristov, Y. V.; Albano, M.; Threadgill, R.

    2016-09-01

    In the present study, combination of the standalone dynamic wake meandering (DWM) model with Reynolds-averaged Navier-Stokes (RANS) CFD solutions for ambient ABL flows is introduced, and its predictive performance for annual energy production (AEP) is evaluated against Vestas’ SCADA data for six operating wind farms over semi-complex terrains under neutral conditions. The performances of conventional linear and quadratic wake superposition techniques are also compared, together with the in-house implemention of successive hierarchical merging approaches. As compared to our standard procedure based on the Jensen model in WindPRO, the overall results are promising, leading to a significant improvement in AEP accuracy for four of the six sites. While the conventional linear superposition shows the best performance for the improved four sites, the hierarchical square superposition shows the least deteriorated result for the other two sites.

  15. An exploratory analysis of treatment completion and client and organizational factors using hierarchical linear modeling.

    PubMed

    Woodward, Albert; Das, Abhik; Raskin, Ira E; Morgan-Lopez, Antonio A

    2006-11-01

    Data from the Alcohol and Drug Services Study (ADSS) are used to analyze the structure and operation of the substance abuse treatment industry in the United States. Published literature contains little systematic empirical analysis of the interaction between organizational characteristics and treatment outcomes. This paper addresses that deficit. It develops and tests a hierarchical linear model (HLM) to address questions about the empirical relationship between treatment inputs (industry costs, types and use of counseling and medical personnel, diagnosis mix, patient demographics, and the nature and level of services used in substance abuse treatment), and patient outcomes (retention and treatment completion rates). The paper adds to the literature by demonstrating a direct and statistically significant link between treatment completion and the organizational and staffing structure of the treatment setting. Related reimbursement issues, questions for future analysis, and limitations of the ADSS for this analysis are discussed.

  16. Novel Catalyst for the Chirality Selective Synthesis of Single Walled Carbon Nanotubes

    DTIC Science & Technology

    2015-05-12

    hierarchical structures comprising nitrogen- doped reduced GO (rGO) and acid- oxidized SWCNTs was produced using a linear hydrothermal microreactor. Fiber...structures comprising nitrogen- doped reduced GO (rGO) and acidoxidized SWCNTs was produced using a linear hydrothermal microreactor. Fiber micro... doped into Co/SiO2 catalysts to change their chirality selectivity. Further, enrichment of (9,8) nanotubes was carried out by extraction using fluorene

  17. Hierarchical screening for multiple mental disorders.

    PubMed

    Batterham, Philip J; Calear, Alison L; Sunderland, Matthew; Carragher, Natacha; Christensen, Helen; Mackinnon, Andrew J

    2013-10-01

    There is a need for brief, accurate screening when assessing multiple mental disorders. Two-stage hierarchical screening, consisting of brief pre-screening followed by a battery of disorder-specific scales for those who meet diagnostic criteria, may increase the efficiency of screening without sacrificing precision. This study tested whether more efficient screening could be gained using two-stage hierarchical screening than by administering multiple separate tests. Two Australian adult samples (N=1990) with high rates of psychopathology were recruited using Facebook advertising to examine four methods of hierarchical screening for four mental disorders: major depressive disorder, generalised anxiety disorder, panic disorder and social phobia. Using K6 scores to determine whether full screening was required did not increase screening efficiency. However, pre-screening based on two decision tree approaches or item gating led to considerable reductions in the mean number of items presented per disorder screened, with estimated item reductions of up to 54%. The sensitivity of these hierarchical methods approached 100% relative to the full screening battery. Further testing of the hierarchical screening approach based on clinical criteria and in other samples is warranted. The results demonstrate that a two-phase hierarchical approach to screening multiple mental disorders leads to considerable increases efficiency gains without reducing accuracy. Screening programs should take advantage of prescreeners based on gating items or decision trees to reduce the burden on respondents. © 2013 Elsevier B.V. All rights reserved.

  18. Formation Flying With Decentralized Control in Libration Point Orbits

    NASA Technical Reports Server (NTRS)

    Folta, David; Carpenter, J. Russell; Wagner, Christoph

    2000-01-01

    A decentralized control framework is investigated for applicability of formation flying control in libration orbits. The decentralized approach, being non-hierarchical, processes only direct measurement data, in parallel with the other spacecraft. Control is accomplished via linearization about a reference libration orbit with standard control using a Linear Quadratic Regulator (LQR) or the GSFC control algorithm. Both are linearized about the current state estimate as with the extended Kalman filter. Based on this preliminary work, the decentralized approach appears to be feasible for upcoming libration missions using distributed spacecraft.

  19. Using hierarchical linear growth models to evaluate protective mechanisms that mediate science achievement

    NASA Astrophysics Data System (ADS)

    von Secker, Clare Elaine

    The study of students at risk is a major topic of science education policy and discussion. Much research has focused on describing conditions and problems associated with the statistical risk of low science achievement among individuals who are members of groups characterized by problems such as poverty and social disadvantage. But outcomes attributed to these factors do not explain the nature and extent of mechanisms that account for differences in performance among individuals at risk. There is ample theoretical and empirical evidence that demographic differences should be conceptualized as social contexts, or collections of variables, that alter the psychological significance and social demands of life events, and affect subsequent relationships between risk and resilience. The hierarchical linear growth models used in this dissertation provide greater specification of the role of social context and the protective effects of attitude, expectations, parenting practices, peer influences, and learning opportunities on science achievement. While the individual influences of these protective factors on science achievement were small, their cumulative effect was substantial. Meta-analysis conducted on the effects associated with psychological and environmental processes that mediate risk mechanisms in sixteen social contexts revealed twenty-two significant differences between groups of students. Positive attitudes, high expectations, and more intense science course-taking had positive effects on achievement of all students, although these factors were not equally protective in all social contexts. In general, effects associated with authoritative parenting and peer influences were negative, regardless of social context. An evaluation comparing the performance and stability of hierarchical linear growth models with traditional repeated measures models is included as well.

  20. The Role of Family Environment in Depressive Symptoms among University Students: A Large Sample Survey in China

    PubMed Central

    Yang, Yanjie; Chen, Lu; Qiu, Xiaohui; Qiao, Zhengxue; Zhou, Jiawei; Pan, Hui; Ban, Bo; Zhu, Xiongzhao; He, Jincai; Ding, Yongqing; Bai, Bing

    2015-01-01

    Objective To explore the relationship between family environment and depressive symptoms and to evaluate the influence of hard and soft family environmental factors on depression levels in a large sample of university students in China. Methods A multi-stage stratified sampling procedure was used to select 6,000 participants. The response rate was 88.8%, with 5,329 students completing the Beck Depression Inventory (BDI) and the Family Environment Scale Chinese Version (FES-CV), which was adapted for the Chinese population. Differences between the groups were tested for significance by the Student’s t-test; ANOVA was used to test continuous variables. The relationship between soft family environmental factors and BDI were tested by Pearson correlation analysis. Hierarchical linear regression analysis was conducted to model the effects of hard environmental factors and soft environmental factors on depression in university students. Results A total of 11.8% of students scored above the threshold of moderate depression(BDI≧14). Hard family environmental factors such as parent relationship, family economic status, level of parental literacy and non-intact family structure were associated with depressive symptoms. The soft family environmental factors—conflict and control—were positively associated with depression, while cohesion was negatively related to depressive symptom after controlling for other important associates of depression. Hierarchical regression analysis indicated that the soft family environment correlates more strongly with depression than the hard family environment. Conclusions Soft family environmental factors—especially cohesion, conflict and control—appeared to play an important role in the occurrence of depressive symptoms. These findings underline the significance of the family environment as a source of risk factors for depression among university students in China and suggest that family-based interventions and improvement are very important to reduce depression among university students. PMID:26629694

  1. The Role of Family Environment in Depressive Symptoms among University Students: A Large Sample Survey in China.

    PubMed

    Yu, Yunmiao; Yang, Xiuxian; Yang, Yanjie; Chen, Lu; Qiu, Xiaohui; Qiao, Zhengxue; Zhou, Jiawei; Pan, Hui; Ban, Bo; Zhu, Xiongzhao; He, Jincai; Ding, Yongqing; Bai, Bing

    2015-01-01

    To explore the relationship between family environment and depressive symptoms and to evaluate the influence of hard and soft family environmental factors on depression levels in a large sample of university students in China. A multi-stage stratified sampling procedure was used to select 6,000 participants. The response rate was 88.8%, with 5,329 students completing the Beck Depression Inventory (BDI) and the Family Environment Scale Chinese Version (FES-CV), which was adapted for the Chinese population. Differences between the groups were tested for significance by the Student's t-test; ANOVA was used to test continuous variables. The relationship between soft family environmental factors and BDI were tested by Pearson correlation analysis. Hierarchical linear regression analysis was conducted to model the effects of hard environmental factors and soft environmental factors on depression in university students. A total of 11.8% of students scored above the threshold of moderate depression (BDI≧14). Hard family environmental factors such as parent relationship, family economic status, level of parental literacy and non-intact family structure were associated with depressive symptoms. The soft family environmental factors--conflict and control--were positively associated with depression, while cohesion was negatively related to depressive symptom after controlling for other important associates of depression. Hierarchical regression analysis indicated that the soft family environment correlates more strongly with depression than the hard family environment. Soft family environmental factors--especially cohesion, conflict and control--appeared to play an important role in the occurrence of depressive symptoms. These findings underline the significance of the family environment as a source of risk factors for depression among university students in China and suggest that family-based interventions and improvement are very important to reduce depression among university students.

  2. Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities

    USGS Publications Warehouse

    Royle, J. Andrew; Dorazio, Robert M.

    2008-01-01

    A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.

  3. Word Order and Voice Influence the Timing of Verb Planning in German Sentence Production.

    PubMed

    Sauppe, Sebastian

    2017-01-01

    Theories of incremental sentence production make different assumptions about when speakers encode information about described events and when verbs are selected, accordingly. An eye tracking experiment on German testing the predictions from linear and hierarchical incrementality about the timing of event encoding and verb planning is reported. In the experiment, participants described depictions of two-participant events with sentences that differed in voice and word order. Verb-medial active sentences and actives and passives with sentence-final verbs were compared. Linear incrementality predicts that sentences with verbs placed early differ from verb-final sentences because verbs are assumed to only be planned shortly before they are articulated. By contrast, hierarchical incrementality assumes that speakers start planning with relational encoding of the event. A weak version of hierarchical incrementality assumes that only the action is encoded at the outset of formulation and selection of lexical verbs only occurs shortly before they are articulated, leading to the prediction of different fixation patterns for verb-medial and verb-final sentences. A strong version of hierarchical incrementality predicts no differences between verb-medial and verb-final sentences because it assumes that verbs are always lexically selected early in the formulation process. Based on growth curve analyses of fixations to agent and patient characters in the described pictures, and the influence of character humanness and the lack of an influence of the visual salience of characters on speakers' choice of active or passive voice, the current results suggest that while verb planning does not necessarily occur early during formulation, speakers of German always create an event representation early.

  4. Intelligence and Accidents: A Multilevel Model

    DTIC Science & Technology

    2006-05-06

    individuals with low scores. Analysis Procedures The HLM 6 computer program (Raudenbush, Bryk, Cheong, & Congdon , 2004) was employed to conduct the...Cheong, Y. F., & Congdon , R. (2004). HLM 6: Hierarchical linear and nonlinear modeling. Chicago: Scientific Software International. Reynolds, D. H

  5. Community turnover of wood-inhabiting fungi across hierarchical spatial scales.

    PubMed

    Abrego, Nerea; García-Baquero, Gonzalo; Halme, Panu; Ovaskainen, Otso; Salcedo, Isabel

    2014-01-01

    For efficient use of conservation resources it is important to determine how species diversity changes across spatial scales. In many poorly known species groups little is known about at which spatial scales the conservation efforts should be focused. Here we examined how the community turnover of wood-inhabiting fungi is realised at three hierarchical levels, and how much of community variation is explained by variation in resource composition and spatial proximity. The hierarchical study design consisted of management type (fixed factor), forest site (random factor, nested within management type) and study plots (randomly placed plots within each study site). To examine how species richness varied across the three hierarchical scales, randomized species accumulation curves and additive partitioning of species richness were applied. To analyse variation in wood-inhabiting species and dead wood composition at each scale, linear and Permanova modelling approaches were used. Wood-inhabiting fungal communities were dominated by rare and infrequent species. The similarity of fungal communities was higher within sites and within management categories than among sites or between the two management categories, and it decreased with increasing distance among the sampling plots and with decreasing similarity of dead wood resources. However, only a small part of community variation could be explained by these factors. The species present in managed forests were in a large extent a subset of those species present in natural forests. Our results suggest that in particular the protection of rare species requires a large total area. As managed forests have only little additional value complementing the diversity of natural forests, the conservation of natural forests is the key to ecologically effective conservation. As the dissimilarity of fungal communities increases with distance, the conserved natural forest sites should be broadly distributed in space, yet the individual conserved areas should be large enough to ensure local persistence.

  6. Community Turnover of Wood-Inhabiting Fungi across Hierarchical Spatial Scales

    PubMed Central

    Abrego, Nerea; García-Baquero, Gonzalo; Halme, Panu; Ovaskainen, Otso; Salcedo, Isabel

    2014-01-01

    For efficient use of conservation resources it is important to determine how species diversity changes across spatial scales. In many poorly known species groups little is known about at which spatial scales the conservation efforts should be focused. Here we examined how the community turnover of wood-inhabiting fungi is realised at three hierarchical levels, and how much of community variation is explained by variation in resource composition and spatial proximity. The hierarchical study design consisted of management type (fixed factor), forest site (random factor, nested within management type) and study plots (randomly placed plots within each study site). To examine how species richness varied across the three hierarchical scales, randomized species accumulation curves and additive partitioning of species richness were applied. To analyse variation in wood-inhabiting species and dead wood composition at each scale, linear and Permanova modelling approaches were used. Wood-inhabiting fungal communities were dominated by rare and infrequent species. The similarity of fungal communities was higher within sites and within management categories than among sites or between the two management categories, and it decreased with increasing distance among the sampling plots and with decreasing similarity of dead wood resources. However, only a small part of community variation could be explained by these factors. The species present in managed forests were in a large extent a subset of those species present in natural forests. Our results suggest that in particular the protection of rare species requires a large total area. As managed forests have only little additional value complementing the diversity of natural forests, the conservation of natural forests is the key to ecologically effective conservation. As the dissimilarity of fungal communities increases with distance, the conserved natural forest sites should be broadly distributed in space, yet the individual conserved areas should be large enough to ensure local persistence. PMID:25058128

  7. Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space.

    PubMed

    Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J

    2010-05-01

    Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.

  8. Ultra-facile fabrication of phosphorus doped egg-like hierarchic porous carbon with superior supercapacitance performance by microwave irradiation combining with self-activation strategy

    NASA Astrophysics Data System (ADS)

    Zhang, Deyi; Han, Mei; Li, Yubing; He, Jingjing; Wang, Bing; Wang, Kunjie; Feng, Huixia

    2017-12-01

    Herein, we report an ultra-facile fabrication method for a phosphorus doped egg-like hierarchic porous carbon by microwave irradiation combining with self-activation strategy under air atmosphere. Comparing with the traditional pyrolytic carbonization method, the reported method exhibits incomparable merits, such as high energy efficiency, ultra-fast and inert atmosphere protection absent fabrication process. Similar morphology and graphitization degree with the sample fabricated by the traditional pyrolytic carbonization method under inert atmosphere protection for 2 h can be easily achieved by the reported microwave irradiation method just for 3 min under ambient atmosphere. The samples fabricated by the reported method display a unique phosphorus doped egg-like hierarchic porous structure, high specific surface area (1642 m2 g-1) and large pore volume (2.04 cm3 g-1). Specific capacitance of the samples fabricated by the reported method reaches up to 209 F g-1, and over 96.2% of initial capacitance remains as current density increasing from 0.5 to 20 A g-1, indicating the superior capacitance performance of the fabricated samples. The hierarchic porous structure, opened microporosity, additional pseudocapacitance, high electrolyte-accessible surface area and good conductivity make essential contribution to its superior capacitance performance.

  9. Resolving the Framework Position of Organic Structure-Directing Agents in Hierarchical Zeolites via Polarized Stimulated Raman Scattering.

    PubMed

    Fleury, Guillaume; Steele, Julian A; Gerber, Iann C; Jolibois, F; Puech, P; Muraoka, Koki; Keoh, Sye Hoe; Chaikittisilp, Watcharop; Okubo, Tatsuya; Roeffaers, Maarten B J

    2018-04-05

    The direct synthesis of hierarchically intergrown silicalite-1 can be achieved using a specific diquaternary ammonium agent. However, the location of these molecules in the zeolite framework, which is critical to understand the formation of the material, remains unclear. Where traditional characterization tools have previously failed, herein we use polarized stimulated Raman scattering (SRS) microscopy to resolve molecular organization inside few-micron-sized crystals. Through a combination of experiment and first-principles calculations, our investigation reveals the preferential location of the templating agent inside the linear pores of the MFI framework. Besides illustrating the attractiveness of SRS microscopy in the field of material science to study and spatially resolve local molecular distribution as well as orientation, these results can be exploited in the design of new templating agents for the preparation of hierarchical zeolites.

  10. Iron status as a covariate in methylmercury-associated neurotoxicity risk.

    PubMed

    Fonseca, Márlon de Freitas; De Souza Hacon, Sandra; Grandjean, Philippe; Choi, Anna Lai; Bastos, Wanderley Rodrigues

    2014-04-01

    Intrauterine methylmercury exposure and prenatal iron deficiency negatively affect offspring's brain development. Since fish is a major source of both methylmercury and iron, occurrence of negative confounding may affect the interpretation of studies concerning cognition. We assessed relationships between methylmercury exposure and iron-status in childbearing females from a population naturally exposed to methylmercury through fish intake (Amazon). We concluded a census (refuse <20%) collecting samples from 274 healthy females (12-49 years) for hair-mercury determination and assessed iron-status through red cell tests and determination of serum ferritin and iron. Reactive C protein and thyroid hormones was used for excluding inflammation and severe thyroid dysfunctions that could affect results. We assessed the association between iron-status and hair-mercury by bivariate correlation analysis and also by different multivariate models: linear regression (to check trends); hierarchical agglomerative clustering method (groups of variables correlated with each other); and factor analysis (to examine redundancy or duplication from a set of correlated variables). Hair-mercury correlated weakly with mean corpuscular volume (r=.141; P=.020) and corpuscular hemoglobin (r=.132; .029), but not with the best biomarker of iron-status, ferritin (r=.037; P=.545). In the linear regression analysis, methylmercury exposure showed weak association with age-adjusted ferritin; age had a significant coefficient (Beta=.015; 95% CI: .003-.027; P=.016) but ferritin did not (Beta=.034; 95% CI: -.147 to .216; P=.711). In the hierarchical agglomerative clustering method, hair-mercury and iron-status showed the smallest similarities. Regarding factor analysis, iron-status and hair-mercury loaded different uncorrelated components. We concluded that iron-status and methylmercury exposure probably occur in an independent way. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. All-in-one bioprobe devised with hierarchical-ordered magnetic NiCo2O4 superstructure for ultrasensitive dual-readout immunosensor for logic diagnosis of tumor marker.

    PubMed

    Dai, Hong; Gong, Lingshan; Zhang, Shupei; Xu, Guifang; Li, Yilin; Hong, Zhensheng; Lin, Yanyu

    2016-03-15

    A new enzyme-free all-in-one bioprobe, consisted of hematin decorated magnetic NiCo2O4 superstructure (ATS-MNS-Hb), was designed for ultrasensitive photoelectrochemical and electrochemical dual-readout immunosensing of carcinoembryonic antigen (CEA) on carbon nanohorns (CNH) support. Herein, the MNS, possessed hierarchical-ordered structure, good porosity and magnetism, acted as nanocarrier to absorb abundant Hb molecular after functionalization, providing a convenient collection means by magnetic control as well as enhanced dual-readout sensing performances. CNH superstructures were employed as support to immobilize abounding captured antibodies, and then as-designed dual mode bioprobe, covalent binding with secondary antibody of CEA, was introduced for ultrasensitive detection of CEA by sandwich immunosensing. Photoelectrochemical response originated from plentiful hematin molecular, a excellent photosensitizer with good visible light harvesting efficiency, absorbed by functionalized porous MNS. The resultant concentration dependant linear calibration range was from 10 fg/mL to 1 ng/mL with ultralow detection limit of 10 fg/mL. For electrochemical process, catalase-like property of MNS was validated, moreover, MNS-Hb hybrid exhibited much higher mimic enzyme catalytic activity and evidently amplified electrocatalytic signal, performing a wide dynamic linear range from 1 ng/mL to 40 ng/mL with low detection limit of 1 ng/mL. Additionally, due to the improved accuracy of dual signals detection, the exact diagnoses of serum samples were gotten by operating resulting dual signals with AND logic system. This work demonstrated the promising application of MNS in developing ultrasensitive, cost-effective and environment friendly dual-readout immunosensor and accurate diagnoses strategy for tumor markers. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Factors Associated with Job Satisfaction among University Teachers in Northeastern Region of China: A Cross-Sectional Study

    PubMed Central

    Pan, Bochen; Shen, Xue; Liu, Li; Yang, Yilong; Wang, Lie

    2015-01-01

    Objective: Teachers’ job satisfaction is one of the key factors in institutional dynamics and is generally considered to be the primary variable by which the effectiveness of an organization’s human resource is evaluated. The objectives of this study were to assess the level of job satisfaction among university teachers and to clarify the associated factors. Method: A cross-sectional study was conducted between November 2013 and January 2014. Teachers from six universities in Shenyang, China were randomly sampled. The job satisfaction scale Minnesota Satisfaction Questionnaire (MSQ), perceived organizational support (POS), psychological capital questionnaire (PCQ-24), and effort-reward imbalance scale (ERI) together with questions about demographic and working factors were administered in questionnaires distributed to 1500 university teachers. Hierarchical linear regression analyses were performed to explore the related factors. Results: 1210 effective responses were obtained (effective respondent rate 80.7%). The average score of overall job satisfaction was 69.71. Hierarchical linear regression analysis revealed that turnover intention, occupational stress and chronic disease all had negative impacts on job satisfaction, whereas perceived organizational support, psychological capital and higher monthly income were positively associated with job satisfaction among the university teachers. Age was also linked to the level of job satisfaction. All the variables explained 60.7% of the variance in job satisfaction. Conclusions: Chinese university teachers had a moderate level of job satisfaction. Demographic and working characteristics were associated factors for job satisfaction. Perceived organizational support showed the strongest association with job satisfaction. Results of the study indicate that improving the perceived organizational support may increase the level of job satisfaction for university teachers. PMID:26473906

  13. The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.

    PubMed

    Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun

    2017-01-01

    Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.

  14. Self-criticism, dependency, and stress reactivity: an experience sampling approach to testing Blatt and Zuroff's (1992) theory of personality predispositions to depression in high-risk youth.

    PubMed

    Adams, Philippe; Abela, John R Z; Auerbach, Randy; Skitch, Steven

    2009-11-01

    S. J. Blatt and D. C. Zuroff's 1992 theory of personality predispositions to depression posits that individuals who possess high levels of self-criticism and/or dependency are vulnerable to developing depression following negative events. The current study used experience sampling methodology to test this theory in a sample of 49 children ages 7 to 14. Children completed measures of dependency, self-criticism, and depressive symptoms. Subsequently, children were given a handheld computer that signaled them to complete measures of depressive symptoms and negative events at randomly selected times over 2 months. Results of hierarchical linear modeling analyses indicated that higher levels of both self-criticism and dependency were associated with greater elevations in depressive symptoms following negative events. Furthermore, each personality predisposition remained a significant predictor of such elevations after controlling for the interaction between the other personality predisposition and negative events. The results suggest that dependency and self-criticism represent distinct vulnerability factors to depression in youth.

  15. Transfer Student Success: Educationally Purposeful Activities Predictive of Undergraduate GPA

    ERIC Educational Resources Information Center

    Fauria, Renee M.; Fuller, Matthew B.

    2015-01-01

    Researchers evaluated the effects of Educationally Purposeful Activities (EPAs) on transfer and nontransfer students' cumulative GPAs. Hierarchical, linear, and multiple regression models yielded seven statistically significant educationally purposeful items that influenced undergraduate student GPAs. Statistically significant positive EPAs for…

  16. Practical Assessment, Research & Evaluation, 2000-2001.

    ERIC Educational Resources Information Center

    Rudner, Lawrence M., Ed.; Schafer, William D., Ed.

    2001-01-01

    This document consists of papers published in the electronic journal "Practical Assessment, Research & Evaluation" during 2000-2001: (1) "Advantages of Hierarchical Linear Modeling" (Jason W. Osborne); (2) "Prediction in Multiple Regression" (Jason W. Osborne); (3) Scoring Rubrics: What, When, and How?"…

  17. Algorithm for solving of two-level hierarchical minimax program control problem of final state the regional socio-economic system in the presence of risks

    NASA Astrophysics Data System (ADS)

    Shorikov, A. F.

    2017-10-01

    In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks. For this problem we propose a mathematical model in the form of two-level hierarchical minimax program control problem of the final state of this process with incomplete information. For solving of its problem we constructed the common algorithm that has a form of a recurrent procedure of solving a linear programming and a finite optimization problems.

  18. Unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance

    USGS Publications Warehouse

    Fiske, I.J.; Chandler, R.B.

    2011-01-01

    Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientic questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mecha- nisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unied modeling in- terface. The R package unmarked provides such a unied modeling framework, including tools for data exploration, model tting, model criticism, post-hoc analysis, and model comparison.

  19. Higher Fasting Plasma Glucose Levels, within the Normal Range, are Associated with Decreased Processing Speed in High Functioning Young Elderly.

    PubMed

    Raizes, Meytal; Elkana, Odelia; Franko, Motty; Ravona Springer, Ramit; Segev, Shlomo; Beeri, Michal Schnaider

    2016-01-01

    We explored the association of plasma glucose levels within the normal range with processing speed in high functioning young elderly, free of type 2 diabetes mellitus (T2DM). A sample of 41 participants (mean age = 64.7, SD = 10; glucose 94.5 mg/dL, SD = 9.3), were examined with a computerized cognitive battery. Hierarchical linear regression analysis showed that higher plasma glucose levels, albeit within the normal range (<110 mg/dL), were associated with longer reaction times (p <  0.01). These findings suggest that even in the subclinical range and in the absence of T2DM, monitoring plasma glucose levels may have an impact on cognitive function.

  20. Hope and Burden among Latino Families of Adults with Schizophrenia

    PubMed Central

    HERNANDEZ, MERCEDES; BARRIO, CONCEPCIÓN; YAMADA, ANN-MARIE

    2016-01-01

    This study examined hope and family burden among Latino families of individuals with schizophrenia. The sample consisted of 54 family members, one family member per outpatient adult recruited from public mental health programs in a diverse urban community. Hierarchical linear regression analyses were used to test the hypothesis that the family member’s increased hope for the patient’s future would be associated with decreased family burden beyond effects explained by the patient’s length of illness and severity of symptoms. Results supported the study hypothesis. Family hope for the patient’s future was associated with four of five types of family burden. Findings point to the prominent role of hope as a source of resilience for Latino families dealing with severe mental illness of a loved one. PMID:24329411

  1. Evaluation of initial posttrauma cardiovascular levels in association with acute PTSD symptoms following a serious motor vehicle accident.

    PubMed

    Buckley, Beth; Nugent, Nicole; Sledjeski, Eve; Raimonde, A Jay; Spoonster, Eileen; Bogart, Laura M; Delahanty, Douglas L

    2004-08-01

    The present study examined the relationship between heart rate (HR) and blood pressure (BP) levels assessed at multiple time points posttrauma and subsequent acute posttraumatic stress disorder (PTSD) symptoms present at a 1-month follow-up. HR and BP levels were measured in 65 motor vehicle accident (MVA) survivors during Emergency Medical Service transport, upon admission to the trauma unit, for the first 20 min postadmission and on the day of discharge. Hierarchical linear modeling analyses revealed no significant relationships between cardiovascular levels and acute PTSD symptoms. Given the small sample size, these results should be interpreted with caution. However, the present results question the use of initial cardiovascular levels as predictors of subsequent acute PTSD in seriously injured MVA victims.

  2. Making a Difference in Science Education: The Impact of Undergraduate Research Programs

    PubMed Central

    Eagan, M. Kevin; Hurtado, Sylvia; Chang, Mitchell J.; Garcia, Gina A.; Herrera, Felisha A.; Garibay, Juan C.

    2014-01-01

    To increase the numbers of underrepresented racial minority students in science, technology, engineering, and mathematics (STEM), federal and private agencies have allocated significant funding to undergraduate research programs, which have been shown to students’ intentions of enrolling in graduate or professional school. Analyzing a longitudinal sample of 4,152 aspiring STEM majors who completed the 2004 Freshman Survey and 2008 College Senior Survey, this study utilizes multinomial hierarchical generalized linear modeling (HGLM) and propensity score matching techniques to examine how participation in undergraduate research affects STEM students’ intentions to enroll in STEM and non-STEM graduate and professional programs. Findings indicate that participation in an undergraduate research program significantly improved students’ probability of indicating plans to enroll in a STEM graduate program. PMID:25190821

  3. Adolescent Attachment Trajectories with Mothers and Fathers: The Importance of Parent-Child Relationship Experiences and Gender

    PubMed Central

    Ruhl, Holly; Dolan, Elaine A.; Buhrmester, Duane

    2014-01-01

    This longitudinal study investigated how attachment with mothers and fathers changes during adolescence, and how gender and parent-child relationship experiences are associated with attachment trajectories. The relative importance of specific positive and negative relationship experiences on attachment trajectories was also examined. An initial sample of 223 adolescents reported on relationship experiences and attachment avoidance and anxiety with mothers and fathers in grades 6, 8, 10, and 12 (final N=110; Mage=11.90 years at onset, SD=.43). Mothers and fathers reported on relationship experiences with adolescents. Hierarchical linear modeling showed that security with parents increased during adolescence. Positive relationship experiences (companionship, satisfaction, approval, support) predicted increases in security and negative experiences (pressure, criticism) predicted decreases in security. Females reported less avoidance than males. PMID:26347590

  4. Action Civics for Promoting Civic Development: Main Effects of Program Participation and Differences by Project Characteristics

    PubMed Central

    Cohen, Alison K.; Littenberg-Tobias, Joshua

    2017-01-01

    Using both quantitative and qualitative data, this study examined the effect of participating in an action civics intervention, Generation Citizen (GC), on civic commitment, civic self-efficacy, and two forms of civic knowledge. The sample consisted of 617 middle and high schools students in 55 classrooms who participated, or were soon to participate, in Generation Citizen. Hierarchical linear models revealed that participating in Generation Citizen was associated with positive gains in action civics knowledge and civic self-efficacy. Qualitative coding identified three types of project characteristics that captured variability in the action projects student chose to complete: context, content, and contact with decision makers. Interactions between project characteristics and participation in GC revealed differences in civic outcomes depending on project characteristics. PMID:27982470

  5. Two-Year Predictors of Runaway and Homeless Episodes Following Shelter Services among Substance Abusing Adolescents

    PubMed Central

    Slesnick, Natasha; Guo, Xiamei; Brakenhoff, Brittany; Feng, Xin

    2013-01-01

    Given high levels of health and psychological costs associated with the family disruption of homelessness, identifying predictors of runaway and homeless episodes is an important goal. The current study followed 179 substance abusing, shelter-recruited adolescents who participated in a randomized clinical trial. Predictors of runaway and homeless episodes were examined over a two year period. Results from the hierarchical linear modeling analysis showed that family cohesion and substance use, but not family conflict or depressive symptoms, delinquency, or school enrollment predicted future runaway and homeless episodes. Findings suggest that increasing family support, care and connection and reducing substance use are important targets of intervention efforts in preventing future runaway and homeless episodes amongst a high risk sample of adolescents. PMID:24011094

  6. Perceived overqualification and its outcomes: the moderating role of empowerment.

    PubMed

    Erdogan, Berrin; Bauer, Talya N

    2009-03-01

    Research shows that perceived overqualification is related to lower job attitudes and greater withdrawal behaviors but to higher supervisor ratings of performance. Drawing upon relative deprivation theory, the authors proposed and tested empowerment as a moderator of the relationship between perceived overqualification and job satisfaction, intentions to remain, voluntary turnover, and objective sales performance to examine if negative outcomes could be lessened while stimulating even higher performance. Hierarchical linear modeling results from a sample of 244 sales associates working in 25 stores of a Turkish retail chain show that empowerment ameliorated the negative effects of perceived overqualification on job satisfaction, intentions to remain, and voluntary turnover. Empowerment did not affect the positive relationship between perceived overqualification and objective sales performance. (c) 2009 APA, all rights reserved.

  7. Pathways for learning two languages: lexical and grammatical associations within and across languages in sequential bilingual children*

    PubMed Central

    PHAM, GIANG

    2018-01-01

    This study examines the strength and direction of lexical-grammatical associations within and between first and second languages (L1 and L2) in a longitudinal sample of sequential bilinguals. Thirty-three children who spoke Vietnamese (L1) and English (L2) completed picture-naming and story-telling tasks in each language at four yearly intervals. Hierarchical linear modeling across Years 1–4 revealed bidirectional within-language associations and a unidirectional cross-language association from the L1 to L2. Results suggest a conditional relationship between languages in which the L1 supports L2 growth, but not vice versa. Findings contribute to defining pathways for L1 and L2 learning across domains and languages. PMID:29670455

  8. Flow experience in the daily lives of older adults: an analysis of the interaction between flow, individual differences, serious leisure, location, and social context.

    PubMed

    Heo, Jinmoo; Lee, Youngkhill; Pedersen, Paul M; McCormick, Bryan P

    2010-09-01

    This study examined how serious leisure, individual differences, social context, and location contribute to older adults' experiences of flow - an intense psychological state - in their daily lives. The Experience Sampling Method was used with 19 older adults in a Midwestern city in the United States. Experience of flow was the outcome measure, and the data were analyzed using hierarchical linear modeling. Results indicated that location and employment status influenced the subjects' flow experience. Furthermore, the findings revealed that retirement was negatively related to experiencing flow, and there was a significant association between home and the flow experience. The results of this study enhance the understanding of flow experiences in the everyday lives of older adults.

  9. The Negative Effects of Public Benefits on Individual Employment: A Multilevel Analysis of Work Hours.

    PubMed

    Nord, Derek; Nye-Lengerman, Kelly

    2015-08-01

    Public benefits are widely used by people with intellectual and development disabilities (IDD) as crucial financial supports. Using Rehabilitation Service Administration 911 and Annual Review Report datasets to account for individual and state vocational rehabilitation (VR) agency variables, a sample of 21,869 people with IDD were analyzed using hierarchical linear modeling to model the effects of public benefits on hours worked per week. Findings point to associations that indicate that public benefits not only limit access to employment participation, they also have a restricting effect on growth of weekly hours that typically come with higher wage positions, compared those that do not access benefits. The article also lays out important implications and recommendations to increase the inclusion of people with IDD in the workplace.

  10. Growth trajectories of mathematics achievement: Longitudinal tracking of student academic progress.

    PubMed

    Mok, Magdalena M C; McInerney, Dennis M; Zhu, Jinxin; Or, Anthony

    2015-06-01

    A number of methods to investigate growth have been reported in the literature, including hierarchical linear modelling (HLM), latent growth modelling (LGM), and multidimensional scaling applied to longitudinal profile analysis (LPAMS). This study aimed at modelling the mathematics growth of students over a span of 6 years from Grade 3 to Grade 9. The sample comprised secondary longitudinal data collected in three waves from n = 866 Hong Kong students when they were in Grade 3, Grade 6, and Grade 9. Mathematics achievement was measured thrice on a vertical scale linked with anchor items. Linear and nonlinear latent growth models were used to assess students' growth. Gender differences were also examined. A nonlinear latent growth curve with a decelerated rate had a good fit to the data. Initial achievement and growth rate were negatively correlated. No gender difference was found. Mathematics growth from Grade 6 to Grade 9 was slower than that from Grade 3 to Grade 6. Students with lower initial achievement improved at a faster rate than those who started at a higher level. Gender did not affect growth rate. © 2014 The British Psychological Society.

  11. The relationship between spiritual well-being and health-related quality of life in college students.

    PubMed

    Anye, Ernest Tamanji; Gallien, Tara L; Bian, Hui; Moulton, Michael

    2013-01-01

    This study investigated the relationship between spiritual well-being (SWB) and various aspects of health-related quality of life (HRQL) of college students. Two hundred twenty-five participants were surveyed during October 2010 to assess SWB and HRQL using the Spiritual Well-Being Scale and questions from the Centers for Disease Control and Prevention's scale for HRQL, respectively. Hierarchical multiple linear regression analyses tested the relationship between SWB and multiple measures of HRQL while controlling for sex, age, and race. Participants who reported higher SWB scores were more likely to participate in religious-type activities and report better HRQL compared with students who reported a moderate sense of SWB. Jointly, SWB and participation in religious activities explained 18% of the variance in HQRL in this sample. SWB made a significant contribution to HRQL in a sample of college students. Such a relationship should be considered by campus health program planners to improve the quality of life of young adults.

  12. A Method for Label-Free, Differential Top-Down Proteomics.

    PubMed

    Ntai, Ioanna; Toby, Timothy K; LeDuc, Richard D; Kelleher, Neil L

    2016-01-01

    Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

  13. Influences of neighborhood context, individual history and parenting behavior on recidivism among juvenile offenders.

    PubMed

    Grunwald, Heidi E; Lockwood, Brian; Harris, Philip W; Mennis, Jeremy

    2010-09-01

    This study examined the effects of neighborhood context on juvenile recidivism to determine if neighborhoods influence the likelihood of reoffending. Although a large body of literature exists regarding the impact of environmental factors on delinquency, very little is known about the effects of these factors on juvenile recidivism. The sample analyzed includes 7,061 delinquent male juveniles committed to community-based programs in Philadelphia, of which 74% are Black, 13% Hispanic, and 11% White. Since sample youths were nested in neighborhoods, a hierarchical generalized linear model was employed to predict recidivism across three general categories of recidivism offenses: drug, violent, and property. Results indicate that predictors vary across the types of offenses and that drug offending differs from property and violent offending. Neighborhood-level factors were found to influence drug offense recidivism, but were not significant predictors of violent offenses, property offenses, or an aggregated recidivism measure, despite contrary expectations. Implications stemming from the finding that neighborhood context influences only juvenile drug recidivism are discussed.

  14. Characterization and Differentiation of Petroleum-Derived Products by E-Nose Fingerprints

    PubMed Central

    Ferreiro-González, Marta; Palma, Miguel; Ayuso, Jesús; Álvarez, José A.; Barroso, Carmelo G.

    2017-01-01

    Characterization of petroleum-derived products is an area of continuing importance in environmental science, mainly related to fuel spills. In this study, a non-separative analytical method based on E-Nose (Electronic Nose) is presented as a rapid alternative for the characterization of several different petroleum-derived products including gasoline, diesel, aromatic solvents, and ethanol samples, which were poured onto different surfaces (wood, cork, and cotton). The working conditions about the headspace generation were 145 °C and 10 min. Mass spectroscopic data (45–200 m/z) combined with chemometric tools such as hierarchical cluster analysis (HCA), later principal component analysis (PCA), and finally linear discriminant analysis (LDA) allowed for a full discrimination of the samples. A characteristic fingerprint for each product can be used for discrimination or identification. The E-Nose can be considered as a green technique, and it is rapid and easy to use in routine analysis, thus providing a good alternative to currently used methods. PMID:29113069

  15. An open-population hierarchical distance sampling model

    USGS Publications Warehouse

    Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,

    2015-01-01

    Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

  16. An open-population hierarchical distance sampling model.

    PubMed

    Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott

    2015-02-01

    Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.

  17. Unsupervised active learning based on hierarchical graph-theoretic clustering.

    PubMed

    Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

    2009-10-01

    Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

  18. An adaptive sampling method for variable-fidelity surrogate models using improved hierarchical kriging

    NASA Astrophysics Data System (ADS)

    Hu, Jiexiang; Zhou, Qi; Jiang, Ping; Shao, Xinyu; Xie, Tingli

    2018-01-01

    Variable-fidelity (VF) modelling methods have been widely used in complex engineering system design to mitigate the computational burden. Building a VF model generally includes two parts: design of experiments and metamodel construction. In this article, an adaptive sampling method based on improved hierarchical kriging (ASM-IHK) is proposed to refine the improved VF model. First, an improved hierarchical kriging model is developed as the metamodel, in which the low-fidelity model is varied through a polynomial response surface function to capture the characteristics of a high-fidelity model. Secondly, to reduce local approximation errors, an active learning strategy based on a sequential sampling method is introduced to make full use of the already required information on the current sampling points and to guide the sampling process of the high-fidelity model. Finally, two numerical examples and the modelling of the aerodynamic coefficient for an aircraft are provided to demonstrate the approximation capability of the proposed approach, as well as three other metamodelling methods and two sequential sampling methods. The results show that ASM-IHK provides a more accurate metamodel at the same simulation cost, which is very important in metamodel-based engineering design problems.

  19. Hierarchical Boltzmann simulations and model error estimation

    NASA Astrophysics Data System (ADS)

    Torrilhon, Manuel; Sarna, Neeraj

    2017-08-01

    A hierarchical simulation approach for Boltzmann's equation should provide a single numerical framework in which a coarse representation can be used to compute gas flows as accurately and efficiently as in computational fluid dynamics, but a subsequent refinement allows to successively improve the result to the complete Boltzmann result. We use Hermite discretization, or moment equations, for the steady linearized Boltzmann equation for a proof-of-concept of such a framework. All representations of the hierarchy are rotationally invariant and the numerical method is formulated on fully unstructured triangular and quadrilateral meshes using a implicit discontinuous Galerkin formulation. We demonstrate the performance of the numerical method on model problems which in particular highlights the relevance of stability of boundary conditions on curved domains. The hierarchical nature of the method allows also to provide model error estimates by comparing subsequent representations. We present various model errors for a flow through a curved channel with obstacles.

  20. Real-Time Detector of Human Fatigue: Detecting Lapses in Alertness

    DTIC Science & Technology

    2008-02-15

    These coefficients and their variances, covariances and standard errors were computed simultaneously using HLM 6 (Raudenbush, Bryk, Cheong, & Congdon ...CA: Sage. Raudenbush, S. W., Bryk, A. S., Cheong, Y. F., & Congdon , R. T. (2004). HLM6: Hierarchical Linear and Nonlinear Modeling [Computer software

  1. Bonding Social Capital in Low-Income Neighborhoods

    ERIC Educational Resources Information Center

    Brisson, Daniel S.; Usher, Charles L.

    2005-01-01

    Social capital has recently become a guiding theoretical framework for family interventions in low-income neighborhoods. In the context of the Annie E. Casey Foundation's Making Connections initiative, this research uses hierarchical linear modeling to examine how neighborhood characteristics and resident participation affect bonding social…

  2. Indigenous Intelligence: Have We Lost Our Indigenous Mind?

    ERIC Educational Resources Information Center

    Dumont, Jim

    2002-01-01

    Eurocentric intelligence is restricted to rational, linear, competitive, and hierarchical thinking. Indigenous intelligence encompasses the body, mind, heart, and experience in total responsiveness and total relationship to the whole environment, which includes the seven generations past and future. Implementation of major changes to indigenous…

  3. The Relationship between Counselors' Multicultural Counseling Competence and Poverty Beliefs

    ERIC Educational Resources Information Center

    Clark, Madeline; Moe, Jeff; Hays, Danica G.

    2017-01-01

    The authors explored the relationship between counselors' multicultural counseling competence (MCC), poverty beliefs, and select demographic factors. Results of hierarchical linear regressions indicate that MCC is predictive of counselor individualistic and structural poverty beliefs. Implications for counselor multicultural training and immersion…

  4. Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types.

    PubMed

    van Unen, Vincent; Höllt, Thomas; Pezzotti, Nicola; Li, Na; Reinders, Marcel J T; Eisemann, Elmar; Koning, Frits; Vilanova, Anna; Lelieveldt, Boudewijn P F

    2017-11-23

    Mass cytometry allows high-resolution dissection of the cellular composition of the immune system. However, the high-dimensionality, large size, and non-linear structure of the data poses considerable challenges for the data analysis. In particular, dimensionality reduction-based techniques like t-SNE offer single-cell resolution but are limited in the number of cells that can be analyzed. Here we introduce Hierarchical Stochastic Neighbor Embedding (HSNE) for the analysis of mass cytometry data sets. HSNE constructs a hierarchy of non-linear similarities that can be interactively explored with a stepwise increase in detail up to the single-cell level. We apply HSNE to a study on gastrointestinal disorders and three other available mass cytometry data sets. We find that HSNE efficiently replicates previous observations and identifies rare cell populations that were previously missed due to downsampling. Thus, HSNE removes the scalability limit of conventional t-SNE analysis, a feature that makes it highly suitable for the analysis of massive high-dimensional data sets.

  5. The effect of maternal psychopathology on parent-child agreement of child anxiety symptoms: A hierarchical linear modeling approach.

    PubMed

    Affrunti, Nicholas W; Woodruff-Borden, Janet

    2015-05-01

    The current study examined the effects of maternal anxiety, worry, depression, child age and gender on mother and child reports of child anxiety using hierarchical linear modeling. Participants were 73 mother-child dyads with children between the ages of 7 and 10 years. Reports of child anxiety symptoms, including symptoms of specific disorders (e.g., social phobia) were obtained using concordant versions of the Screen for Anxiety and Related Emotional Disorders (SCARED). Children reported significantly higher levels of anxiety symptoms relative to their mothers. Maternal worry and depression predicted for significantly lower levels of maternal-reported child anxiety and increasing discrepant reports. Maternal anxiety predicted for higher levels of maternal-reported child anxiety and decreasing discrepant reports. Maternal depression was associated with increased child-reported child anxiety symptoms. No significant effect of child age or gender was observed. Findings may inform inconsistencies in previous studies on reporter discrepancies. Implications and future directions are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  6. Assessing exposure to violence using multiple informants: application of hierarchical linear model.

    PubMed

    Kuo, M; Mohler, B; Raudenbush, S L; Earls, F J

    2000-11-01

    The present study assesses the effects of demographic risk factors on children's exposure to violence (ETV) and how these effects vary by informants. Data on exposure to violence of 9-, 12-, and 15-year-olds were collected from both child participants (N = 1880) and parents (N = 1776), as part of the assessment of the Project on Human Development in Chicago Neighborhoods (PHDCN). A two-level hierarchical linear model (HLM) with multivariate outcomes was employed to analyze information obtained from these two different groups of informants. The findings indicate that parents generally report less ETV than do their children and that associations of age, gender, and parent education with ETV are stronger in the self-reports than in the parent reports. The findings support a multivariate approach when information obtained from different sources is being integrated. The application of HLM allows an assessment of interactions between risk factors and informants and uses all available data, including data from one informant when data from the other informant is missing.

  7. Delineating the joint hierarchical structure of clinical and personality disorders in an outpatient psychiatric sample.

    PubMed

    Forbes, Miriam K; Kotov, Roman; Ruggero, Camilo J; Watson, David; Zimmerman, Mark; Krueger, Robert F

    2017-11-01

    A large body of research has focused on identifying the optimal number of dimensions - or spectra - to model individual differences in psychopathology. Recently, it has become increasingly clear that ostensibly competing models with varying numbers of spectra can be synthesized in empirically derived hierarchical structures. We examined the convergence between top-down (bass-ackwards or sequential principal components analysis) and bottom-up (hierarchical agglomerative cluster analysis) statistical methods for elucidating hierarchies to explicate the joint hierarchical structure of clinical and personality disorders. Analyses examined 24 clinical and personality disorders based on semi-structured clinical interviews in an outpatient psychiatric sample (n=2900). The two methods of hierarchical analysis converged on a three-tier joint hierarchy of psychopathology. At the lowest tier, there were seven spectra - disinhibition, antagonism, core thought disorder, detachment, core internalizing, somatoform, and compulsivity - that emerged in both methods. These spectra were nested under the same three higher-order superspectra in both methods: externalizing, broad thought dysfunction, and broad internalizing. In turn, these three superspectra were nested under a single general psychopathology spectrum, which represented the top tier of the hierarchical structure. The hierarchical structure mirrors and extends upon past research, with the inclusion of a novel compulsivity spectrum, and the finding that psychopathology is organized in three superordinate domains. This hierarchy can thus be used as a flexible and integrative framework to facilitate psychopathology research with varying levels of specificity (i.e., focusing on the optimal level of detailed information, rather than the optimal number of factors). Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Advances in statistics

    Treesearch

    Howard Stauffer; Nadav Nur

    2005-01-01

    The papers included in the Advances in Statistics section of the Partners in Flight (PIF) 2002 Proceedings represent a small sample of statistical topics of current importance to Partners In Flight research scientists: hierarchical modeling, estimation of detection probabilities, and Bayesian applications. Sauer et al. (this volume) examines a hierarchical model...

  9. Zinc oxide hierarchical nanostructures for photocatalysis

    NASA Astrophysics Data System (ADS)

    Yukhnovets, O.; Semenova, A. A.; Levkevich, E. A.; Maximov, A. I.; Moshnikov, V. A.

    2018-03-01

    In this work, we perform the study of zinc oxide hierarchical structures synthesized by the low-temperature hydrothermal method. The paper considers morphological properties of obtained structures. Photocatalytic activity of samples was analysed by methyl orange degradation under UV irradiation. The sufficient decrease in methyl orange has been demonstrated.

  10. Quality evaluation of Houttuynia cordata Thunb. by high performance liquid chromatography with photodiode-array detection (HPLC-DAD).

    PubMed

    Yang, Zhan-nan; Sun, Yi-ming; Luo, Shi-qiong; Chen, Jin-wu; Chen, Jin-wu; Yu, Zheng-wen; Sun, Min

    2014-03-01

    A new, validated method, developed for the simultaneous determination of 16 phenolics (chlorogenic acid, scopoletin, vitexin, rutin, afzelin, isoquercitrin, narirutin, kaempferitrin, quercitrin, quercetin, kaempferol, chrysosplenol D, vitexicarpin, 5-hydroxy-3,3',4',7-tetramethoxy flavonoids, 5-hydroxy-3,4',6,7-tetramethoxy flavonoids and kaempferol-3,7,4'-trimethyl ether) in Houttuynia cordata Thunb. was successfully applied to 35 batches of samples collected from different regions or at different times and their total antioxidant activities (TAAs) were investigated. The aim was to develop a quality control method to simultaneously determine the major active components in H. cordata. The HPLC-DAD method was performed using a reverse-phase C18 column with a gradient elution system (acetonitrile-methanol-water) and simultaneous detection at 345 nm. Linear behaviors of method for all the analytes were observed with linear regression relationship (r(2)>0.999) at the concentration ranges investigated. The recoveries of the 16 phenolics ranged from 98.93% to 101.26%. The samples analyzed were differentiated and classified based on the contents of the 16 characteristic compounds and the TAA using hierarchical clustering analysis (HCA) and principal component analysis (PCA). The results analyzed showed that similar chemical profiles and TAAs were divided into the same group. There was some evidence that active compounds, although they varied significantly, may possess uniform anti-oxidant activities and have potentially synergistic effects.

  11. Simultaneous analysis of 11 main active components in Cirsium setosum based on HPLC-ESI-MS/MS and combined with statistical methods.

    PubMed

    Sun, Qian; Chang, Lu; Ren, Yanping; Cao, Liang; Sun, Yingguang; Du, Yingfeng; Shi, Xiaowei; Wang, Qiao; Zhang, Lantong

    2012-11-01

    A novel method based on high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry was developed for simultaneous determination of the 11 major active components including ten flavonoids and one phenolic acid in Cirsium setosum. Separation was performed on a reversed-phase C(18) column with gradient elution of methanol and 0.1‰ acetic acid (v/v). The identification and quantification of the analytes were achieved on a hybrid quadrupole linear ion trap mass spectrometer. Multiple-reaction monitoring scanning was employed for quantification with switching electrospray ion source polarity between positive and negative modes in a single run. Full validation of the assay was carried out including linearity, precision, accuracy, stability, limits of detection and quantification. The results demonstrated that the method developed was reliable, rapid, and specific. The 25 batches of C. setosum samples from different sources were first determined using the developed method and the total contents of 11 analytes ranged from 1717.460 to 23028.258 μg/g. Among them, the content of linarin was highest, and its mean value was 7340.967 μg/g. Principal component analysis and hierarchical clustering analysis were performed to differentiate and classify the samples, which is helpful for comprehensive evaluation of the quality of C. setosum. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Ultrametric properties of the attractor spaces for random iterated linear function systems

    NASA Astrophysics Data System (ADS)

    Buchovets, A. G.; Moskalev, P. V.

    2018-03-01

    We investigate attractors of random iterated linear function systems as independent spaces embedded in the ordinary Euclidean space. The introduction on the set of attractor points of a metric that satisfies the strengthened triangle inequality makes this space ultrametric. Then inherent in ultrametric spaces the properties of disconnectedness and hierarchical self-similarity make it possible to define an attractor as a fractal. We note that a rigorous proof of these properties in the case of an ordinary Euclidean space is very difficult.

  13. Notes sur les mouvements recursifs (Notes on Regressive Moves).

    ERIC Educational Resources Information Center

    Auchlin, Antoine; And Others

    1981-01-01

    Examines the phenomenon of regressive moves (retro-interpretation) in the light of a hypothesis according to which the formation of complex and hierarchically organized conversation units is subordinated to the linearity of discourse. Analyzes a transactional exchange, describing the interplay of integration, anticipation, and retro-interpretation…

  14. The Hierarchical Personality Structure of Aspiring Creative Writers

    ERIC Educational Resources Information Center

    Maslej, Marta M.; Rain, Marina; Fong, Katrina; Oatley, Keith; Mar, Raymond A.

    2014-01-01

    Empirical studies of personality traits in creative writers have demonstrated mixed findings, perhaps due to issues of sampling, measurement, and the reporting of statistical information. The goal of this study is to quantify the personality structure of aspiring creative writers according to a modern hierarchal model of trait personality. A…

  15. A new family of fluidic precursors for the self-templated synthesis of hierarchical nanoporous carbons

    DOE PAGES

    Fulvio, Pasquale F.; Hillesheim, Patrick C.; Oyola, Yatsandra; ...

    2016-06-24

    Hierarchical nanoporous nitrogen-doped carbons were prepared from task specific ionic liquids having a bis-imidazolium motif linked with various organic groups. While ethyl chains linking the imidazolium ions afford microporous-mesoporous carbons, long or aromatic groups resulted in microporous samples.

  16. Testing Crites' Model of Career Maturity: A Hierarchical Strategy.

    ERIC Educational Resources Information Center

    Wallbrown, Fred H.; And Others

    1986-01-01

    Investigated the construct validity of Crites' model of career maturity and the Career Maturity Inventory (CMI). Results from a nationwide sample of adolescents, using hierarchical factor analytic methodology, indicated confirmatory support for the multidimensionality of Crites' model of career maturity, and the construct validity of the CMI as a…

  17. Hierarchical Bayesian modelling of mobility metrics for hazard model input calibration

    NASA Astrophysics Data System (ADS)

    Calder, Eliza; Ogburn, Sarah; Spiller, Elaine; Rutarindwa, Regis; Berger, Jim

    2015-04-01

    In this work we present a method to constrain flow mobility input parameters for pyroclastic flow models using hierarchical Bayes modeling of standard mobility metrics such as H/L and flow volume etc. The advantage of hierarchical modeling is that it can leverage the information in global dataset for a particular mobility metric in order to reduce the uncertainty in modeling of an individual volcano, especially important where individual volcanoes have only sparse datasets. We use compiled pyroclastic flow runout data from Colima, Merapi, Soufriere Hills, Unzen and Semeru volcanoes, presented in an open-source database FlowDat (https://vhub.org/groups/massflowdatabase). While the exact relationship between flow volume and friction varies somewhat between volcanoes, dome collapse flows originating from the same volcano exhibit similar mobility relationships. Instead of fitting separate regression models for each volcano dataset, we use a variation of the hierarchical linear model (Kass and Steffey, 1989). The model presents a hierarchical structure with two levels; all dome collapse flows and dome collapse flows at specific volcanoes. The hierarchical model allows us to assume that the flows at specific volcanoes share a common distribution of regression slopes, then solves for that distribution. We present comparisons of the 95% confidence intervals on the individual regression lines for the data set from each volcano as well as those obtained from the hierarchical model. The results clearly demonstrate the advantage of considering global datasets using this technique. The technique developed is demonstrated here for mobility metrics, but can be applied to many other global datasets of volcanic parameters. In particular, such methods can provide a means to better contain parameters for volcanoes for which we only have sparse data, a ubiquitous problem in volcanology.

  18. The effects of guided inquiry instruction on student achievement in high school biology

    NASA Astrophysics Data System (ADS)

    Vass, Laszlo

    The purpose of this quantitative, quasi-experimental study was to measure the effect of a student-centered instructional method called guided inquiry on the achievement of students in a unit of study in high school biology. The study used a non-random sample of 109 students, the control group of 55 students enrolled in high school one, received teacher centered instruction while the experimental group of 54 students enrolled at high school two received student-centered, guided inquiry instruction. The pretest-posttest design of the study analyzed scores using an independent t-test, a dependent t-test (p = <.001), an ANCOVA (p = .007), mixed method ANOVA (p = .024) and hierarchical linear regression (p = <.001). The experimental group that received guided inquiry instruction had statistically significantly higher achievement than the control group.

  19. [Job Demands-Resources, exhaustion and work engagement in a long-term care institution].

    PubMed

    Conway, P M; Neri, L; Campanini, P; Francioli, L; Camerino, D; Punzi, S; Fichera, G P; Costa, G

    2012-01-01

    In this study, we aimed at testing the main hypotheses of the Job Demands-Resources model (JD-R) in a sample of employees (n = 205, mainly healthcare workers) of a long-term care institution located in Northern Italy. Hierarchical linear regression analyses show that almost all job demands considered were significantly associated with higher general psycho-physical exhaustion (beta ranging from 0.14 to 0.29), whereas more unfavourable scores in all job resources were associated with lower work engagement (from -0.27 to -0.51). However, also significant cross-over associations were observed, mainly between job resources and exhaustion, with effect sizes comparable with those found for the relationships between job demands and exhaustion. Hence, our study only partially supports the JD-R model. Implications of results for work-related stress management are finally discussed.

  20. Expanding the psychosocial work environment: workplace norms and work-family conflict as correlates of stress and health.

    PubMed

    Hammer, Tove Helland; Saksvik, Per Øystein; Nytrø, Kjell; Torvatn, Hans; Bayazit, Mahmut

    2004-01-01

    This study examined the contributions of organizational level norms about work requirements and social relations, and work-family conflict, to job stress and subjective health symptoms, controlling for Karasek's job demand-control-support model of the psychosocial work environment, in a sample of 1,346 employees from 56 firms in the Norwegian food and beverage industry. Hierarchical linear modeling analyses showed that organizational norms governing work performance and social relations, and work-to-family and family-to-work conflict, explained significant amounts of variance for job stress. The cross-level interaction between work performance norms and work-to-family conflict was also significantly related to job stress. Work-to-family conflict was significantly related to health symptoms, but family-to-work conflict and organizational norms were not.

  1. Schools, parents, and youth violence: a multilevel, ecological analysis.

    PubMed

    Brookmeyer, Kathryn A; Fanti, Kostas A; Henrich, Christopher C

    2006-12-01

    Using data from the National Longitudinal Study of Adolescent Health (Add Health), this study utilized an ecological approach to investigate the joint contribution of parents and schools on changes in violent behavior over time among a sample of 6,397 students (54% female) from 125 schools. This study examined the main and interactive effects of parent and school connectedness as buffers of violent behavior within a hierarchical linear model, focusing on both students and schools as the unit of analysis. Results show that students who feel more connected to their schools demonstrate reductions in violent behavior over time. On the school level, our findings suggest that school climate serves as a protective factor for student violent behavior. Finally, parent and school connectedness appear to work together to buffer adolescents from the effects of violence exposure on subsequent violent behavior.

  2. Hierarchical structure of the energy landscape of proteins revisited by time series analysis. I. Mimicking protein dynamics in different time scales

    NASA Astrophysics Data System (ADS)

    Alakent, Burak; Camurdan, Mehmet C.; Doruker, Pemra

    2005-10-01

    Time series models, which are constructed from the projections of the molecular-dynamics (MD) runs on principal components (modes), are used to mimic the dynamics of two proteins: tendamistat and immunity protein of colicin E7 (ImmE7). Four independent MD runs of tendamistat and three independent runs of ImmE7 protein in vacuum are used to investigate the energy landscapes of these proteins. It is found that mean-square displacements of residues along the modes in different time scales can be mimicked by time series models, which are utilized in dividing protein dynamics into different regimes with respect to the dominating motion type. The first two regimes constitute the dominance of intraminimum motions during the first 5ps and the random walk motion in a hierarchically higher-level energy minimum, which comprise the initial time period of the trajectories up to 20-40ps for tendamistat and 80-120ps for ImmE7. These are also the time ranges within which the linear nonstationary time series are completely satisfactory in explaining protein dynamics. Encountering energy barriers enclosing higher-level energy minima constrains the random walk motion of the proteins, and pseudorelaxation processes at different levels of minima are detected in tendamistat, depending on the sampling window size. Correlation (relaxation) times of 30-40ps and 150-200ps are detected for two energy envelopes of successive levels for tendamistat, which gives an overall idea about the hierarchical structure of the energy landscape. However, it should be stressed that correlation times of the modes are highly variable with respect to conformational subspaces and sampling window sizes, indicating the absence of an actual relaxation. The random-walk step sizes and the time length of the second regime are used to illuminate an important difference between the dynamics of the two proteins, which cannot be clarified by the investigation of relaxation times alone: ImmE7 has lower-energy barriers enclosing the higher-level energy minimum, preventing the protein to relax and letting it move in a random-walk fashion for a longer period of time.

  3. Four- and five-factor models of the WAIS-IV in a clinical sample: Variations in indicator configuration and factor correlational structure.

    PubMed

    Staffaroni, Adam M; Eng, Megan E; Moses, James A; Zeiner, Harriet Katz; Wickham, Robert E

    2018-05-01

    A growing body of research supports the validity of 5-factor models for interpreting the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV). The majority of these studies have utilized the WAIS-IV normative or clinical sample, the latter of which differs in its diagnostic composition from the referrals seen at outpatient neuropsychology clinics. To address this concern, 2 related studies were conducted on a sample of 322 American military Veterans who were referred for outpatient neuropsychological assessment. In Study 1, 4 hierarchical models with varying indicator configurations were evaluated: 3 extant 5-factor models from the literature and the traditional 4-factor model. In Study 2, we evaluated 3 variations in correlation structure in the models from Study 1: indirect hierarchical (i.e., higher-order g), bifactor (direct hierarchical), and oblique models. The results from Study 1 suggested that both 4- and 5-factor models showed acceptable fit. The results from Study 2 showed that bifactor and oblique models offer improved fit over the typically specified indirect hierarchical model, and the oblique models outperformed the orthogonal bifactor models. An exploratory analysis found improved fit when bifactor models were specified with oblique rather than orthogonal latent factors. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  4. Studies on the formation of hierarchical zeolite T aggregates with well-defined morphology in different template systems

    NASA Astrophysics Data System (ADS)

    Yin, Xiaoyan; Chu, Naibo; Lu, Xuewei; Li, Zhongfang; Guo, Hong

    2016-01-01

    In this paper, the disk-like and pumpkin-like hierarchical zeolite T aggregates consisted of primary nano-grains have been hydrothermally synthesized with and without the aid of the second template. The first template is used with tetramethylammonium hydroxide (TMAOH) and the second template is used with triethanolamine (TEA) or polyving akohol (PVA). A combination of characterization techniques, including XRD, SEM, TEM and N2 adsorption-desorption to examine the crystal crystallinity, morphology and surface properties of hierarchical zeolite T aggregates. In the single-template preparation process, the two-step varying-temperature treatment has been used to improve the meso-porosity of zeolite T aggregates. In the double-template preparation process, the amounts of PVA or TEA on the crystallinity, morphology and meso-porosity of zeolite T aggregates have been studied. It has been proved that the interstitial voids between the primary grains of aggregates are the origin of additional mesopores of samples. The micro- and meso-porosities of samples prepared with and without the second template have been contrasted in detail at last. In particular, the sample synthesized with the addition of PVA presents a hierarchical pore structure with the highest Sext value of 122 m2/g and Vmeso value of 0.255 cm3/g.

  5. Hierarchical Dirichlet process model for gene expression clustering

    PubMed Central

    2013-01-01

    Clustering is an important data processing tool for interpreting microarray data and genomic network inference. In this article, we propose a clustering algorithm based on the hierarchical Dirichlet processes (HDP). The HDP clustering introduces a hierarchical structure in the statistical model which captures the hierarchical features prevalent in biological data such as the gene express data. We develop a Gibbs sampling algorithm based on the Chinese restaurant metaphor for the HDP clustering. We apply the proposed HDP algorithm to both regulatory network segmentation and gene expression clustering. The HDP algorithm is shown to outperform several popular clustering algorithms by revealing the underlying hierarchical structure of the data. For the yeast cell cycle data, we compare the HDP result to the standard result and show that the HDP algorithm provides more information and reduces the unnecessary clustering fragments. PMID:23587447

  6. Remarks on Hierarchic Control for a Linearized Micropolar Fluids System in Moving Domains

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

    Jesus, Isaías Pereira de, E-mail: isaias@ufpi.edu.br

    We study a Stackelberg strategy subject to the evolutionary linearized micropolar fluids equations in domains with moving boundaries, considering a Nash multi-objective equilibrium (non necessarily cooperative) for the “follower players” (as is called in the economy field) and an optimal problem for the leader player with approximate controllability objective. We will obtain the following main results: the existence and uniqueness of Nash equilibrium and its characterization, the approximate controllability of the linearized micropolar system with respect to the leader control and the existence and uniqueness of the Stackelberg–Nash problem, where the optimality system for the leader is given.

  7. Comparing hierarchical models via the marginalized deviance information criterion.

    PubMed

    Quintero, Adrian; Lesaffre, Emmanuel

    2018-07-20

    Hierarchical models are extensively used in pharmacokinetics and longitudinal studies. When the estimation is performed from a Bayesian approach, model comparison is often based on the deviance information criterion (DIC). In hierarchical models with latent variables, there are several versions of this statistic: the conditional DIC (cDIC) that incorporates the latent variables in the focus of the analysis and the marginalized DIC (mDIC) that integrates them out. Regardless of the asymptotic and coherency difficulties of cDIC, this alternative is usually used in Markov chain Monte Carlo (MCMC) methods for hierarchical models because of practical convenience. The mDIC criterion is more appropriate in most cases but requires integration of the likelihood, which is computationally demanding and not implemented in Bayesian software. Therefore, we consider a method to compute mDIC by generating replicate samples of the latent variables that need to be integrated out. This alternative can be easily conducted from the MCMC output of Bayesian packages and is widely applicable to hierarchical models in general. Additionally, we propose some approximations in order to reduce the computational complexity for large-sample situations. The method is illustrated with simulated data sets and 2 medical studies, evidencing that cDIC may be misleading whilst mDIC appears pertinent. Copyright © 2018 John Wiley & Sons, Ltd.

  8. Synthesis of hierarchical mesoporous lithium nickel cobalt manganese oxide spheres with high rate capability for lithium-ion batteries

    NASA Astrophysics Data System (ADS)

    Tong, Wei; Huang, Yudai; Cai, Yanjun; Guo, Yong; Wang, Xingchao; Jia, Dianzeng; Sun, Zhipeng; Pang, Weikong; Guo, Zaiping; Zong, Jun

    2018-01-01

    Hierarchical mesoporous LiNi1/3Co1/3Mn1/3O2 spheres have been synthesized by urea-assisted solvothermal method with adding Triton X-100. The structure and morphology of the as-prepared materials were analyzed by X-ray diffraction and electron microscope. The results show that the as-prepared samples can be indexed as hexagonal layered structure with hierarchical architecture, and the possible formation mechanism is speculated. When evaluated as cathode material, the hierarchical mesoporous LiNi1/3Co1/3Mn1/3O2 spheres show good electrochemical properties with high initial discharge capacity of 129.9 mAh g-1, and remain the discharge capacity of 95.5 mAh g-1 after 160 cycles at 10C. The excellent electrochemical performance of the as-prepared sample can be attributed to its stable hierarchical mesoporous framework in conjunction with large specific surface, low cation mixing and small particle size. They not only provide a large number of reaction sites for surface or interface reaction, but also shorten the diffusion length of Li+ ions. Meanwhile, the mesoporous spheres composed of nanoparticles can contribute to high rate ability and buffer volume changes during charge/discharge process.

  9. Quantitative Analysis and Comparison of Four Major Flavonol Glycosides in the Leaves of Toona sinensis (A. Juss.) Roemer (Chinese Toon) from Various Origins by High-Performance Liquid Chromatography-Diode Array Detector and Hierarchical Clustering Analysis

    PubMed Central

    Sun, Xiaoxiang; Zhang, Liting; Cao, Yaqi; Gu, Qinying; Yang, Huan; Tam, James P.

    2016-01-01

    Background: Toona sinensis (A. Juss.) Roemer is an endemic species of Toona genus native to Asian area. Its dried leaves are applied in the treatment of many diseases; however, few investigations have been reported for the quantitative analysis and comparison of major bioactive flavonol glycosides in the leaves harvested from various origins. Objective: To quantitatively analyze four major flavonol glycosides including rutinoside, quercetin-3-O-β-D-glucoside, quercetin-3-O-α-L-rhamnoside, and kaempferol-3-O-α-L-rhamnoside in the leaves from different production sites and classify them according to the content of these glycosides. Materials and Methods: A high-performance liquid chromatography-diode array detector (HPLC-DAD) method for their simultaneous determination was developed and validated for linearity, precision, accuracy, stability, and repeatability. Moreover, the method established was then employed to explore the difference in the content of these four glycosides in raw materials. Finally, a hierarchical clustering analysis was performed to classify 11 voucher specimens. Results: The separation was performed on a Waters XBridge Shield RP18 column (150 mm × 4.6 mm, 3.5 μm) kept at 35°C, and acetonitrile and H2O containing 0.30% trifluoroacetic acid as mobile phase was driven at 1.0 mL/min during the analysis. Ten microliters of solution were injected and 254 nm was selected to monitor the separation. A strong linear relationship between the peak area and concentration of four analytes was observed. And, the method was also validated to be repeatable, stable, precise, and accurate. Conclusion: An efficient and reliable HPLC-DAD method was established and applied in the assays for the samples from 11 origins successfully. Moreover, the content of those flavonol glycosides varied much among different batches, and the flavonoids could be considered as biomarkers to control the quality of Chinese Toon. SUMMARY Four major flavonol glycosides in the leaves of Toona sinensis were determined by HPLC-DAD and their contents were compared among various origins by HCA. Abbreviations used: HPLC-DAD: High-performance liquid chromatography-diode array detector, HCA: Hierarchical clustering analysis, MS: Mass spectrometry, RSD: Relative standard deviation. PMID:27279719

  10. CuO-Decorated ZnO Hierarchical Nanostructures as Efficient and Established Sensing Materials for H2S Gas Sensors

    PubMed Central

    Vuong, Nguyen Minh; Chinh, Nguyen Duc; Huy, Bui The; Lee, Yong-Ill

    2016-01-01

    Highly sensitive hydrogen sulfide (H2S) gas sensors were developed from CuO-decorated ZnO semiconducting hierarchical nanostructures. The ZnO hierarchical nanostructure was fabricated by an electrospinning method following hydrothermal and heat treatment. CuO decoration of ZnO hierarchical structures was carried out by a wet method. The H2S gas-sensing properties were examined at different working temperatures using various quantities of CuO as the variable. CuO decoration of the ZnO hierarchical structure was observed to promote sensitivity for H2S gas higher than 30 times at low working temperature (200 °C) compared with that in the nondecorated hierarchical structure. The sensing mechanism of the hybrid sensor structure is also discussed. The morphology and characteristics of the samples were examined by scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), UV-vis absorption, photoluminescence (PL), and electrical measurements. PMID:27231026

  11. Contextual Effects on Kindergarten Teachers' Intention to Report Child Abuse

    ERIC Educational Resources Information Center

    Feng, Jui-Ying; Wu, Yow-Wu B.; Fetzer, Susan; Chang, Hsin-Yi

    2012-01-01

    Child abuse is underreported for children with socioeconomic inequalities. The impact of geographic location combined with sociocultural characteristics on teachers' reports of child abuse remains unclear. A national survey of 572 kindergarten teachers from 79 schools in Taiwan used hierarchical linear modeling to investigate the contribution of…

  12. VR Employment Outcomes of Individuals with Autism Spectrum Disorders: A Decade in the Making

    ERIC Educational Resources Information Center

    Alverson, Charlotte Y.; Yamamoto, Scott H.

    2018-01-01

    This study utilized hierarchical linear modeling analysis of a 10-year extant dataset from Rehabilitation Services Administration to investigate significant predictors of employment outcomes for vocational rehabilitation (VR) clients with autism. Predictor variables were gender, ethnicity, attained education level, IEP status in high school,…

  13. Hierarchy and Scope of Planning in Subject-Verb Agreement Production

    ERIC Educational Resources Information Center

    Gillespie, Maureen; Pearlmutter, Neal J.

    2011-01-01

    Two subject-verb agreement error elicitation studies tested the hierarchical feature-passing account of agreement computation in production and three timing-based alternatives: linear distance to the head noun, semantic integration, and a combined effect of both (a scope of planning account). In Experiment 1, participants completed subject noun…

  14. Pessimism, Trauma, Risky Sex: Covariates of Depression in College Students

    ERIC Educational Resources Information Center

    Swanholm, Eric; Vosvick, Mark; Chng, Chwee-Lye

    2009-01-01

    Objective: To explain variance in depression in students (N = 648) using a model incorporating sexual trauma, pessimism, and risky sex. Method: Survey data collected from undergraduate students receiving credit for participation. Results: Controlling for demographics, a hierarchical linear regression analysis [Adjusted R[superscript 2] = 0.34,…

  15. Using Hierarchical Linear Modeling for Proformative Evaluation: A Case Example

    ERIC Educational Resources Information Center

    Coryn, Chris L. S.

    2007-01-01

    Proformative evaluation--first introduced in Scriven's (2006) "The great enigma: An evaluation design puzzle"--"is motivated, like formative evaluation, by the intention to improve something that is still developing, but unlike formative, the improvement is only possible by taking action, hence proactive instead of reactive, hence both, hence…

  16. Individual and School Predictors of Middle School Aggression

    ERIC Educational Resources Information Center

    Reis, Janet; Trockel, Mickey; Mulhall, Peter

    2007-01-01

    Hierarchical linear modeling is used to assess individual student, family, and school predictors of aggression in 111,662 students in sixth, seventh, and eighth grades. Nine measures of problem-solving strategies, quality of family and peer interaction, and perceptions of school climate are analyzed at the individual student level. Eight measures…

  17. Factors Affecting Online Groupwork Interest: A Multilevel Analysis

    ERIC Educational Resources Information Center

    Du, Jianxia; Xu, Jianzhong; Fan, Xitao

    2013-01-01

    The purpose of the present study is to examine the personal and contextual factors that may affect students' online groupwork interest. Using the data obtained from graduate students in an online course, both student- and group-level predictors for online groupwork interest were analyzed within the framework of hierarchical linear modeling…

  18. Predicting South Korean University Students' Happiness through Social Support and Efficacy Beliefs

    ERIC Educational Resources Information Center

    Lee, Diane Sookyoung; Padilla, Amado M.

    2016-01-01

    This study investigated the adversity and coping experiences of 198 South Korean university students and takes a cultural lens in understanding how social and individual factors shape their happiness. Hierarchical linear regression analyses suggest that Korean students' perceptions of social support significantly predicted their happiness,…

  19. The Effects of Academic Optimism on Elementary Reading Achievement

    ERIC Educational Resources Information Center

    Bevel, Raymona K.; Mitchell, Roxanne M.

    2012-01-01

    Purpose: The purpose of this paper is to explore the relationship between academic optimism (AO) and elementary reading achievement (RA). Design/methodology/approach: Using correlation and hierarchical linear regression, the authors examined school-level effects of AO on fifth grade reading achievement in 29 elementary schools in Alabama.…

  20. Examining Elementary Social Studies Marginalization: A Multilevel Model

    ERIC Educational Resources Information Center

    Fitchett, Paul G.; Heafner, Tina L.; Lambert, Richard G.

    2014-01-01

    Utilizing data from the National Center for Education Statistics Schools and Staffing Survey (SASS), a multilevel model (Hierarchical Linear Model) was developed to examine the association of teacher/classroom and state level indicators on reported elementary social studies instructional time. Findings indicated that state testing policy was a…

  1. Effects of Preschool Intervention Strategies on School Readiness in Kindergarten

    ERIC Educational Resources Information Center

    Ma, Xin; Nelson, Regena F.; Shen, Jianping; Krenn, Huilan Y.

    2015-01-01

    Using hierarchical linear modeling, the present study aimed to examine whether targeted intervention strategies implemented individually during a preschool program exhibited any short-term and long-term effects on children's school readiness in kindergarten, utilizing data gathered through the Supporting Partnerships to Assure Ready Kids (SPARK)…

  2. Nonresident Undergraduates' Performance in English Writing Classes-- Hierarchical Linear Modeling Analysis

    ERIC Educational Resources Information Center

    Vaughn, Allison A.; Bergman, Matthew; Fass-Holmes, Barry

    2015-01-01

    Do undergraduates whose native language is not English have writing deficiencies leading to academic struggles? The present study showed that the answer to this question was "no" at an American West Coast public university. This university's nonresident undergraduates on average earned B- to B+ in their colleges' English…

  3. Centering Effects in HLM Level-1 Predictor Variables.

    ERIC Educational Resources Information Center

    Schumacker, Randall E.; Bembry, Karen

    Research has suggested that important research questions can be addressed with meaningful interpretations using hierarchical linear modeling (HLM). The proper interpretation of results, however, is invariably linked to the choice of centering for the Level-1 predictor variables that produce the outcome measure for the Level-2 regression analysis.…

  4. Substance Use, Anxiety, and Depressive Symptoms among College Students

    ERIC Educational Resources Information Center

    Walters, Kenneth S.; Bulmer, Sandra Minor; Troiano, Peter F.; Obiaka, Uzoma; Bonhomme, Rebecca

    2018-01-01

    Research on college substance use and mental illness is limited and inconsistent. Measures of substance use, and anxiety and depressive symptoms, were completed by 1,316 undergraduates within a major drug transportation corridor. Hierarchical linear regressions were used to test associations between anxious and depressive symptoms and substance…

  5. A Study on the Horizontal Stratification of Higher Education in South Korea

    ERIC Educational Resources Information Center

    Park, Hwanbo

    2015-01-01

    This study analyzed university and college graduates' income gap in South Korea to investigate factors influencing such disparities. Specifically, this study focused on types of higher education institutions and academic disciplines among the many factors affecting post-graduation income differences, using a hierarchical linear model. According to…

  6. Racial Identity and Academic Achievement in the Neighborhood Context: A Multilevel Analysis

    ERIC Educational Resources Information Center

    Byrd, Christy M.; Chavous, Tabbye M.

    2009-01-01

    Increasingly, researchers have found relationships between a strong, positive sense of racial identity and academic achievement among African American youth. Less attention, however, has been given to the roles and functions of racial identity among youth experiencing different social and economic contexts. Using hierarchical linear modeling, the…

  7. Caregiver Life Satisfaction: Relationship to Youth Symptom Severity through Treatment

    ERIC Educational Resources Information Center

    Athay, M. Michele

    2012-01-01

    This study utilized the Satisfaction with Life Scale to investigate the life satisfaction of caregivers for youth receiving mental health services (N = 383). Specifically, this study assessed how caregiver life satisfaction relates to youth symptom severity throughout treatment. Hierarchical linear modeling with a time-varying covariate was used…

  8. Psychopathology and Marital Satisfaction: The Importance of Evaluating Both Partners

    ERIC Educational Resources Information Center

    Whisman, Mark A.; Uebelacker, Lisa A.; Weinstock, Lauren M.

    2004-01-01

    Using path analysis and hierarchical linear modeling, the authors evaluated the associations between both partners' level of depression and anxiety, as measured by Minnesota Multiphasic Personality Inventory-2 (MMPI-2) content scales, and both partners' level of marital satisfaction among married couples (N = 774) that participated in the MMPI…

  9. Effects of Technology Immersion on Middle School Students' Learning Opportunities and Achievement

    ERIC Educational Resources Information Center

    Shapley, Kelly; Sheehan, Daniel; Maloney, Catherine; Caranikas-Walker, Fanny

    2011-01-01

    An experimental study of the Technology Immersion model involved comparisons between 21 middle schools that received laptops for each teacher and student, instructional and learning resources, professional development, and technical and pedagogical support, and 21 control schools. Using hierarchical linear modeling to analyze longitudinal survey…

  10. Working-Class Jobs and New Parents' Mental Health

    ERIC Educational Resources Information Center

    Perry-Jenkins, Maureen; Smith, JuliAnna Z.; Goldberg, Abbie E.; Logan, Jade

    2011-01-01

    Little research has explored linkages between work conditions and mental health in working-class employed parents. The current study aims to address this gap, employing hierarchical linear modeling techniques to examine how levels of and changes in job autonomy, job urgency, supervisor support, and coworker support predicted parents' depressive…

  11. Handling Correlations between Covariates and Random Slopes in Multilevel Models

    ERIC Educational Resources Information Center

    Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders

    2014-01-01

    This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…

  12. Dealing with Dependence (Part II): A Gentle Introduction to Hierarchical Linear Modeling

    ERIC Educational Resources Information Center

    McCoach, D. Betsy

    2010-01-01

    In education, most naturally occurring data are clustered within contexts. Students are clustered within classrooms, classrooms are clustered within schools, and schools are clustered within districts. When people are clustered within naturally occurring organizational units such as schools, classrooms, or districts, the responses of people from…

  13. Predicting Homework Effort: Support for a Domain-Specific, Multilevel Homework Model

    ERIC Educational Resources Information Center

    Trautwein, Ulrich; Ludtke, Oliver; Schnyder, Inge; Niggli, Alois

    2006-01-01

    According to the domain-specific, multilevel homework model proposed in the present study, students' homework effort is influenced by expectancy and value beliefs, homework characteristics, parental homework behavior, and conscientiousness. The authors used structural equation modeling and hierarchical linear modeling analyses to test the model in…

  14. A Multilevel Analysis on Student Learning in Colleges and Universities.

    ERIC Educational Resources Information Center

    Hu, Shouping; Kuh, George D.

    This study tested a learning productivity model for undergraduates at four-year colleges and universities using hierarchical linear modeling. Student level data were from 44,328 full-time enrolled undergraduates from 120 four-year colleges and universities who completed the College Student Experiences Questionnaire between 1990 and 1997.…

  15. Predictors of Burnout in Children's Residential Treatment Center Staff

    ERIC Educational Resources Information Center

    Lakin, Brittany L.; Leon, Scott C.; Miller, Steven A.

    2008-01-01

    This study explored burnout among frontline staff within a children's residential treatment center (RTC) population. Data were collected from 375 full-time, frontline, children's RTC staff employed at 21 RTCs in Illinois. Using hierarchical linear modeling (HLM), results indicated that frontline staff age, training, empathic concern, communicative…

  16. Multilevel Correlates of Childhood Physical Aggression and Prosocial Behavior

    ERIC Educational Resources Information Center

    Romano, Elisa; Tremblay, Richard E.; Boulerice, Bernard; Swisher, Raymond

    2005-01-01

    The study identified independent individual, family, and neighborhood correlates of children's physical aggression and prosocial behavior. Participants were 2,745-11-year olds nested in 1,982 families, which were themselves nested in 96 Canadian neighborhoods. Hierarchical linear modeling showed that the total variation explained by the…

  17. Romantic Relationships and Adjustment Problems in China: The Moderating Effect of Classroom Romantic Context

    ERIC Educational Resources Information Center

    Hou, Jinqin; Natsuaki, Misaki N.; Zhang, Jianxin; Guo, Fei; Huang, Zheng; Wang, Mianbo; Chen, Zhiyan

    2013-01-01

    Theoretical and empirical research has shown that adolescent romantic relationships are associated with a wide range of developmental outcomes, including adverse consequences. The present study used a hierarchical linear model to examine the moderating effect of classroom romantic context on the association between adolescent romantic…

  18. Leader-Member Exchange, Learning Orientation and Innovative Work Behavior

    ERIC Educational Resources Information Center

    Atitumpong, Aungkhana; Badir, Yuosre F.

    2018-01-01

    Purpose: This study aims to examine the effects of leader-member exchange (LMX) and employee learning orientation on employee innovative work behavior (IWB) through creative self-efficacy. Design/methodology/approach: Data have been collected from 337 employees and 137 direct managers from manufacturing sector. A hierarchical linear model has been…

  19. Diversity and Educational Benefits: Moving Beyond Self-Reported Questionnaire Data

    ERIC Educational Resources Information Center

    Herzog, Serge

    2007-01-01

    Effects of ethnic/racial diversity among students and faculty on cognitive growth of undergraduate students are estimated via a series of hierarchical linear and multinomial logistic regression models. Using objective measures of compositional, curricular, and interactional diversity based on actuarial course enrollment records of over 6,000…

  20. Neighborhood Disadvantage and Variations in Blood Pressure

    ERIC Educational Resources Information Center

    Cathorall, Michelle L.; Xin, Huaibo; Peachey, Andrew; Bibeau, Daniel L.; Schulz, Mark; Aronson, Robert

    2015-01-01

    Purpose: To examine the extent to which neighborhood disadvantage accounts for variation in blood pressure. Methods: Demographic, biometric, and self-reported data from 19,261 health screenings were used. Addresses of participants were geocoded and located within census block groups (n = 14,510, 75.3%). Three hierarchical linear models were…

  1. The Effects of High School Organization on Dropping Out: An Exploratory Investigation.

    ERIC Educational Resources Information Center

    Bryk, Anthony S.; Thum, Yeow Meng

    1989-01-01

    A hierarchical linear model analysis investigated the effects of structural and normative features of schools on absenteeism and the probability of dropping out. Subjects included 4,450 sophomores in 160 Catholic and public high schools from the High School and Beyond 1980 cohort. (SLD)

  2. Departmental Contexts and Faculty Research Activity in Norway

    ERIC Educational Resources Information Center

    Smeby, Jens-Christian; Try, Sverre

    2005-01-01

    The aim of the paper is to examine the relationship between departmental attributes and university faculty research activity. Since individual and departmental factors are highly interrelated, individual attributes are included in a hierarchical linear model taking into consideration the nested structure of the data. Research activity is measured…

  3. Unpacking the Inequality among Turkish Schools: Findings from PISA 2006

    ERIC Educational Resources Information Center

    Alacaci, Cengiz; Erbas, Ayhan Kursat

    2010-01-01

    The study investigates the effects of certain school characteristics on students' mathematics performances in Turkey in the PISA 2006 while controlling for family background and demographic characteristics. Three models of Hierarchical Linear Modeling (HLM) are constructed. The results reveal that 55% of the variance is attributable to…

  4. Accelerating Recovery from Poverty: Prevention Effects for Recently Separated Mothers

    ERIC Educational Resources Information Center

    Forgatch, Marion S.; DeGarmo, David S.

    2007-01-01

    This study evaluated benefits of a preventive intervention to the living standards of recently separated mothers. In the Oregon Divorce Study's randomized experimental design, data were collected 5 times over 30 months and evaluated with Hierarchical Linear Growth Models. Relative to their no-intervention control counterparts, experimental mothers…

  5. Neighborhood Context and Police Vigor: A Multilevel Analysis

    ERIC Educational Resources Information Center

    Sobol, James J.; Wu, Yuning; Sun, Ivan Y.

    2013-01-01

    This study provides a partial test of Klinger's ecological theory of police behavior using hierarchical linear modeling on 1,677 suspects who had encounters with police within 24 beats. The current study used data from four sources originally collected by the Project on Policing Neighborhoods (POPN), including systematic social observation,…

  6. School Health Promotion Policies and Adolescent Risk Behaviors in Israel: A Multilevel Analysis

    ERIC Educational Resources Information Center

    Tesler, Riki; Harel-Fisch, Yossi; Baron-Epel, Orna

    2016-01-01

    Background: Health promotion policies targeting risk-taking behaviors are being implemented across schools in Israel. This study identified the most effective components of these policies influencing cigarette smoking and alcohol consumption among adolescents. Methods: Logistic hierarchical linear model (HLM) analysis of data for 5279 students in…

  7. School-Based Kindergarten Transition Practices and Child Outcomes: Revisiting the Issue

    ERIC Educational Resources Information Center

    Little, Michael H.

    2017-01-01

    The purpose of this study was to examine the relationship between school-based kindergarten transition practices and student achievement and executive functioning using recent, nationally representative data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11. The analysis employed 3-level hierarchical linear models and…

  8. Aerial surveillance based on hierarchical object classification for ground target detection

    NASA Astrophysics Data System (ADS)

    Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

    2015-03-01

    Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

  9. Hierarchical hybrid film of MnO2 nanoparticles/multi-walled fullerene nanotubes-graphene for highly selective sensing of hydrogen peroxide.

    PubMed

    Pan, Yang; Hou, Zhaohui; Yi, Wei; Zhu, Wei; Zeng, Fanyan; Liu, You-Nian

    2015-08-15

    Hierarchical hybrid films of MnO2 nanoparticles/multi-walled fullerene nanotubes-graphene (MNPs/MWFNTs-GS) have been prepared via a simple wet-chemical method. For this purpose, MWFNTs (~300nm in length) are fabricated from tailoring multi-walled carbon nanotubes (MWCNTs), and then inserted into GS to pile up into a hierarchical hybrid film with the in situ formative MNPs. Scanning electron microscope, transmission electron microscope and X-ray diffraction are used to confirm the morphology and structure of the as-obtained film. The electrochemical studies reveal that MNPs/MWFNTs-GS exhibit significantly enhanced electrocatalytic activity compared with MNPs/GS, and show a rapid response to H2O2 over a wide linear range of 2.0μM-8.44mM with a high sensitivity of 206.3μA mM(-1)cm(-2) and an excellent selectivity. These favorable electrochemical detection properties may be mainly attributed to the introduction of MWFNTs, which helps to promote the electron/ion transport between MNPs and GS and form the hierarchical film structure. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Using GOMS models and hypertext to create representations of medical procedures for online display

    NASA Technical Reports Server (NTRS)

    Gugerty, Leo; Halgren, Shannon; Gosbee, John; Rudisill, Marianne

    1991-01-01

    This study investigated two methods to improve organization and presentation of computer-based medical procedures. A literature review suggested that the GOMS (goals, operators, methods, and selecton rules) model can assist in rigorous task analysis, which can then help generate initial design ideas for the human-computer interface. GOMS model are hierarchical in nature, so this study also investigated the effect of hierarchical, hypertext interfaces. We used a 2 x 2 between subjects design, including the following independent variables: procedure organization - GOMS model based vs. medical-textbook based; navigation type - hierarchical vs. linear (booklike). After naive subjects studies the online procedures, measures were taken of their memory for the content and the organization of the procedures. This design was repeated for two medical procedures. For one procedure, subjects who studied GOMS-based and hierarchical procedures remembered more about the procedures than other subjects. The results for the other procedure were less clear. However, data for both procedures showed a 'GOMSification effect'. That is, when asked to do a free recall of a procedure, subjects who had studies a textbook procedure often recalled key information in a location inconsistent with the procedure they actually studied, but consistent with the GOMS-based procedure.

  11. Hierarchical models of animal abundance and occurrence

    USGS Publications Warehouse

    Royle, J. Andrew; Dorazio, R.M.

    2006-01-01

    Much of animal ecology is devoted to studies of abundance and occurrence of species, based on surveys of spatially referenced sample units. These surveys frequently yield sparse counts that are contaminated by imperfect detection, making direct inference about abundance or occurrence based on observational data infeasible. This article describes a flexible hierarchical modeling framework for estimation and inference about animal abundance and occurrence from survey data that are subject to imperfect detection. Within this framework, we specify models of abundance and detectability of animals at the level of the local populations defined by the sample units. Information at the level of the local population is aggregated by specifying models that describe variation in abundance and detection among sites. We describe likelihood-based and Bayesian methods for estimation and inference under the resulting hierarchical model. We provide two examples of the application of hierarchical models to animal survey data, the first based on removal counts of stream fish and the second based on avian quadrat counts. For both examples, we provide a Bayesian analysis of the models using the software WinBUGS.

  12. Embodied linearity of speed control in Drosophila melanogaster.

    PubMed

    Medici, V; Fry, S N

    2012-12-07

    Fruitflies regulate flight speed by adjusting their body angle. To understand how low-level posture control serves an overall linear visual speed control strategy, we visually induced free-flight acceleration responses in a wind tunnel and measured the body kinematics using high-speed videography. Subsequently, we reverse engineered the transfer function mapping body pitch angle onto flight speed. A linear model is able to reproduce the behavioural data with good accuracy. Our results show that linearity in speed control is realized already at the level of body posture-mediated speed control and is therefore embodied at the level of the complex aerodynamic mechanisms of body and wings. Together with previous results, this study reveals the existence of a linear hierarchical control strategy, which can provide relevant control principles for biomimetic implementations, such as autonomous flying micro air vehicles.

  13. Embodied linearity of speed control in Drosophila melanogaster

    PubMed Central

    Medici, V.; Fry, S. N.

    2012-01-01

    Fruitflies regulate flight speed by adjusting their body angle. To understand how low-level posture control serves an overall linear visual speed control strategy, we visually induced free-flight acceleration responses in a wind tunnel and measured the body kinematics using high-speed videography. Subsequently, we reverse engineered the transfer function mapping body pitch angle onto flight speed. A linear model is able to reproduce the behavioural data with good accuracy. Our results show that linearity in speed control is realized already at the level of body posture-mediated speed control and is therefore embodied at the level of the complex aerodynamic mechanisms of body and wings. Together with previous results, this study reveals the existence of a linear hierarchical control strategy, which can provide relevant control principles for biomimetic implementations, such as autonomous flying micro air vehicles. PMID:22933185

  14. Diurnal Coupling between Testosterone and Cortisol from Adolescence to Older Adulthood

    PubMed Central

    Harden, K. Paige; Wrzus, Cornelia; Luong, Gloria; Grotzinger, Andrew; Bajbouj, Malek; Rauers, Antje; Wagner, Gert G.; Riediger, Michaela

    2016-01-01

    The hypothalamic-pituitary-adrenal (HPA) and hypothalamic-pituitary-gonadal (HPG) axes are typically conceptualized as mutually inhibitory systems; however, previous studies have found evidence for positive within-person associations (i.e., coupling) between cortisol and testosterone. One developmental hypothesis is that positive testosterone-cortisol coupling is unique to the adolescent period and that coupling becomes attenuated, or even switches direction, in adulthood. This study used a lifespan sample (N = 292, ages 11 to 88) to test for age-related differences in coupling between cortisol and testosterone in daily life. Participants provided salivary hormone samples at waking, 30 minutes after waking, and during the evening for two days. Hierarchical linear modeling was used to test the within-person and between-person associations between testosterone and cortisol. Within-person associations were further decomposed into associations due to coupled diurnal change versus coupled variability around diurnal change. Results indicated positive associations between cortisol and testosterone at all levels of analysis. Additionally, positive coupling was evident across the lifespan, even in older adults who are no longer expected to reproduce, but further investigation of developmental differences with a larger sample is necessary. Potential mechanisms and functions for positive coupling are discussed. PMID:27474909

  15. When goals diverge: Staff consensus and the organizational climate.

    PubMed

    Melnick, Gerald; Ulaszek, Wendy R; Lin, Hsiu-Ju; Wexler, Harry K

    2009-08-01

    A sample of correctional officers and prison substance abuse treatment staff collected by the National Criminal Justice Treatment Practices Survey is used to provide an exploratory study of an aspect of organizational culture consisting of consensus (agreement) among prison personnel regarding their beliefs about rehabilitation in the presence of conflicting organizational goals and aspects of the organizational climate important to change. Findings show that among those staff members responding to the survey, the belief in rehabilitation scale mean score was associated with higher levels of organizational commitment, and interdepartmental coordination. However, an hierarchical linear modeling (HLM) analysis that used an index score derived from the standard deviation for staff consensus regarding these same beliefs about rehabilitation produced a different pattern of results, showing that high levels of consensus were associated with job frustration, cynicism towards the ability of the institution to change, and lower levels of organizational commitment. The authors conclude that, although the sample may not express the beliefs of corrections officers or prison-based treatment staff at large, within the sample, consensus appeared to play a unique role in evaluating the effect of divergent goals on organizational climate as it relates to change, and warrants consideration when considering the effects of organizational climate.

  16. Optimism is universal: exploring the presence and benefits of optimism in a representative sample of the world.

    PubMed

    Gallagher, Matthew W; Lopez, Shane J; Pressman, Sarah D

    2013-10-01

    Current theories of optimism suggest that the tendency to maintain positive expectations for the future is an adaptive psychological resource associated with improved well-being and physical health, but the majority of previous optimism research has been conducted in industrialized nations. The present study examined (a) whether optimism is universal, (b) what demographic factors predict optimism, and (c) whether optimism is consistently associated with improved subjective well-being and perceived health worldwide. The present study used representative samples of 142 countries that together represent 95% of the world's population. The total sample of 150,048 individuals had a mean age of 38.28 (SD = 16.85) and approximately equal sex distribution (51.2% female). The relationships between optimism, subjective well-being, and perceived health were examined using hierarchical linear modeling. Results indicated that most individuals and most countries worldwide are optimistic and that higher levels of optimism are associated with improved subjective well-being and perceived health worldwide. The present study provides compelling evidence that optimism is a universal phenomenon and that the associations between optimism and improved psychological functioning are not limited to industrialized nations. © 2012 Wiley Periodicals, Inc.

  17. Quality evaluation of Evodia rutaecarpa (Juss.) Benth by high performance liquid chromatography with photodiode-array detection.

    PubMed

    Zhao, Yang; Li, Zhangwan; Zhou, Xin; Cai, Zongwei; Gong, Xiaojian; Zhou, Chanyuan

    2008-12-01

    A simple, sensitive and accurate HPLC-DAD method was developed for simultaneous determination of wuchuyuamide-I, quercetin, limonin, evodiamine and rutaecarpine in Evodia rutaecarpa that has been widely used as one of the traditional Chinese medicines (TCMs). Chromatographic separations were performed on a reverse-phase C(18) column with the gradient elution of acetonitrile-water and the simultaneous detection at five wavelengths. Good linear behaviors over the investigated concentration ranges were observed with the values of r higher than 0.999 for all the analytes. The recoveries measured at three levels varied from 98.77 to 102.36%. The validated method was successfully applied for the simultaneous determination of the five chemical constituents in 36 batches of samples collected from different regions or time that were investigated and authenticated as E. rutaecarpa (Juss.) Benth. Hierarchical clustering analysis (HCA) and principal components analysis (PCA) were performed to differentiate and classify the samples based on the contents of the five characteristic constituents. The total contents of evodiamine and rutaecarpine in different samples were calculated and the blending method proposed was demonstrated to be very useful in saving resources and in guiding rational herb use.

  18. A unified stochastic formulation of dissipative quantum dynamics. I. Generalized hierarchical equations

    NASA Astrophysics Data System (ADS)

    Hsieh, Chang-Yu; Cao, Jianshu

    2018-01-01

    We extend a standard stochastic theory to study open quantum systems coupled to a generic quantum environment. We exemplify the general framework by studying a two-level quantum system coupled bilinearly to the three fundamental classes of non-interacting particles: bosons, fermions, and spins. In this unified stochastic approach, the generalized stochastic Liouville equation (SLE) formally captures the exact quantum dissipations when noise variables with appropriate statistics for different bath models are applied. Anharmonic effects of a non-Gaussian bath are precisely encoded in the bath multi-time correlation functions that noise variables have to satisfy. Starting from the SLE, we devise a family of generalized hierarchical equations by averaging out the noise variables and expand bath multi-time correlation functions in a complete basis of orthonormal functions. The general hierarchical equations constitute systems of linear equations that provide numerically exact simulations of quantum dynamics. For bosonic bath models, our general hierarchical equation of motion reduces exactly to an extended version of hierarchical equation of motion which allows efficient simulation for arbitrary spectral densities and temperature regimes. Similar efficiency and flexibility can be achieved for the fermionic bath models within our formalism. The spin bath models can be simulated with two complementary approaches in the present formalism. (I) They can be viewed as an example of non-Gaussian bath models and be directly handled with the general hierarchical equation approach given their multi-time correlation functions. (II) Alternatively, each bath spin can be first mapped onto a pair of fermions and be treated as fermionic environments within the present formalism.

  19. Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL.

    PubMed

    Wang, Lili; Palmer, Andrew J; Cocker, Fiona; Sanderson, Kristy

    2017-01-09

    No universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored. This study examined the performance of the count and cluster definitions of multimorbidity on the sociodemographic profile and health-related quality of life (HRQoL) in a general population. Data were derived from the nationally representative 2007 Australian National Survey of Mental Health and Wellbeing (n = 8841). The HRQoL scores were measured using the Assessment of Quality of Life (AQoL-4D) instrument. The simple count (2+ & 3+ conditions) and hierarchical cluster methods were used to define/identify clusters of multimorbidity. Linear regression was used to assess the associations between HRQoL and multimorbidity as defined by the different methods. The assessment of multimorbidity, which was defined using the count method, resulting in the prevalence of 26% (MM2+) and 10.1% (MM3+). Statistically significant clusters identified through hierarchical cluster analysis included heart or circulatory conditions (CVD)/arthritis (cluster-1, 9%) and major depressive disorder (MDD)/anxiety (cluster-2, 4%). A sensitivity analysis suggested that the stability of the clusters resulted from hierarchical clustering. The sociodemographic profiles were similar between MM2+, MM3+ and cluster-1, but were different from cluster-2. HRQoL was negatively associated with MM2+ (β: -0.18, SE: -0.01, p < 0.001), MM3+ (β: -0.23, SE: -0.02, p < 0.001), cluster-1 (β: -0.10, SE: 0.01, p < 0.001) and cluster-2 (β: -0.36, SE: 0.01, p < 0.001). Our findings confirm the existence of an inverse relationship between multimorbidity and HRQoL in the Australian population and indicate that the hierarchical clustering approach is validated when the outcome of interest is HRQoL from this head-to-head comparison. Moreover, a simple count fails to identify if there are specific conditions of interest that are driving poorer HRQoL. Researchers should exercise caution when selecting a definition of multimorbidity because it may significantly influence the study outcomes.

  20. The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

    NASA Astrophysics Data System (ADS)

    Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

    2018-04-01

    Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

  1. MicroRNA Expression in Formalin-fixed Paraffin-embedded Cancer Tissue: Identifying Reference MicroRNAs and Variability.

    PubMed

    Boisen, Mogens Karsbøl; Dehlendorff, Christian; Linnemann, Dorte; Schultz, Nicolai Aagaard; Jensen, Benny Vittrup; Høgdall, Estrid Vilma Solyom; Johansen, Julia Sidenius

    2015-12-29

    Archival formalin-fixed paraffin-embedded (FFPE) cancer tissue samples are a readily available resource for microRNA (miRNA) biomarker identification. No established standard for reference miRNAs in FFPE tissue exists. We sought to identify stable reference miRNAs for normalization of miRNA expression in FFPE tissue samples from patients with colorectal (CRC) and pancreatic (PC) cancer and to quantify the variability associated with sample age and fixation. High-throughput miRNA profiling results from 203 CRC and 256 PC FFPE samples as well as from 37 paired frozen/FFPE samples from nine other CRC tumors (methodological samples) were used. Candidate reference miRNAs were identified by their correlation with global mean expression. The stability of reference genes was analyzed according to published methods. The association between sample age and global mean miRNA expression was tested using linear regression. Variability was described using correlation coefficients and linear mixed effects models. Normalization effects were determined by changes in standard deviation and by hierarchical clustering. We created lists of 20 miRNAs with the best correlation to global mean expression in each cancer type. Nine of these miRNAs were present in both lists, and miR-103a-3p was the most stable reference miRNA for both CRC and PC FFPE tissue. The optimal number of reference miRNAs was 4 in CRC and 10 in PC. Sample age had a significant effect on global miRNA expression in PC (50% reduction over 20 years) but not in CRC. Formalin fixation for 2-6 days decreased miRNA expression 30-65%. Normalization using global mean expression reduced variability for technical and biological replicates while normalization using the expression of the identified reference miRNAs reduced variability only for biological replicates. Normalization only had a minor impact on clustering results. We identified suitable reference miRNAs for future miRNA expression experiments using CRC- and PC FFPE tissue samples. Formalin fixation decreased miRNA expression considerably, while the effect of increasing sample age was estimated to be negligible in a clinical setting.

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

    Chen, Zhe; Cao, Minhua, E-mail: caomh@bit.edu.cn; Key Laboratory of Cluster Science, Ministry of Education of China, Department of Chemistry, Beijing Institute of Technology, Beijing 100081

    Research highlights: {yields} Novel Bi{sub 2}S{sub 3} hierarchical nanostructures self-assembled by nanorods are successfully synthesized in mild benzyl alcohol system under hydrothermal conditions. {yields} The hierarchical nanostructures exhibit a flower-like shape. {yields} PVP plays an important role for the formation of the hierarchical nanostructures. {yields} Bi{sub 2}S{sub 3} film prepared from the flower-like hierarchical nanostructures exhibits good hydrophobic properties. -- Abstract: Novel Bi{sub 2}S{sub 3} hierarchical nanostructures self-assembled by nanorods are successfully synthesized in mild benzyl alcohol system under hydrothermal conditions. The hierarchical nanostructures exhibit a flower-like shape. X-ray diffraction (XRD), X-ray photoelectron spectra (XPS), scanning electron microscopy (SEM), transmissionmore » electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), and selected area electron diffraction (SAED) were used to characterize the as-synthesized samples. Meanwhile, the effect of various experimental parameters including the concentration of reagents and reaction time on final product has been investigated. In our experiment, PVP plays an important role for the formation of the hierarchical nanostructures and the possible mechanism was proposed. In addition, Bi{sub 2}S{sub 3} film prepared from the flower-like hierarchical nanostructures exhibits good hydrophobic properties, which may bring nontrivial functionalities and may have some promising applications in the future.« less

  3. Being BOLD: The neural dynamics of face perception.

    PubMed

    Gentile, Francesco; Ales, Justin; Rossion, Bruno

    2017-01-01

    According to a non-hierarchical view of human cortical face processing, selective responses to faces may emerge in a higher-order area of the hierarchy, in the lateral part of the middle fusiform gyrus (fusiform face area [FFA]) independently from face-selective responses in the lateral inferior occipital gyrus (occipital face area [OFA]), a lower order area. Here we provide a stringent test of this hypothesis by gradually revealing segmented face stimuli throughout strict linear descrambling of phase information [Ales et al., 2012]. Using a short sampling rate (500 ms) of fMRI acquisition and single subject statistical analysis, we show a face-selective responses emerging earlier, that is, at a lower level of structural (i.e., phase) information, in the FFA compared with the OFA. In both regions, a face detection response emerging at a lower level of structural information for upright than inverted faces, both in the FFA and OFA, in line with behavioral responses and with previous findings of delayed responses to inverted faces with direct recordings of neural activity were also reported. Overall, these results support the non-hierarchical view of human cortical face processing and open new perspectives for time-resolved analysis at the single subject level of fMRI data obtained during continuously evolving visual stimulation. Hum Brain Mapp 38:120-139, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  4. Chunking dynamics: heteroclinics in mind

    PubMed Central

    Rabinovich, Mikhail I.; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S.

    2014-01-01

    Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components—brain modes—participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles—metastable states—connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics. PMID:24672469

  5. Chunking dynamics: heteroclinics in mind.

    PubMed

    Rabinovich, Mikhail I; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S

    2014-01-01

    Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components-brain modes-participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles-metastable states-connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics.

  6. Multiscale responses of soil stability and invasive plants to removal of non-native grazers from an arid conservation reserve

    USGS Publications Warehouse

    Beever, E.A.; Huso, M.; Pyke, D.A.

    2006-01-01

    Disturbances and ecosystem recovery from disturbance both involve numerous processes that operate on multiple spatial and temporal scales. Few studies have investigated how gradients of disturbance intensity and ecosystem responses are distributed across multiple spatial resolutions and also how this relationship changes through time during recovery. We investigated how cover of non-native species and soil-aggregate stability (a measure of vulnerability to erosion by water) in surface and subsurface soils varied spatially during grazing by burros and cattle and whether patterns in these variables changed after grazer removal from Mojave National Preserve, California, USA. We compared distance from water and number of ungulate defecations - metrics of longer-term and recent grazing intensity, respectively, - as predictors of our response variables. We used information-theoretic analyses to compare hierarchical linear models that accounted for important covariates and allowed for interannual variation in the disturbance-response relationship at local and landscape scales. Soil stability was greater under perennial vegetation than in bare interspaces, and surface soil stability decreased with increasing numbers of ungulate defecations. Stability of surface samples was more affected by time since removal of grazers than was stability of subsurface samples, and subsurface soil stability in bare spaces was not related to grazing intensity, time since removal, or any of our other predictors. In the high rainfall year (2003) after cattle had been removed for 1-2 years, cover of all non-native plants averaged nine times higher than in the low-rainfall year (2002). Given the heterogeneity in distribution of large-herbivore impacts that we observed at several resolutions, hierarchical analyses provided a more complete understanding of the spatial and temporal complexities of disturbance and recovery processes in arid ecosystems. ?? 2006 Blackwell Publishing Ltd.

  7. Multi-scale responses of soil stability and invasive plants to removal of non-native grazers from an arid conservation reserve

    USGS Publications Warehouse

    Beever, Erik A.; Huso, Manuela M. P.; Pyke, David A.

    2006-01-01

    Disturbances and ecosystem recovery from disturbance both involve numerous processes that operate on multiple spatial and temporal scales. Few studies have investigated how gradients of disturbance intensity and ecosystem responses are distributed across multiple spatial resolutions and also how this relationship changes through time during recovery. We investigated how cover of non-native species and soil-aggregate stability (a measure of vulnerability to erosion by water) in surface and subsurface soils varied spatially during grazing by burros and cattle and whether patterns in these variables changed after grazer removal from Mojave National Preserve, California, USA. We compared distance from water and number of ungulate defecations — metrics of longer-term and recent grazing intensity, respectively, — as predictors of our response variables. We used information-theoretic analyses to compare hierarchical linear models that accounted for important covariates and allowed for interannual variation in the disturbance–response relationship at local and landscape scales. Soil stability was greater under perennial vegetation than in bare interspaces, and surface soil stability decreased with increasing numbers of ungulate defecations. Stability of surface samples was more affected by time since removal of grazers than was stability of subsurface samples, and subsurface soil stability in bare spaces was not related to grazing intensity, time since removal, or any of our other predictors. In the high rainfall year (2003) after cattle had been removed for 1–2 years, cover of all non-native plants averaged nine times higher than in the low-rainfall year (2002). Given the heterogeneity in distribution of large-herbivore impacts that we observed at several resolutions, hierarchical analyses provided a more complete understanding of the spatial and temporal complexities of disturbance and recovery processes in arid ecosystems.

  8. Hierarchical Surface Architecture of Plants as an Inspiration for Biomimetic Fog Collectors.

    PubMed

    Azad, M A K; Barthlott, W; Koch, K

    2015-12-08

    Fog collectors can enable us to alleviate the water crisis in certain arid regions of the world. A continuous fog-collection cycle consisting of a persistent capture of fog droplets and their fast transport to the target is a prerequisite for developing an efficient fog collector. In regard to this topic, a biological superior design has been found in the hierarchical surface architecture of barley (Hordeum vulgare) awns. We demonstrate here the highly wettable (advancing contact angle 16° ± 2.7 and receding contact angle 9° ± 2.6) barbed (barb = conical structure) awn as a model to develop optimized fog collectors with a high fog-capturing capability, an effective water transport, and above all an efficient fog collection. We compare the fog-collection efficiency of the model sample with other plant samples naturally grown in foggy habitats that are supposed to be very efficient fog collectors. The model sample, consisting of dry hydrophilized awns (DH awns), is found to be about twice as efficient (fog-collection rate 563.7 ± 23.2 μg/cm(2) over 10 min) as any other samples investigated under controlled experimental conditions. Finally, a design based on the hierarchical surface architecture of the model sample is proposed for the development of optimized biomimetic fog collectors.

  9. Hydrothermal fabrication of N-doped (BiO)2CO3: Structural and morphological influence on the visible light photocatalytic activity

    NASA Astrophysics Data System (ADS)

    Dong, Fan; Wang, Rui; Li, Xinwei; Ho, Wing-Kei

    2014-11-01

    Various 3D N-doped (BiO)2CO3 (N-BOC) hierarchical superstructures self-assembled with 2D nanosheets were fabricated by one-step hydrothermal treatment of bismuth citrate and urea. The as-obtained samples were characterized by XRD, XPS, FT-IR, SEM, N2 adsorption-desorption isotherms and UV-vis DRS. The hydrothermal temperature plays a crucial role in tuning the crystal and morphological structure of the samples. Adjusting the reaction temperature to 150, 180 and 210 °C, we obtained N-doped (BiO)2CO3 samples with corresponding attractive persimmon-like, flower-like and nanoflakes nano/microstructures. The photocatalytic activities of the samples were evaluated by removal of NO under visible and solar light irradiation. The results revealed that the N-doped (BiO)2CO3 hierarchical superstructures showed enhanced visible light photocatalytic activity compared to pure (BiO)2CO3 and TiO2-based visible light photocatalysts. The outstanding photocatalytic performance of N-BOC samples can be ascribed to the doped nitrogen and the special hierarchical structure. The present work could provide new perspectives in controlling the morphological structure and photocatalytic activity of photocatalyst for better environmental pollution control.

  10. Hierarchical modeling of cluster size in wildlife surveys

    USGS Publications Warehouse

    Royle, J. Andrew

    2008-01-01

    Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

  11. Hierarchical Time-Lagged Independent Component Analysis: Computing Slow Modes and Reaction Coordinates for Large Molecular Systems.

    PubMed

    Pérez-Hernández, Guillermo; Noé, Frank

    2016-12-13

    Analysis of molecular dynamics, for example using Markov models, often requires the identification of order parameters that are good indicators of the rare events, i.e. good reaction coordinates. Recently, it has been shown that the time-lagged independent component analysis (TICA) finds the linear combinations of input coordinates that optimally represent the slow kinetic modes and may serve in order to define reaction coordinates between the metastable states of the molecular system. A limitation of the method is that both computing time and memory requirements scale with the square of the number of input features. For large protein systems, this exacerbates the use of extensive feature sets such as the distances between all pairs of residues or even heavy atoms. Here we derive a hierarchical TICA (hTICA) method that approximates the full TICA solution by a hierarchical, divide-and-conquer calculation. By using hTICA on distances between heavy atoms we identify previously unknown relaxation processes in the bovine pancreatic trypsin inhibitor.

  12. Parameterizations for ensemble Kalman inversion

    NASA Astrophysics Data System (ADS)

    Chada, Neil K.; Iglesias, Marco A.; Roininen, Lassi; Stuart, Andrew M.

    2018-05-01

    The use of ensemble methods to solve inverse problems is attractive because it is a derivative-free methodology which is also well-adapted to parallelization. In its basic iterative form the method produces an ensemble of solutions which lie in the linear span of the initial ensemble. Choice of the parameterization of the unknown field is thus a key component of the success of the method. We demonstrate how both geometric ideas and hierarchical ideas can be used to design effective parameterizations for a number of applied inverse problems arising in electrical impedance tomography, groundwater flow and source inversion. In particular we show how geometric ideas, including the level set method, can be used to reconstruct piecewise continuous fields, and we show how hierarchical methods can be used to learn key parameters in continuous fields, such as length-scales, resulting in improved reconstructions. Geometric and hierarchical ideas are combined in the level set method to find piecewise constant reconstructions with interfaces of unknown topology.

  13. An Amperometric Acetylcholinesterase Sensor Based on the Bio-templated Synthesis of Hierarchical Mesoporous Bioactive Glass Microspheres

    NASA Astrophysics Data System (ADS)

    Lv, Zhuo; Luo, Ruiping; Xi, Lijuan; Chen, Yang; Wang, Hongsu

    2017-11-01

    This work describes the synthesis of three-dimensional hollow hierarchical mesoporous bioactive glass (HMBG) microspheres based on Herba leonuri pollen grains via a hydrothermal method. The HMBG microspheres perfectly copied the hierarchical porous structure and inner hollow structure constituting the double-layer surface of the natural Herba leonuri pollen grains. This structural mimicry of the pollen grains resulted in a higher degree of adsorption of acetylcholinesterase (AChE) on HMBG microspheres in comparison with mesoporous bioactive glass. Subsequently, an amperometric biosensor for the detection of Malathion was fabricated by immobilizing AChE onto an HMBG microspheres-modified carbon paste electrode. The biosensor response exhibited two good linear ranges during an incubation time of 10 min in the malathion concentration ranges of 0.02-50 ppb and 50-600 ppb, with a detection limit of 0.0135 ppb ( S/ N = 3). Overall, the prepared enzymatic biosensor showed high sensitivity in the rapid detection of Malathion and could be applied to detect pesticide residues in vegetable matter.

  14. Nanoporous platinum-cobalt alloy for electrochemical sensing for ethanol, hydrogen peroxide, and glucose.

    PubMed

    Xu, Caixia; Sun, Fenglei; Gao, Hua; Wang, Jinping

    2013-05-30

    Nanoporous platinum-cobalt (NP-PtCo) alloy with hierarchical nanostructure is straightforwardly fabricated by dealloying PtCoAl alloy in a mild alkaline solution. Selectively etching Al resulted in a hierarchical three-dimensional network nanostructure with a narrow size distribution at 3 nm. The as-prepared NP-PtCo alloy shows superior performance toward ethanol and hydrogen peroxide (H2O2) with highly sensitive response due to its unique electrocatalytic activity. In addition, NP-PtCo also exhibits excellent amperometric durability and long-term stability for H2O2 as well as a good anti-interference toward ascorbic acid, uric acid, and dopamine. The hierarchical nanoporous architecture in PtCo alloy is also highly active for glucose sensing electrooxidation and sensing in a wide linear range. The NP-PtCo alloy holds great application potential for electrochemical sensing with simple preparation, unique catalytic activity, and high structure stability. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Superposition-Based Analysis of First-Order Probabilistic Timed Automata

    NASA Astrophysics Data System (ADS)

    Fietzke, Arnaud; Hermanns, Holger; Weidenbach, Christoph

    This paper discusses the analysis of first-order probabilistic timed automata (FPTA) by a combination of hierarchic first-order superposition-based theorem proving and probabilistic model checking. We develop the overall semantics of FPTAs and prove soundness and completeness of our method for reachability properties. Basically, we decompose FPTAs into their time plus first-order logic aspects on the one hand, and their probabilistic aspects on the other hand. Then we exploit the time plus first-order behavior by hierarchic superposition over linear arithmetic. The result of this analysis is the basis for the construction of a reachability equivalent (to the original FPTA) probabilistic timed automaton to which probabilistic model checking is finally applied. The hierarchic superposition calculus required for the analysis is sound and complete on the first-order formulas generated from FPTAs. It even works well in practice. We illustrate the potential behind it with a real-life DHCP protocol example, which we analyze by means of tool chain support.

  16. Microfibres and macroscopic films from the coordination-driven hierarchical self-assembly of cylindrical micelles

    PubMed Central

    Lunn, David J.; Gould, Oliver E. C.; Whittell, George R.; Armstrong, Daniel P.; Mineart, Kenneth P.; Winnik, Mitchell A.; Spontak, Richard J.; Pringle, Paul G.; Manners, Ian

    2016-01-01

    Anisotropic nanoparticles prepared from block copolymers are of growing importance as building blocks for the creation of synthetic hierarchical materials. However, the assembly of these structural units is generally limited to the use of amphiphilic interactions. Here we report a simple, reversible coordination-driven hierarchical self-assembly strategy for the preparation of micron-scale fibres and macroscopic films based on monodisperse cylindrical block copolymer micelles. Coordination of Pd(0) metal centres to phosphine ligands immobilized within the soluble coronas of block copolymer micelles is found to induce intermicelle crosslinking, affording stable linear fibres comprised of micelle subunits in a staggered arrangement. The mean length of the fibres can be varied by altering the micelle concentration, reaction stoichiometry or aspect ratio of the micelle building blocks. Furthermore, the fibres aggregate on drying to form robust, self-supporting macroscopic micelle-based thin films with useful mechanical properties that are analogous to crosslinked polymer networks, but on a longer length scale. PMID:27538877

  17. The Construct of Creativity: Structural Model for Self-Reported Creativity Ratings

    ERIC Educational Resources Information Center

    Kaufman, James C.; Cole, Jason C.; Baer, John

    2009-01-01

    Several thousand subjects completed self-report questionnaires about their own creativity in 56 discrete domains. This sample was then randomly divided into three subsamples that were subject to factor analyses that compared an oblique model (with a set of correlated factors) and a hierarchical model (with a single second-order, or hierarchical,…

  18. The Hierarchical Factor Model of ADHD: Invariant across Age and National Groupings?

    ERIC Educational Resources Information Center

    Toplak, Maggie E.; Sorge, Geoff B.; Flora, David B.; Chen, Wai; Banaschewski, Tobias; Buitelaar, Jan; Ebstein, Richard; Eisenberg, Jacques; Franke, Barbara; Gill, Michael; Miranda, Ana; Oades, Robert D.; Roeyers, Herbert; Rothenberger, Aribert; Sergeant, Joseph; Sonuga-Barke, Edmund; Steinhausen, Hans-Christoph; Thompson, Margaret; Tannock, Rosemary; Asherson, Philip; Faraone, Stephen V.

    2012-01-01

    Objective: To examine the factor structure of attention-deficit/hyperactivity disorder (ADHD) in a clinical sample of 1,373 children and adolescents with ADHD and their 1,772 unselected siblings recruited from different countries across a large age range. Hierarchical and correlated factor analytic models were compared separately in the ADHD and…

  19. Familial and Religious Influences on Adolescent Alcohol Use: A Multi-Level Study of Students and School Communities

    ERIC Educational Resources Information Center

    Bjarnason, Thoroddur; Thorlindsson, Thorolfur; Sigfusdottir, Inga D.; Welch, Michael R.

    2005-01-01

    A multi-level Durkheimian theory of familial and religious influences on adolescent alcohol use is developed and tested with hierarchical linear modeling of data from Icelandic schools and students. On the individual level, traditional family structure, parental monitoring, parental support, religious participation, and perceptions of divine…

  20. Comparing Private Schools and Public Schools Using Hierarchical Linear Modeling. NCES 2006-461

    ERIC Educational Resources Information Center

    Braun, Henry; Jenkins, Frank; Grigg, Wendy

    2006-01-01

    The goal of the study was to examine differences in mean National Assessment of Educational Progress (NAEP) reading and mathematics scores between public and private schools when selected characteristics of students and/or schools were taken into account. Among the student characteristics considered were gender, race/ethnicity, disability status,…

  1. Classroom Age Composition and Developmental Change in 70 Urban Preschool Classrooms

    ERIC Educational Resources Information Center

    Moller, Arlen C.; Forbes-Jones, Emma; Hightower, A. Dirk

    2008-01-01

    A multilevel modeling approach was used to investigate the influence of age composition in 70 urban preschool classrooms. A series of hierarchical linear models demonstrated that greater variance in classroom age composition was negatively related to development on the Child Observation Record (COR) Cognitive, Motor, and Social subscales. This was…

  2. The Role of Evaluative Metadata in an Online Teacher Resource Exchange

    ERIC Educational Resources Information Center

    Abramovich, Samuel; Schunn, Christian D.; Correnti, Richard J.

    2013-01-01

    A large-scale online teacher resource exchange is studied to examine the ways in which metadata influence teachers' selection of resources. A hierarchical linear modeling approach was used to tease apart the simultaneous effects of resource features and author features. From a decision heuristics theoretical perspective, teachers appear to…

  3. A Three-Level Hierarchical Linear Model Using Student Growth Curve Modeling and Contextual Data

    ERIC Educational Resources Information Center

    Giorgio, Dorian

    2012-01-01

    Educational experts have criticized status models of school accountability, as required by the No Child Left Behind Act (NCLB), describing them as ineffectual in measuring achievement because their one-time assessment of student knowledge ignores student growth. Research on student achievement has instead identified growth models as superior…

  4. Item Response Theory Using Hierarchical Generalized Linear Models

    ERIC Educational Resources Information Center

    Ravand, Hamdollah

    2015-01-01

    Multilevel models (MLMs) are flexible in that they can be employed to obtain item and person parameters, test for differential item functioning (DIF) and capture both local item and person dependence. Papers on the MLM analysis of item response data have focused mostly on theoretical issues where applications have been add-ons to simulation…

  5. How Does District Principal Evaluation Affect Learning-Centered Principal Leadership? Evidence from Michigan School Districts

    ERIC Educational Resources Information Center

    Sun, Min; Youngs, Peter

    2009-01-01

    This study used Hierarchical Multivariate Linear models to investigate relationships between principals' behaviors and district principal evaluation purpose, focus, and assessed leadership activities in 13 school districts in Michigan. The study found that principals were more likely to engage in learning-centered leadership behaviors when the…

  6. Analyzing Hierarchical Relationships Among Modes of Cognitive Reasoning and Integrated Science Process Skills.

    ERIC Educational Resources Information Center

    Yeany, Russell H.; And Others

    1986-01-01

    Searched for a learning hierarchy among skills comprising formal operations and integrated science processes. Ordering, theoretic, and probabilistic latent structure methods were used to analyze data collected from 700 science students. Both linear and branching relationships were identified within and across the two sets of skills. (Author/JN)

  7. A Multi-Level Examination of College and Its Influence on Ecumenical Worldview Development

    ERIC Educational Resources Information Center

    Mayhew, Matthew J.

    2012-01-01

    This multi-level, longitudinal study investigated the ecumenical worldview development of 13,932 students enrolled in one of 126 institutions. Results indicated that the final hierarchical linear model, consisting of institution-and-student-level predictors as well as slopes explaining the relationships among some of these predictors, explained…

  8. A Multilevel Study of the Role of Environment in Adolescent Substance Use

    ERIC Educational Resources Information Center

    Steen, Julie A.

    2010-01-01

    The purpose of this study is to assess the relationships between county-level characteristics and adolescent use of alcohol, cigarettes, and marijuana. The study consisted of a hierarchical generalized linear analysis of secondary data from the Florida Youth Substance Abuse Survey. Variables on the county level included the percent of adolescents…

  9. Trajectories of Family Management Practices and Early Adolescent Behavioral Outcomes

    ERIC Educational Resources Information Center

    Wang, Ming-Te; Dishion, Thomas J.; Stormshak, Elizabeth A.; Willett, John B.

    2011-01-01

    Stage-environment fit theory was used to examine the reciprocal lagged relations between family management practices and early adolescent problem behavior during the middle school years. In addition, the potential moderating roles of family structure and of gender were explored. Hierarchical linear modeling was used to describe patterns of growth…

  10. Marriage, Cohabitation, and Happiness: A Cross-National Analysis of 27 Countries

    ERIC Educational Resources Information Center

    Lee, Kristen Schultz; Ono, Hiroshi

    2012-01-01

    The authors investigated how the reported happiness of married and cohabiting individuals varies cross-nationally with societal gender beliefs and religious context. They used the 2002 International Social Survey Programme data from 27 countries (N = 36,889) and specified hierarchical linear models with macro-micro level interactions in order to…

  11. Do Nondomestic Undergraduates Choose a Major Field in Order to Maximize Grade Point Averages?

    ERIC Educational Resources Information Center

    Bergman, Matthew E.; Fass-Holmes, Barry

    2016-01-01

    The authors investigated whether undergraduates attending an American West Coast public university who were not U.S. citizens (nondomestic) maximized their grade point averages (GPA) through their choice of major field. Multiple regression hierarchical linear modeling analyses showed that major field's effect size was small for these…

  12. Treatment Effects of a Relationship-Strengthening Intervention for Economically Disadvantaged New Parents

    ERIC Educational Resources Information Center

    Charles, Pajarita; Jones, Anne; Guo, Shenyang

    2014-01-01

    Objective: The purpose of the present study was to evaluate the treatment effects of a relationship skills and family strengthening intervention for n = 726 high-risk, disadvantaged new parents. Method: Hierarchical linear modeling and regression models were used to assess intervention treatment effects. These findings were subsequently verified…

  13. To Enter Stone, Be Water: Situating Literacy Coaching as Rhizomatic

    ERIC Educational Resources Information Center

    Reilly, Mary Ann

    2014-01-01

    Reilly leans on the metaphor of rhizomes to remind readers that the work of a coach is not linear or hierarchical, but fluid and dynamic. Reilly frames literacy coaches as rhizomatic agents in schools and urges coaches to appreciate resistance and interruptions as critical and necessary for transformative teaching and learning.

  14. Rural Compared to Urban Home Community Settings as Predictors of First-Year Students' Adjustment to University

    ERIC Educational Resources Information Center

    Ames, Megan E.; Wintre, Maxine G.; Prancer, S. Mark; Pratt, Michael W.; Birnie-Lefcovitch, Shelly; Polivy, Janet; Adams, Gerald R.

    2014-01-01

    Undergraduates (N = 2,823) at 6 universities were surveyed longitudinally to examine the relevance of student home setting on the transition to university. Preliminary results indicated that rural students seem less likely to attend large, ethnically diverse universities. Hierarchical linear models revealed that "proximal rural" students…

  15. Predictors of Tobacco and Alcohol Refusal Efficacy for Urban and Rural African-American Adolescents

    ERIC Educational Resources Information Center

    Nasim, Aashir; Belgrave, Faye Z.; Corona, Rosalie; Townsend, Tiffany G.

    2009-01-01

    This study sought to determine the relative contributions of individual, family, peer, and community risk and promotive factors in explaining alcohol and tobacco refusal attitudes among 227 African-American adolescents (ages 12 to 17) from urban and rural areas. Hierarchical linear regression (HLR) results revealed differences in the predictive…

  16. Information Technology, Mathematics Achievement and Educational Equity in Developed Economies

    ERIC Educational Resources Information Center

    Tan, Cheng Yong; Hew, Khe Foon

    2017-01-01

    The present study examined how access to home and school IT resources impacted student mathematics achievement. Data comprised 144,395 secondary school students from 7,308 schools in 22 developed economies who participated in the Programme for International Student Assessment (PISA) 2012. Results of hierarchical linear modelling showed that after…

  17. The Contributions of Teachers' Emotional Support to Children's Social Behaviors and Self-Regulatory Skills in First Grade

    ERIC Educational Resources Information Center

    Merritt, Eileen G.; Wanless, Shannon B.; Rimm-Kaufman, Sara E.; Cameron, Claire; Peugh, James L.

    2012-01-01

    The present observational study used hierarchical linear modeling to examine predictors of children's social and self-regulatory outcomes in first-grade classrooms. Specifically, goals were the following: (1) to explore relations between emotionally supportive teacher-child interactions and children's social behaviors (aggression with peers,…

  18. Perceived Family Resources Based on Number of Members with ADHD

    ERIC Educational Resources Information Center

    Corwin, Melinda; Mulsow, Miriam; Feng, Du

    2012-01-01

    Objective: This study examines how the number of family members with ADHD affects other family members' perceived resources. Method: A total of 40 adolescents diagnosed with ADHD and their mothers, fathers, and adolescent siblings living in the household participated. Hierarchical linear modeling was used to analyze family-level data from a total…

  19. A Multilevel Analysis of Phase II of the Louisiana School Effectiveness Study.

    ERIC Educational Resources Information Center

    Kennedy, Eugene; And Others

    This paper presents findings of a study that used conventional modeling strategies (student- and school-level) and a new multilevel modeling strategy, Hierarchical Linear Modeling, to investigate school effects on student-achievement outcomes for data collected as part of Phase 2 of the Louisiana School Effectiveness Study. The purpose was to…

  20. What Is the Relationship between Teacher Quality and Student Achievement? An Exploratory Study

    ERIC Educational Resources Information Center

    Stronge, James H.; Ward, Thomas J.; Tucker, Pamela D.; Hindman, Jennifer L.

    2007-01-01

    The major purpose of the study was to examine what constitutes effective teaching as defined by measured increases in student learning with a focus on the instructional behaviors and practices. Ordinary least squares (OLS) regression analyses and hierarchical linear modeling (HLM) were used to identify teacher effectiveness levels while…

  1. Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study

    ERIC Educational Resources Information Center

    Heyvaert, Mieke; Moeyaert, Mariola; Verkempynck, Paul; Van den Noortgate, Wim; Vervloet, Marlies; Ugille, Maaike; Onghena, Patrick

    2017-01-01

    This article reports on a Monte Carlo simulation study, evaluating two approaches for testing the intervention effect in replicated randomized AB designs: two-level hierarchical linear modeling (HLM) and using the additive method to combine randomization test "p" values (RTcombiP). Four factors were manipulated: mean intervention effect,…

  2. Hierarchical Bio-Inspired Cooperative Control for Nonlinear Dynamical Systems and Hardware Demonstration

    DTIC Science & Technology

    2013-04-03

    cooperative control, LEGO robotic testbed, non-linear dynamics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES...testbed The architecture of the LEGO robots (® LEGO is a trademark and/or copyright of the LEGO Group) used in tests were based off the quick-start

  3. An Investigation of Teacher Impact on Student Inquiry Science Performance Using a Hierarchical Linear Model

    ERIC Educational Resources Information Center

    Liu, Ou Lydia; Lee, Hee-Sun; Linn, Marcia C.

    2010-01-01

    Teachers play a central role in inquiry science classrooms. In this study, we investigate how seven teacher variables (i.e., gender, experience, perceived importance of inquiry and traditional teaching, workshop attendance, partner teacher, use of technology) affect student knowledge integration understanding of science topics drawing on previous…

  4. Outdoor Behavioral Health Care: Client and Treatment Characteristics Effects on Young Adult Outcomes

    ERIC Educational Resources Information Center

    Roberts, Sean D.; Stroud, Daniel; Hoag, Matthew J.; Combs, Katie M.

    2016-01-01

    A lack of clarity exists regarding how different clients respond to outdoor behavioral health care (OBH). In this study, specific client and treatment characteristics were assessed for 186 young adults completing an OBH therapeutic wilderness program. Clinical outcomes were measured with the Outcome Questionnaire-45.2. Hierarchical linear modeling…

  5. U. S. Fourth Graders' Informational Text Comprehension: Indicators from NAEP

    ERIC Educational Resources Information Center

    Schugar, Heather R.; Dreher, Miriam Jean

    2017-01-01

    This study is a secondary analysis of reading data collected from over 165,000 fourth graders as part of the U.S. National Assessment of Educational Progress. Using hierarchical linear modelling, the authors investigated factors associated with students' informational text comprehension, including out-of-school reading engagement, and in-school…

  6. Suppressor Variables and Multilevel Mixture Modelling

    ERIC Educational Resources Information Center

    Darmawan, I Gusti Ngurah; Keeves, John P.

    2006-01-01

    A major issue in educational research involves taking into consideration the multilevel nature of the data. Since the late 1980s, attempts have been made to model social science data that conform to a nested structure. Among other models, two-level structural equation modelling or two-level path modelling and hierarchical linear modelling are two…

  7. Community Context, Social Integration into Family, and Youth Violence

    ERIC Educational Resources Information Center

    Knoester, Chris; Haynie, Dana L.

    2005-01-01

    The purpose of this study is to analyze the extent to which neighborhood-level family structure and feelings of family integration are associated with acts of violence among 16,910 adolescents from the National Longitudinal Study of Adolescent Health. The results from our hierarchical linear models indicate that adolescents who live in…

  8. Does Mission Matter? An Analysis of Private School Achievement Differences

    ERIC Educational Resources Information Center

    Boerema, Albert J.

    2009-01-01

    Using student achievement data from British Columbia, Canada, this study is an exploration of the differences that lie within the private school sector using hierarchical linear modeling to analyze the data. The analysis showed that when controlling for language, parents' level of educational attainment, and prior achievement, the private school…

  9. The Role of Schools, Families, and Psychological Variables on Math Achievement of Black High School Students

    ERIC Educational Resources Information Center

    Strayhorn, Terrell L.

    2010-01-01

    Using data from the National Education Longitudinal Study (NELS;1988/2000), the author conducted hierarchical linear regression analyses, with a nested design, to estimate the influence of affective variables--parent involvement, teacher perceptions, and school environments--on Black students' math achievement in grade 10. Drawing on…

  10. A Cluster Analysis of Personality Style in Adults with ADHD

    ERIC Educational Resources Information Center

    Robin, Arthur L.; Tzelepis, Angela; Bedway, Marquita

    2008-01-01

    Objective: The purpose of this study was to use hierarchical linear cluster analysis to examine the normative personality styles of adults with ADHD. Method: A total of 311 adults with ADHD completed the Millon Index of Personality Styles, which consists of 24 scales assessing motivating aims, cognitive modes, and interpersonal behaviors. Results:…

  11. Racial Differences in Perceptions of Social Support in Consumer-Centered Services

    ERIC Educational Resources Information Center

    Woodward, Amanda Toler; Mowbray, Carol T.; Holter, Mark C.; Bybee, Deborah

    2007-01-01

    The purpose of this study was to explore potential racial differences in the experience of support offered by consumer-centered services for adults with serious mental illness. The study used hierarchical linear modeling to examine the level of support consumers report receiving from programs and the extent to which program-level characteristics…

  12. Student Engagement and Academic Performance in Mexico: Evidence and Puzzles from PISA

    ERIC Educational Resources Information Center

    Weiss, Christopher C.; García, Emma

    2015-01-01

    This paper investigates the relationship between student engagement--with teachers and schools--and academic performance in Mexico. It uses hierarchical linear models and data from the OECD 2003 PISA study to examine the relative importance of engagement in comparison to other educational inputs--school and family characteristics--as predictors of…

  13. Student Motivation in Low-Stakes Assessment Contexts: An Exploratory Analysis in Engineering Mechanics

    ERIC Educational Resources Information Center

    Musekamp, Frank; Pearce, Jacob

    2016-01-01

    The goal of this paper is to examine the relationship of student motivation and achievement in low-stakes assessment contexts. Using Pearson product-moment correlations and hierarchical linear regression modelling to analyse data on 794 tertiary students who undertook a low-stakes engineering mechanics assessment (along with the questionnaire of…

  14. Principals' Leadership Behaviors as Perceived by Teachers in At-Risk Middle Schools

    ERIC Educational Resources Information Center

    Johnson, R. Anthony

    2011-01-01

    A need for greater understanding of teachers' (N = 530) perceptions of the leadership behaviors of principals in Title I middle schools (n = 13) is prevalent exists. The researcher used the "Audit of Principal Effectiveness" survey to collect data. The researcher also used Hierarchical Linear Modeling as the quantitative analysis.…

  15. Family Structure States and Transitions: Associations with Children's Well-Being during Middle Childhood

    ERIC Educational Resources Information Center

    Magnuson, Katherine; Berger, Lawrence M.

    2009-01-01

    Using longitudinal data from the Maternal and Child Supplement of the National Longitudinal Survey of Youth (N = 3,862) and Hierarchical Linear Models, we estimated associations of family structure states and transitions with children's achievement and behavior trajectories during middle childhood. Results suggest that residing in a single-mother…

  16. A Multilevel Analysis of Gender Differences in Psychological Distress over Time

    ERIC Educational Resources Information Center

    Botticello, Amanda L.

    2009-01-01

    Females have higher rates of depression than males, a disparity that emerges in adolescence and persists into adulthood. This study uses hierarchical linear modeling to assess the effects of school context on gender differences in depressive symptoms among adolescents based on two waves of data from the National Longitudinal Study of Adolescent…

  17. Just Another Club? The Distinctiveness of the Relation between Religious Service Attendance and Adolescent Psychosocial Adjustment

    ERIC Educational Resources Information Center

    Good, Marie; Willoughby, Teena; Fritjers, Jan

    2009-01-01

    This study used hierarchical linear modeling to compare longitudinal patterns of adolescent religious service attendance and club attendance, and to contrast the longitudinal relations between adolescent adjustment and religious service versus club attendance. Participants included 1050 students (47% girls) encompassing a school district in…

  18. Falling Off Track: How Teacher-Student Relationships Predict Early High School Failure Rates.

    ERIC Educational Resources Information Center

    Miller, Shazia Rafiullah

    This paper examines the relationship between the climate of teacher-student relations within a school and individual student's likelihood of freshman year success. Using administrative data from the Chicago Public Schools and survey data, researchers used hierarchical linear modeling to determine whether teacher-student climate predicts students'…

  19. An International Meta-Analysis of Reading Recovery

    ERIC Educational Resources Information Center

    D'Agostino, Jerome V.; Harmey, Sinéad J.

    2016-01-01

    Reading Recovery is one of the most researched literacy programs worldwide. Although there have been at least 4 quantitative reviews of its effectiveness, none have considered all rigorous group-comparison studies from all implementing nations from the late 1970s to 2015. Using a hierarchical linear modeling (HLM) v-known analysis, we examined if…

  20. Bottom-Up Analysis of Single-Case Research Designs

    ERIC Educational Resources Information Center

    Parker, Richard I.; Vannest, Kimberly J.

    2012-01-01

    This paper defines and promotes the qualities of a "bottom-up" approach to single-case research (SCR) data analysis. Although "top-down" models, for example, multi-level or hierarchical linear models, are gaining momentum and have much to offer, interventionists should be cautious about analyses that are not easily understood, are not governed by…

  1. Student and School Factors Affecting Mathematics Achievement: International Comparisons between Korea, Japan and the USA

    ERIC Educational Resources Information Center

    Shin, Jongho; Lee, Hyunjoo; Kim, Yongnam

    2009-01-01

    The purpose of the study was to comparatively investigate student- and school-level factors affecting mathematics achievement of Korean, Japanese and American students. For international comparisons, the PISA 2003 data were analysed by using the Hierarchical Linear Modeling method. The variables of competitive-learning preference, instrumental…

  2. Assessment and Innovation: One Darn Thing Leads to Another

    ERIC Educational Resources Information Center

    Rutz, Carol; Lauer-Glebov, Jacqulyn

    2005-01-01

    Using recent experience at Carleton College in Minnesota as a case history, the authors offer a model for assessment that provides more flexibility than the well-known assessment feedback loop, which assumes a linear progression within a hierarchical administrative structure. The proposed model is based on a double helix, with values and feedback…

  3. The Relationship between School Collective Reflective Practice and Teacher Physiological Efficacy Sources

    ERIC Educational Resources Information Center

    Kennedy, Sheryl Y.; Smith, Julia B.

    2013-01-01

    This study used Hierarchical Linear Modeling to analyze the relationship between school organizational behaviors and practices (at the school level) on teachers' reports of internal and external physiological sources of efficacy. Six hundred sixty-one teachers from 42 schools in the United States were surveyed to measure both individual sources of…

  4. 3D deformable image matching: a hierarchical approach over nested subspaces

    NASA Astrophysics Data System (ADS)

    Musse, Olivier; Heitz, Fabrice; Armspach, Jean-Paul

    2000-06-01

    This paper presents a fast hierarchical method to perform dense deformable inter-subject matching of 3D MR Images of the brain. To recover the complex morphological variations in neuroanatomy, a hierarchy of 3D deformations fields is estimated, by minimizing a global energy function over a sequence of nested subspaces. The nested subspaces, generated from a single scaling function, consist of deformation fields constrained at different scales. The highly non linear energy function, describing the interactions between the target and the source images, is minimized using a coarse-to-fine continuation strategy over this hierarchy. The resulting deformable matching method shows low sensitivity to local minima and is able to track large non-linear deformations, with moderate computational load. The performances of the approach are assessed both on simulated 3D transformations and on a real data base of 3D brain MR Images from different individuals. The method has shown efficient in putting into correspondence the principle anatomical structures of the brain. An application to atlas-based MRI segmentation, by transporting a labeled segmentation map on patient data, is also presented.

  5. Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

    PubMed

    Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

    2014-07-01

    This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Hierarchical design of an electro-hydraulic actuator based on robust LPV methods

    NASA Astrophysics Data System (ADS)

    Németh, Balázs; Varga, Balázs; Gáspár, Péter

    2015-08-01

    The paper proposes a hierarchical control design of an electro-hydraulic actuator, which is used to improve the roll stability of vehicles. The purpose of the control system is to generate a reference torque, which is required by the vehicle dynamic control. The control-oriented model of the actuator is formulated in two subsystems. The high-level hydromotor is described in a linear form, while the low-level spool valve is a polynomial system. These subsystems require different control strategies. At the high level, a linear parameter-varying control is used to guarantee performance specifications. At the low level, a control Lyapunov-function-based algorithm, which creates discrete control input values of the valve, is proposed. The interaction between the two subsystems is guaranteed by the spool displacement, which is control input at the high level and must be tracked at the low-level control. The spool displacement has physical constraints, which must also be incorporated into the control design. The robust design of the high-level control incorporates the imprecision of the low-level control as an uncertainty of the system.

  7. Socioeconomic Status Is Not Related with Facial Fluctuating Asymmetry: Evidence from Latin-American Populations

    PubMed Central

    Quinto-Sánchez, Mirsha; Cintas, Celia; Silva de Cerqueira, Caio Cesar; Ramallo, Virginia; Acuña-Alonzo, Victor; Adhikari, Kaustubh; Castillo, Lucía; Gomez-Valdés, Jorge; Everardo, Paola; De Avila, Francisco; Hünemeier, Tábita; Jaramillo, Claudia; Arias, Williams; Fuentes, Macarena; Gallo, Carla; Poletti, Giovani; Schuler-Faccini, Lavinia; Bortolini, Maria Cátira; Canizales-Quinteros, Samuel; Rothhammer, Francisco; Bedoya, Gabriel; Rosique, Javier; Ruiz-Linares, Andrés; González-José, Rolando

    2017-01-01

    The expression of facial asymmetries has been recurrently related with poverty and/or disadvantaged socioeconomic status. Departing from the developmental instability theory, previous approaches attempted to test the statistical relationship between the stress experienced by individuals grown in poor conditions and an increase in facial and corporal asymmetry. Here we aim to further evaluate such hypothesis on a large sample of admixed Latin Americans individuals by exploring if low socioeconomic status individuals tend to exhibit greater facial fluctuating asymmetry values. To do so, we implement Procrustes analysis of variance and Hierarchical Linear Modelling (HLM) to estimate potential associations between facial fluctuating asymmetry values and socioeconomic status. We report significant relationships between facial fluctuating asymmetry values and age, sex, and genetic ancestry, while socioeconomic status failed to exhibit any strong statistical relationship with facial asymmetry. These results are persistent after the effect of heterozygosity (a proxy for genetic ancestry) is controlled in the model. Our results indicate that, at least on the studied sample, there is no relationship between socioeconomic stress (as intended as low socioeconomic status) and facial asymmetries. PMID:28060876

  8. An Efficient Multicore Implementation of a Novel HSS-Structured Multifrontal Solver Using Randomized Sampling

    DOE PAGES

    Ghysels, Pieter; Li, Xiaoye S.; Rouet, Francois -Henry; ...

    2016-10-27

    Here, we present a sparse linear system solver that is based on a multifrontal variant of Gaussian elimination and exploits low-rank approximation of the resulting dense frontal matrices. We use hierarchically semiseparable (HSS) matrices, which have low-rank off-diagonal blocks, to approximate the frontal matrices. For HSS matrix construction, a randomized sampling algorithm is used together with interpolative decompositions. The combination of the randomized compression with a fast ULV HSS factoriz ation leads to a solver with lower computational complexity than the standard multifrontal method for many applications, resulting in speedups up to 7 fold for problems in our test suite.more » The implementation targets many-core systems by using task parallelism with dynamic runtime scheduling. Numerical experiments show performance improvements over state-of-the-art sparse direct solvers. The implementation achieves high performance and good scalability on a range of modern shared memory parallel systems, including the Intel Xeon Phi (MIC). The code is part of a software package called STRUMPACK - STRUctured Matrices PACKage, which also has a distributed memory component for dense rank-structured matrices.« less

  9. "But it might be a heart attack": intolerance of uncertainty and panic disorder symptoms.

    PubMed

    Carleton, R Nicholas; Duranceau, Sophie; Freeston, Mark H; Boelen, Paul A; McCabe, Randi E; Antony, Martin M

    2014-06-01

    Panic disorder models describe interactions between feared anxiety-related physical sensations (i.e., anxiety sensitivity; AS) and catastrophic interpretations therein. Intolerance of uncertainty (IU) has been implicated as necessary for catastrophic interpretations in community samples. The current study examined relationships between IU, AS, and panic disorder symptoms in a clinical sample. Participants had a principal diagnosis of panic disorder, with or without agoraphobia (n=132; 66% women). IU was expected to account for significant variance in panic symptoms controlling for AS. AS was expected to mediate the relationship between IU and panic symptoms, whereas IU was expected to moderate the relationship between AS and panic symptoms. Hierarchical linear regressions indicated that IU accounted for significant unique variance in panic symptoms relative to AS, with comparable part correlations. Mediation and moderation models were also tested and suggested direct and indirect effects of IU on panic symptoms through AS; however, an interaction effect was not supported. The current cross-sectional evidence supports a role for IU in panic symptoms, independent of AS. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Personality predispositions to depression in children of affectively-ill parents: the buffering role of self-esteem.

    PubMed

    Abela, John R Z; Fishman, Michael B; Cohen, Joseph R; Young, Jami F

    2012-01-01

    A major theory of personality predispositions to depression posits that individuals who possess high levels of self-criticism and/or dependency are vulnerable to developing depression following negative life events. The goal of the current study was to test this theory of personality predispositions and the self-esteem buffering hypothesis in a sample of youth using an idiographic approach, a high-risk sample, and a multiwave longitudinal design. One hundred forty children aged 6 to 14 completed measures of dependency, self-criticism, self-esteem, and depressive symptoms. Over the course of the following year, 8 follow-up assessments were conducted 6 weeks apart during which all children were administered measures assessing depressive symptoms and the occurrence of negative events. Results of hierarchical linear modeling analyses indicated that higher levels of dependency were associated with greater increases in depressive symptoms following negative events among children possessing low, but not high, self-esteem. In contrast, self-criticism was not associated with changes in depressive symptoms over time regardless of children's levels of stress and/or self-esteem.

  11. Assessing the relationship between family mealtime communication and adolescent emotional well-being using the experience sampling method.

    PubMed

    Offer, Shira

    2013-06-01

    While most prior research has focused on the frequency of family meals the issue of which elements of family mealtime are most salient for adolescents' well-being has remained overlooked. The current study used the experience sampling method, a unique form of time diary, and survey data drawn from the 500 Family Study (N = 237 adolescents with 8122 observations) to examine the association between family mealtime communication and teens' emotional well-being. Results showed that in approximately half of the time spent on family meals (3 h per week on average) adolescents reported talking to their parents. Hierarchical linear model analyses revealed that controlling for the quality of family relationships family mealtime communication was significantly associated with higher positive affect and engagement and with lower negative affect and stress. Findings suggest that family meals constitute an important site for communication between teens and parents that is beneficial to adolescents' emotional well-being. Copyright © 2013 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  12. Trait impulsivity predicts D-KEFS tower test performance in university students.

    PubMed

    Lyvers, Michael; Basch, Vanessa; Duff, Helen; Edwards, Mark S

    2015-01-01

    The present study examined a widely used self-report index of trait impulsiveness in relation to performance on a well-known neuropsychological executive function test in 70 university undergraduate students (50 women, 20 men) aged 18 to 24 years old. Participants completed the Barratt Impulsiveness Scale (BIS-11) and the Frontal Systems Behavior Scale (FrSBe), after which they performed the Tower Test of the Delis-Kaplan Executive Function System. Hierarchical linear regression showed that after controlling for gender, current alcohol consumption, age at onset of weekly alcohol use, and FrSBe scores, BIS-11 significantly predicted Tower Test Achievement scores, β = -.44, p < .01. The results indicate that self-reported impulsiveness is associated with poorer executive cognitive performance even in a sample likely to be characterized by relatively high general cognitive functioning (i.e., university students). The results also support the role of inhibition as a key aspect of executive task performance. Elevated scores on the BIS-11 and FrSBe are known to be linked to risky drinking in young adults as confirmed in this sample; however, only BIS-11 predicted Tower Test performance.

  13. Socioeconomic Status Is Not Related with Facial Fluctuating Asymmetry: Evidence from Latin-American Populations.

    PubMed

    Quinto-Sánchez, Mirsha; Cintas, Celia; Silva de Cerqueira, Caio Cesar; Ramallo, Virginia; Acuña-Alonzo, Victor; Adhikari, Kaustubh; Castillo, Lucía; Gomez-Valdés, Jorge; Everardo, Paola; De Avila, Francisco; Hünemeier, Tábita; Jaramillo, Claudia; Arias, Williams; Fuentes, Macarena; Gallo, Carla; Poletti, Giovani; Schuler-Faccini, Lavinia; Bortolini, Maria Cátira; Canizales-Quinteros, Samuel; Rothhammer, Francisco; Bedoya, Gabriel; Rosique, Javier; Ruiz-Linares, Andrés; González-José, Rolando

    2017-01-01

    The expression of facial asymmetries has been recurrently related with poverty and/or disadvantaged socioeconomic status. Departing from the developmental instability theory, previous approaches attempted to test the statistical relationship between the stress experienced by individuals grown in poor conditions and an increase in facial and corporal asymmetry. Here we aim to further evaluate such hypothesis on a large sample of admixed Latin Americans individuals by exploring if low socioeconomic status individuals tend to exhibit greater facial fluctuating asymmetry values. To do so, we implement Procrustes analysis of variance and Hierarchical Linear Modelling (HLM) to estimate potential associations between facial fluctuating asymmetry values and socioeconomic status. We report significant relationships between facial fluctuating asymmetry values and age, sex, and genetic ancestry, while socioeconomic status failed to exhibit any strong statistical relationship with facial asymmetry. These results are persistent after the effect of heterozygosity (a proxy for genetic ancestry) is controlled in the model. Our results indicate that, at least on the studied sample, there is no relationship between socioeconomic stress (as intended as low socioeconomic status) and facial asymmetries.

  14. Prevalence and Severity of Dementia in Nursing Home Residents.

    PubMed

    Helvik, Anne-Sofie; Engedal, Knut; Benth, Jūratė Šaltytė; Selbæk, Geir

    2015-01-01

    The aim of this study was to compare the presence and severity of dementia in two large cross-sectional samples of nursing home residents from 2004/2005 and 2010/2011. Demographic information as well as data on the type of nursing home unit, length of stay before assessment, physical health, regularly used prescribed drugs and Clinical Dementia Rating scale scores were used in the analyses. Logistic and linear regression models for hierarchical data were estimated. The odds of the occurrence and of a greater severity of dementia were higher in 2010/2011 than in 2004/2005. Independent of the time of study, married men had more severe dementia than single men, and single women had more severe dementia than single men. The findings may reflect the increase in the need for more nursing home beds designed for people with dementia between 2004/2005 and 2010/2011. © 2015 S. Karger AG, Basel.

  15. Understanding the positive role of neighborhood socioeconomic advantage in achievement: the contribution of the home, child care, and school environments.

    PubMed

    Dupere, Veronique; Leventhal, Tama; Crosnoe, Robert; Dion, Eric

    2010-09-01

    The goal of this study was to examine the mechanisms underlying associations between neighborhood socioeconomic advantage and children's achievement trajectories between ages 54 months and 15 years. Results of hierarchical linear growth models based on a diverse sample of 1,364 children indicate that neighborhood socioeconomic advantage was nonlinearly associated with youths' initial vocabulary and reading scores, such that the presence of educated, affluent professionals in the neighborhood had a favorable association with children's achievement among those in less advantaged neighborhoods until it leveled off at moderate levels of advantage. A similar tendency was observed for math achievement. The quality of the home and child care environments as well as school advantage partially explained these associations. The findings suggest that multiple environments need to be considered simultaneously for understanding neighborhood-achievement links.

  16. Four-factor justice and daily job satisfaction: a multilevel investigation.

    PubMed

    Loi, Raymond; Yang, Jixia; Diefendorff, James M

    2009-05-01

    This study examined the differential effects of 4 types of organizational justice on daily job satisfaction at between- and within-individual levels. Specifically, the authors predicted that interpersonal justice and informational justice would exhibit meaningful daily variations and would have direct impacts on individuals' job satisfaction on a daily basis. They further theorized that distributive justice and procedural justice at a between-person level would moderate the within-person relationships. The authors used hierarchical linear modeling to test their hypotheses with a sample of 231 full-time employees in Hong Kong over the course of 25 working days. The results showed that both daily interpersonal and informational justice were positively related to daily job satisfaction. As hypothesized, between-individual distributive justice moderated the relationship between daily interpersonal justice and daily job satisfaction, and between-individual procedural justice moderated the relationship between daily informational justice and daily job satisfaction. (c) 2009 APA, all rights reserved.

  17. ‘Weakest Link’ as a Cognitive Vulnerability Within the Hopelessness Theory of Depression in Chinese University Students

    PubMed Central

    Xiao, Jing; Qiu, Yu; He, Yini; Cui, Lixia; Auerbach, Randy P.; McWhinnie, Chad M.; Yao, Shuqiao

    2015-01-01

    The current study tested the cognitive vulnerability–stress component of hopelessness theory using a ‘weakest link’ approach (e.g. an individual is as cognitively vulnerable to depression as his or her most depressogenic attributional style makes him or her) in a sample of Chinese university students. Participants included 520 students in Changsha. During an initial assessment, participants completed measures assessing weakest link, depressive symptoms and occurrence of negative events once a month for 6 months. Results from hierarchical linear modelling analyses showed that higher levels of weakest link scores were associated with greater increases in depressive symptoms following the occurrence of negative events. Higher weakest link level was associated with greater increases in depressive symptoms over time. These results provide support for the applicability of the ‘weakest link’ approach to the hopelessness theory to Chinese university students. PMID:24639362

  18. 'Weakest Link' as a Cognitive Vulnerability Within the Hopelessness Theory of Depression in Chinese University Students.

    PubMed

    Xiao, Jing; Qiu, Yu; He, Yini; Cui, Lixia; Auerbach, Randy P; McWhinnie, Chad M; Yao, Shuqiao

    2016-02-01

    The current study tested the cognitive vulnerability-stress component of hopelessness theory using a 'weakest link' approach (e.g. an individual is as cognitively vulnerable to depression as his or her most depressogenic attributional style makes him or her) in a sample of Chinese university students. Participants included 520 students in Changsha. During an initial assessment, participants completed measures assessing weakest link, depressive symptoms and occurrence of negative events once a month for 6 months. Results from hierarchical linear modelling analyses showed that higher levels of weakest link scores were associated with greater increases in depressive symptoms following the occurrence of negative events. Higher weakest link level was associated with greater increases in depressive symptoms over time. These results provide support for the applicability of the 'weakest link' approach to the hopelessness theory to Chinese university students. Copyright © 2014 John Wiley & Sons, Ltd.

  19. New Parents’ Psychological Adjustment and Trajectories of Early Parental Involvement

    PubMed Central

    Jia, Rongfang; Kotila, Letitia E.; Schoppe-Sullivan, Sarah J.; Kamp Dush, Claire M.

    2016-01-01

    Trajectories of parental involvement time (engagement and child care) across 3, 6, and 9 months postpartum and associations with parents’ own and their partners’ psychological adjustment (dysphoria, anxiety, and empathic personal distress) were examined using a sample of dual-earner couples experiencing first-time parenthood (N = 182 couples). Using time diary measures that captured intensive parenting moments, hierarchical linear modeling analyses revealed that patterns of associations between psychological adjustment and parental involvement time depended on the parenting domain, aspect of psychological adjustment, and parent gender. Psychological adjustment difficulties tended to bias the 2-parent system toward a gendered pattern of “mother step in” and “father step out,” as father involvement tended to decrease, and mother involvement either remained unchanged or increased, in response to their own and their partners’ psychological adjustment difficulties. In contrast, few significant effects were found in models using parental involvement to predict psychological adjustment. PMID:27397935

  20. LGBT-Competence in Social Work Education: The Relationship of School Contexts to Student Sexual Minority Competence.

    PubMed

    McCarty-Caplan, David

    2018-01-01

    This study examined the relationship between master of social work programs' (MSW) support of lesbian, gay, bisexual, and transgender people (LGBT-competence) and the sexual minority competence (LGB-competence) of social work students. Data were gathered from a sample of MSW program directors, faculty members, and students (N = 1385) within 34 MSW programs in the United States. A series of hierarchical linear models tested if a MSW program's LGBT-competence was associated with the LGB-competence of its students. Results showed a significant relationship between organizational LGBT-competence and individual LGB-competence within schools of social work, and that programs with greater LGBT-competence also had students who felt more competent to work with sexual minorities. These findings suggest schools of social work can take substantive action at an organizational level to improve the professional LGB-competence of future social workers. Implications for social work education are discussed.

  1. Feedback Seeking in Early Adolescence: Self-Enhancement or Self-Verification?

    PubMed

    Rosen, Lisa H; Principe, Connor P; Langlois, Judith H

    2013-02-13

    The authors examined whether early adolescents ( N = 90) solicit self-enhancing feedback (i.e., positive feedback) or self-verifying feedback (i.e., feedback congruent with self-views, even when these views are negative). Sixth, seventh, and eighth graders first completed a self-perception measure and then selected whether to receive positive or negative feedback from an unknown peer in different domains of self. Results were consistent with self-verification theory; adolescents who perceived themselves as having both strengths and weaknesses were more likely to seek negative feedback regarding a self-perceived weakness compared to a self-perceived strength. The authors found similar support for self-verification processes when they considered the entire sample regardless of perceived strengths and weaknesses; hierarchical linear modeling (HLM) examined the predictive power of ratings of self-perceived ability, certainty, and importance on feedback seeking for all participants and provided additional evidence of self-verification strivings in adolescence.

  2. Feedback Seeking in Early Adolescence: Self-Enhancement or Self-Verification?

    PubMed Central

    Rosen, Lisa H.; Principe, Connor P.; Langlois, Judith H.

    2012-01-01

    The authors examined whether early adolescents (N = 90) solicit self-enhancing feedback (i.e., positive feedback) or self-verifying feedback (i.e., feedback congruent with self-views, even when these views are negative). Sixth, seventh, and eighth graders first completed a self-perception measure and then selected whether to receive positive or negative feedback from an unknown peer in different domains of self. Results were consistent with self-verification theory; adolescents who perceived themselves as having both strengths and weaknesses were more likely to seek negative feedback regarding a self-perceived weakness compared to a self-perceived strength. The authors found similar support for self-verification processes when they considered the entire sample regardless of perceived strengths and weaknesses; hierarchical linear modeling (HLM) examined the predictive power of ratings of self-perceived ability, certainty, and importance on feedback seeking for all participants and provided additional evidence of self-verification strivings in adolescence. PMID:23543746

  3. Sense of community in Hong Kong: relations with community-level characteristics and residents' well-being.

    PubMed

    Mak, Winnie W S; Cheung, Rebecca Y M; Law, Lawrence S C

    2009-09-01

    Sense of community (SOC) has been one of the most studied topics in community psychology. However, no empirical study to date has investigated SOC in Hong Kong and its relations with community characteristics and residents' psychological well-being. A representative sample of 941 Hong Kong Chinese based on a randomized household survey was conducted in all 18 districts in Hong Kong. Results of hierarchical linear modeling indicated that SOC was not associated with sociodemographic indicators on both the individual-level (i.e., gender, age, family income, education level, type of residence, and area-to-capita ratio of residence) and the community-level (i.e., proportion of individuals with tertiary education, median family income, ownership of residence, population density, and resident stability). SOC was negatively related to daily hassles and positively with social support and quality of life. Conceptualization of SOC in Hong Kong was discussed.

  4. Father and adolescent son variables related to son's HIV prevention.

    PubMed

    Glenn, Betty L; Demi, Alice; Kimble, Laura P

    2008-02-01

    The purpose of this study was to examine the relationship between fathers' influences and African American male adolescents' perceptions of self-efficacy to reduce high-risk sexual behavior. A convenience sample of 70 fathers was recruited from churches in a large metropolitan area in the South. Hierarchical multiple linear regression analysis indicated father-related factors and son-related factors were associated with 26.1% of the variance in son's self-efficacy to be abstinent. In the regression model greater son's perception of the communication of sexual standards and greater father's perception of his son's self-efficacy were significantly related to greater son's self-efficacy for abstinence. The second regression model with son's self-efficacy for safer sex as the criterion was not statistically significant. Data support the need for fathers to express confidence in their sons' ability to be abstinent or practice safer sex and to communicate with their sons regarding sexual issues and standards.

  5. Racial identity and academic achievement in the neighborhood context: a multilevel analysis.

    PubMed

    Byrd, Christy M; Chavous, Tabbye M

    2009-04-01

    Increasingly, researchers have found relationships between a strong, positive sense of racial identity and academic achievement among African American youth. Less attention, however, has been given to the roles and functions of racial identity among youth experiencing different social and economic contexts. Using hierarchical linear modeling, the authors examined the relationship of racial identity to academic outcomes, taking into account neighborhood-level factors. The sample consisted of 564 African American eighth-graders (56% male). The authors found that neighborhood characteristics and racial identity related positively to academic outcomes, but that some relationships were different across neighborhood types. For instance, in neighborhoods low in economic opportunity, high pride was associated with a higher GPA, but in more advantaged neighborhoods, high pride was associated with a lower GPA. The authors discuss the need to take youth's contexts into account in order to understand how racial identity is active in the lives of African American youth.

  6. Two-year predictors of runaway and homeless episodes following shelter services among substance abusing adolescents.

    PubMed

    Slesnick, Natasha; Guo, Xiamei; Brakenhoff, Brittany; Feng, Xin

    2013-10-01

    Given high levels of health and psychological costs associated with the family disruption of homelessness, identifying predictors of runaway and homeless episodes is an important goal. The current study followed 179 substance abusing, shelter-recruited adolescents who participated in a randomized clinical trial. Predictors of runaway and homeless episodes were examined over a two year period. Results from the hierarchical linear modeling analysis showed that family cohesion and substance use, but not family conflict or depressive symptoms, delinquency, or school enrollment predicted future runaway and homeless episodes. Findings suggest that increasing family support, care and connection and reducing substance use are important targets of intervention efforts in preventing future runaway and homeless episodes amongst a high risk sample of adolescents. Copyright © 2013 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  7. An examination of the role of perceived support and employee commitment in employee-customer encounters.

    PubMed

    Vandenberghe, Christian; Bentein, Kathleen; Michon, Richard; Chebat, Jean-Charles; Tremblay, Michel; Fils, Jean-François

    2007-07-01

    The authors examined the relationships between perceived organizational support, organizational commitment, commitment to customers, and service quality in a fast-food firm. The research design matched customer responses with individual employees' attitudes, making this study a true test of the service provider-customer encounter. On the basis of a sample of matched employee-customer data (N = 133), hierarchical linear modeling analyses revealed that perceived organizational support had both a unit-level and an employee-level effect on 1 dimension of service quality: helping behavior. Contrary to affective organizational commitment, affective commitment to customers enhanced service quality. The 2 sub-dimensions of continuance commitment to the organization--perceived high sacrifice and perceived lack of alternatives--exerted effects opposite in sign: The former fostered service quality, whereas the latter reduced it. The implications of these findings are discussed within the context of research on employee-customer encounters.

  8. Social ecology of child soldiers: child, family, and community determinants of mental health, psychosocial well-being, and reintegration in Nepal.

    PubMed

    Kohrt, Brandon A; Jordans, Mark J D; Tol, Wietse A; Perera, Em; Karki, Rohit; Koirala, Suraj; Upadhaya, Nawaraj

    2010-11-01

    This study employed a social ecology framework to evaluate psychosocial well-being in a cross-sectional sample of 142 former child soldiers in Nepal. Outcome measures included the Depression Self Rating Scale (DSRS), Child Posttraumatic Stress Disorder Symptom Scale (CPSS), and locally developed measures of functional impairment and reintegration. Hierarchical linear modeling was used to examine the contribution of factors at multiple levels. At the child level, traumatic exposures, especially torture, predicted poor outcomes, while education improved outcomes. At the family level, conflict-related death of a relative, physical abuse in the household, and loss of wealth during the conflict predicted poor outcomes. At the community level, living in high caste Hindu communities predicted lack of reintegration supports. Ultimately, social ecology is well suited to identify intervention foci across ecological levels based on community differences in vulnerability and protective factors.

  9. A pilot examination of social context and everyday physical activity among adults receiving Community Mental Health Services.

    PubMed

    McCormick, B P; Frey, G C; Lee, C-T; Gajic, T; Stamatovic-Gajic, B; Maksimovic, M

    2009-03-01

    Community mental health center (CMHC) clients include a variety of people with moderate to severe mental illnesses who also report a number of physical health problems. Physical activity (PA) has been identified as one intervention to improve health among this population; however, little is known about the role of social context in PA. The purpose of this study was to examine the role of social context in everyday PA among CMHC clients. Data were collected from CMHC clients in two cultures using accelerometery and experience sampling methods. Data were analyzed using hierarchical linear modeling. Independence in housing nor culture was significantly associated with levels of PA. Being alone was significantly negatively related to PA level. Social isolation appears to be negatively related to PA at the level of everyday life. Physical activity interventions with this population should consider including social components as a part of PA.

  10. Adolescents' as active agents in the socialization process: legitimacy of parental authority and obligation to obey as predictors of obedience.

    PubMed

    Darling, Nancy; Cumsille, Patricio; Martínez, M Loreto

    2007-04-01

    Adolescents' agreement with parental standards and beliefs about the legitimacy of parental authority and their own obligation to obey were used to predict adolescents' obedience, controlling for parental monitoring, rules, and rule enforcement. Hierarchical linear models were used to predict both between-adolescent and within-adolescent, issue-specific differences in obedience in a sample of 703 Chilean adolescents (M age=15.0 years). Adolescents' global agreement with parents and global beliefs about their obligation to obey predicted between-adolescent obedience, controlling for parental monitoring, age, and gender. Adolescents' issue-specific agreement, legitimacy beliefs, and obligation to obey predicted issue-specific obedience, controlling for rules and parents' reports of rule enforcement. The potential of examining adolescents' agreement and beliefs about authority as a key link between parenting practices and adolescents' decisions to obey is discussed.

  11. Marital Status as a Moderating Factor in the Process of Disablement.

    PubMed

    Kail, Ben Lennox

    2016-02-01

    To test current marital status as a moderator on the influence of depressive symptoms and chronic conditions on subsequent functional limitations. Data come from the Health and Retirement Study (HRS; 1998-2010). Hierarchal linear modeling models tested differences in functional limitations among a sample of 20,215 people. At baseline, married people suffered from fewer subsequent functional limitations than the unmarried. Moreover, limited evidence suggests the influence of depressive symptoms was greater for the married than the unmarried; however, the influence of chronic conditions was consistently attenuated for married people. Accounting for differences in prior health, work, socioeconomic status, and health behaviors did not explain the moderating influence of marital status on the associations between symptoms of depression and chronic conditions with functional limitations. This research highlights the need to identify potential modifiers that may help disrupt the process of disablement among both the married and the unmarried alike. © The Author(s) 2015.

  12. Poverty and involuntary engagement stress responses: examining the link to anxiety and aggression within low-income families.

    PubMed

    Wolff, Brian C; Santiago, Catherine DeCarlo; Wadsworth, Martha E

    2009-05-01

    Families living with the burdens of poverty-related stress are at risk for developing a range of psychopathology. The present study examines the year-long prospective relationships among poverty-related stress, involuntary engagement stress response (IESR) levels, and anxiety symptoms and aggression in an ethnically diverse sample of 98 families (300 individual family members) living at or below 150% of the US federal poverty line. Hierarchical Linear Modeling (HLM) moderator model analyses provided strong evidence that IESR levels moderated the influence of poverty-related stress on anxiety symptoms and provided mixed evidence for the same interaction effect on aggression. Higher IESR levels, a proxy for physiological stress reactivity, worsened the impact of stress on symptoms. Understanding how poverty-related stress and involuntary stress responses affect psychological functioning has implications for efforts to prevent or reduce psychopathology, particularly anxiety, among individuals and families living in poverty.

  13. Testing the adaptation to poverty-related stress model: predicting psychopathology symptoms in families facing economic hardship.

    PubMed

    Wadsworth, Martha E; Raviv, Tali; Santiago, Catherine Decarlo; Etter, Erica M

    2011-01-01

    This study tested the Adaptation to Poverty-related Stress Model and its proposed relations between poverty-related stress, effortful and involuntary stress responses, and symptoms of psychopathology in an ethnically diverse sample of low-income children and their parents. Prospective Hierarchical Linear Modeling analyses conducted with 98 families (300 family members: 136 adults, 82 adolescents and preadolescents, 82 school-age children) revealed that, consistent with the model, primary and secondary control coping were protective against poverty-related stress primarily for internalizing symptoms. Conversely, disengagement coping exacerbated externalizing symptoms over time. In addition, involuntary engagement stress responses exacerbated the effects of poverty-related stress for internalizing symptoms, whereas involuntary disengagement responses exacerbated externalizing symptoms. Age and gender effects were found in most models, reflecting more symptoms of both types for parents than children and higher levels of internalizing symptoms for girls.

  14. Can the Arts Get Under the Skin? Arts and Cortisol for Economically Disadvantaged Children.

    PubMed

    Brown, Eleanor D; Garnett, Mallory L; Anderson, Kate E; Laurenceau, Jean-Philippe

    2017-07-01

    This within-subjects experimental study investigated the influence of the arts on cortisol for economically disadvantaged children. Participants were 310 children, ages 3-5 years, who attended a Head Start preschool and were randomly assigned to participate in different schedules of arts and homeroom classes on different days of the week. Cortisol was sampled at morning baseline and after arts and homeroom classes on two different days at start, middle, and end of the year. For music, dance, and visual arts, grouped and separately, results of piecewise hierarchical linear modeling with time-varying predictors suggested cortisol was lower after an arts versus homeroom class at middle and end of the year but not start of the year. Implications concern the impact of arts on cortisol for children facing poverty risks. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

  15. Direct and contextual effects of individual values on organizational citizenship behavior in teams.

    PubMed

    Arthaud-Day, Marne L; Rode, Joseph C; Turnley, William H

    2012-07-01

    The authors use Schwartz's values theory as an integrative framework for testing the relationship between individual values and peer-reported organizational citizenship behavior (OCB) in teams, controlling for sex, satisfaction, and personality traits. Using hierarchical linear modeling in a sample of 582 students distributed across 135 class project teams, the authors find positive, direct effects for achievement on citizenship behaviors directed toward individuals (OCB-I), for benevolence on citizenship behaviors directed toward the group (OCB-O), and for self-direction on both OCB-I and OCB-O. Applying relational demography techniques to test for contextual effects, the authors find that group mean power scores negatively moderate the relationship between individual power and OCB-I, whereas group mean self-direction scores positively moderate the relationship between self-direction and both OCB-I and OCB-O. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

  16. Evaluation of the environmental contamination at an abandoned mining site using multivariate statistical techniques--the Rodalquilar (Southern Spain) mining district.

    PubMed

    Bagur, M G; Morales, S; López-Chicano, M

    2009-11-15

    Unsupervised and supervised pattern recognition techniques such as hierarchical cluster analysis, principal component analysis, factor analysis and linear discriminant analysis have been applied to water samples recollected in Rodalquilar mining district (Southern Spain) in order to identify different sources of environmental pollution caused by the abandoned mining industry. The effect of the mining activity on waters was monitored determining the concentration of eleven elements (Mn, Ba, Co, Cu, Zn, As, Cd, Sb, Hg, Au and Pb) by inductively coupled plasma mass spectrometry (ICP-MS). The Box-Cox transformation has been used to transform the data set in normal form in order to minimize the non-normal distribution of the geochemical data. The environmental impact is affected mainly by the mining activity developed in the zone, the acid drainage and finally by the chemical treatment used for the benefit of gold.

  17. Hierarchical Structure of the Eysenck Personality Inventory in a Large Population Sample: Goldberg's Trait-Tier Mapping Procedure

    PubMed Central

    Chapman, Benjamin P.; Weiss, Alexander; Barrett, Paul; Duberstein, Paul

    2014-01-01

    The structure of the Eysenck Personality Inventory (EPI) is poorly understood, and applications have mostly been confined to the broad Neuroticism, Extraversion, and Lie scales. Using a hierarchical factoring procedure, we mapped the sequential differentiation of EPI scales from broad, molar factors to more specific, molecular factors, in a UK population sample of over 6500 persons. Replicable facets at the lowest tier of Neuroticism included emotional fragility, mood lability, nervous tension, and rumination. The lowest order set of replicable Extraversion facets consisted of social dynamism, sociotropy, decisiveness, jocularity, social information seeking, and impulsivity. The Lie scale consisted of an interpersonal virtue and a behavioral diligence facet. Users of the EPI may be well served in some circumstances by considering its broad Neuroticism, Extraversion, and Lie scales as multifactorial, a feature that was explicitly incorporated into subsequent Eysenck inventories and is consistent with other hierarchical trait structures. PMID:25983361

  18. Association between surgeon volume and hospitalisation costs for patients with oral cancer: a nationwide population base study in Taiwan.

    PubMed

    Lee, C-C; Ho, H-C; Jack, Lee C-C; Su, Y-C; Lee, M-S; Hung, S-K; Chou, Pesus

    2010-02-01

    Oral cancer leads to a considerable use of and expenditure on health care. Wide resection of the tumour and reconstruction with a pedicle flap/free flap is widely used. This study was conducted to explore the relationship between hospitalisation costs and surgeon case volume when this operation was performed. A population-based study. This study uses data for the years 2005-2006 obtained from the National Health Insurance Research Database published in the Taiwanese National Health Research Institute. From this population-based data, the authors selected a total of 2663 oral cancer patients who underwent tumour resection and reconstruction. Case volume relationships were based on the following criteria; low-, medium-, high-, very high-volume surgeons were defined by or= 56 resections with reconstruction, respectively. Hierarchical linear regression analysis was subsequently performed to explore the relationship between surgeon case volume and the cost and length of hospitalisation. The mean hospitalisation cost among the 2663 patients was US$ 9528 (all costs are given in US dollars). After adjusting for physician, hospital, and patient characteristics in a hierarchical linear regression model, the cost per patient for low-volume surgeons was found to be US$ 741 (P = 0.012) higher than that for medium-volume surgeons, US$ 1546 (P < 0.001) higher than that for high-volume surgeons, and US$ 1820 (P < 0.001) higher than that for very-high-volume surgeons. After adjustment for physician, hospital, and patient characteristics, the hierarchical linear regression model revealed that the mean length of stay per patient for low-volume surgeons was the highest (P < 0.001). After adjustment for physician, hospital, and patient characteristics, low-volume surgeons performing wide excision with reconstructive surgery in oral cancer patients incurred significantly higher costs and longer hospital stays per patient than did other surgeons. Treatment strategies adopted by high- and very-high-volume surgeons should be analysed further and utilised more widely.

  19. On the use of a PM2.5 exposure simulator to explain birthweight

    PubMed Central

    Berrocal, Veronica J.; Gelfand, Alan E.; Holland, David M.; Burke, Janet; Miranda, Marie Lynn

    2010-01-01

    In relating pollution to birth outcomes, maternal exposure has usually been described using monitoring data. Such characterization provides a misrepresentation of exposure as it (i) does not take into account the spatial misalignment between an individual’s residence and monitoring sites, and (ii) it ignores the fact that individuals spend most of their time indoors and typically in more than one location. In this paper, we break with previous studies by using a stochastic simulator to describe personal exposure (to particulate matter) and then relate simulated exposures at the individual level to the health outcome (birthweight) rather than aggregating to a selected spatial unit. We propose a hierarchical model that, at the first stage, specifies a linear relationship between birthweight and personal exposure, adjusting for individual risk factors and introduces random spatial effects for the census tract of maternal residence. At the second stage, our hierarchical model specifies the distribution of each individual’s personal exposure using the empirical distribution yielded by the stochastic simulator as well as a model for the spatial random effects. We have applied our framework to analyze birthweight data from 14 counties in North Carolina in years 2001 and 2002. We investigate whether there are certain aspects and time windows of exposure that are more detrimental to birthweight by building different exposure metrics which we incorporate, one by one, in our hierarchical model. To assess the difference in relating ambient exposure to birthweight versus personal exposure to birthweight, we compare estimates of the effect of air pollution obtained from hierarchical models that linearly relate ambient exposure and birthweight versus those obtained from our modeling framework. Our analysis does not show a significant effect of PM2.5 on birthweight for reasons which we discuss. However, our modeling framework serves as a template for analyzing the relationship between personal exposure and longer term health endpoints. PMID:21691413

  20. Linear scaling computation of the Fock matrix. VI. Data parallel computation of the exchange-correlation matrix

    NASA Astrophysics Data System (ADS)

    Gan, Chee Kwan; Challacombe, Matt

    2003-05-01

    Recently, early onset linear scaling computation of the exchange-correlation matrix has been achieved using hierarchical cubature [J. Chem. Phys. 113, 10037 (2000)]. Hierarchical cubature differs from other methods in that the integration grid is adaptive and purely Cartesian, which allows for a straightforward domain decomposition in parallel computations; the volume enclosing the entire grid may be simply divided into a number of nonoverlapping boxes. In our data parallel approach, each box requires only a fraction of the total density to perform the necessary numerical integrations due to the finite extent of Gaussian-orbital basis sets. This inherent data locality may be exploited to reduce communications between processors as well as to avoid memory and copy overheads associated with data replication. Although the hierarchical cubature grid is Cartesian, naive boxing leads to irregular work loads due to strong spatial variations of the grid and the electron density. In this paper we describe equal time partitioning, which employs time measurement of the smallest sub-volumes (corresponding to the primitive cubature rule) to load balance grid-work for the next self-consistent-field iteration. After start-up from a heuristic center of mass partitioning, equal time partitioning exploits smooth variation of the density and grid between iterations to achieve load balance. With the 3-21G basis set and a medium quality grid, equal time partitioning applied to taxol (62 heavy atoms) attained a speedup of 61 out of 64 processors, while for a 110 molecule water cluster at standard density it achieved a speedup of 113 out of 128. The efficiency of equal time partitioning applied to hierarchical cubature improves as the grid work per processor increases. With a fine grid and the 6-311G(df,p) basis set, calculations on the 26 atom molecule α-pinene achieved a parallel efficiency better than 99% with 64 processors. For more coarse grained calculations, superlinear speedups are found to result from reduced computational complexity associated with data parallelism.

  1. Quality evaluation of Shenmaidihuang Pills based on the chromatographic fingerprints and simultaneous determination of seven bioactive constituents.

    PubMed

    Liu, Sifei; Zhang, Guangrui; Qiu, Ying; Wang, Xiaobo; Guo, Lihan; Zhao, Yanxin; Tong, Meng; Wei, Lan; Sun, Lixin

    2016-12-01

    In this study, we aimed to establish a comprehensive and practical quality evaluation system for Shenmaidihuang pills. A simple and reliable high-performance liquid chromatography coupled with photodiode array detection method was developed both for fingerprint analysis and quantitative determination. In fingerprint analysis, relative retention time and relative peak area were used to identify the common peaks in 18 samples for investigation. Twenty one peaks were selected as the common peaks to evaluate the similarities of 18 Shenmaidihuang pills samples with different manufacture dates. Furthermore, similarity analysis was applied to evaluate the similarity of samples. Hierarchical cluster analysis and principal component analysis were also performed to evaluate the variation of Shenmaidihuang pills. In quantitative analysis, linear regressions, injection precisions, recovery, repeatability and sample stability were all tested and good results were obtained to simultaneously determine the seven identified compounds, namely, 5-hydroxymethylfurfural, morroniside, loganin, paeonol, paeoniflorin, psoralen, isopsoralen in Shenmaidihuang pills. The contents of some analytes in different batches of samples indicated significant difference, especially for 5-hydroxymethylfurfural. So, it was concluded that the chromatographic fingerprint method obtained by high-performance liquid chromatography coupled with photodiode array detection associated with multiple compounds determination is a powerful and meaningful tool to comprehensively conduct the quality control of Shenmaidihuang pills. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

    NASA Technical Reports Server (NTRS)

    Hoover, Richard B.; Storrie-Lombardi, Michael C.

    2004-01-01

    Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

  3. Starting Out: A time-lagged study of new graduate nurses' transition to practice.

    PubMed

    Laschinger, Heather K Spence; Cummings, Greta; Leiter, Michael; Wong, Carol; MacPhee, Maura; Ritchie, Judith; Wolff, Angela; Regan, Sandra; Rhéaume-Brüning, Ann; Jeffs, Lianne; Young-Ritchie, Carol; Grinspun, Doris; Gurnham, Mary Ellen; Foster, Barbara; Huckstep, Sherri; Ruffolo, Maurio; Shamian, Judith; Burkoski, Vanessa; Wood, Kevin; Read, Emily

    2016-05-01

    As the nursing profession ages, new graduate nurses are an invaluable health human resource. The purpose of this study was to investigate factors influencing new graduate nurses' successful transition to their full professional role in Canadian hospital settings and to determine predictors of job and career satisfaction and turnover intentions over a one-year time period in their early employment. A national two-wave survey of new graduate nurses across Canada. A random sample of 3906 Registered Nurses with less than 3 years of experience currently working in direct patient care was obtained from the provincial registry databases across Canada. At Time 1, 1020 of 3743 eligible nurses returned completed questionnaires (usable response rate=27.3%). One year later, Time 1 respondents were mailed a follow-up survey; 406 returned a completed questionnaire (response rate=39.8%). Surveys containing standardized questionnaires were mailed to participants' home address. Descriptive statistics, correlations, and hierarchical linear regression analyses were conducted using SPSS software. Overall, new graduate nurses were positive about their experiences and committed to nursing. However, over half of new nurses in the first year of practice reported high levels of emotional exhaustion and many witnessed or experienced incivility (24-42%) at work. Findings from hierarchical linear regression analyses revealed that situational and personal factors explained significant amounts of variance in new graduate nurses' job and career satisfaction and turnover intentions. Cynicism was a significant predictor of all four outcomes one year later, while Psycap predicted job and career satisfaction and career turnover intentions. Results provide a look into the worklife experiences of Canadian new graduate nurses over a one-year time period and identify factors that influence their job-related outcomes. These findings show that working conditions for new graduate nurses are generally positive and stable over time, although workplace mistreatment is an issue to be addressed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. The hierarchical structure of self-reported impulsivity

    PubMed Central

    Kirby, Kris N.; Finch, Julia C.

    2010-01-01

    The hierarchical structure of 95 self-reported impulsivity items, along with delay-discount rates for money, was examined. A large sample of college students participated in the study (N = 407). Items represented every previously proposed dimension of self-reported impulsivity. Exploratory PCA yielded at least 7 interpretable components: Prepared/Careful, Impetuous, Divertible, Thrill and Risk Seeking, Happy-Go-Lucky, Impatiently Pleasure Seeking, and Reserved. Discount rates loaded on Impatiently Pleasure Seeking, and correlated with the impulsiveness and venturesomeness scales from the I7 (Eysenck, Pearson, Easting, & Allsopp, 1985). The hierarchical emergence of the components was explored, and we show how this hierarchical structure may help organize conflicting dimensions found in previous analyses. Finally, we argue that the discounting model (Ainslie, 1975) provides a qualitative framework for understanding the dimensions of impulsivity. PMID:20224803

  5. Hierarchical biointerfaces assembled by leukocyte-inspired particles for specifically recognizing cancer cells.

    PubMed

    Meng, Jingxin; Liu, Hongliang; Liu, Xueli; Yang, Gao; Zhang, Pengchao; Wang, Shutao; Jiang, Lei

    2014-09-24

    By mimicking certain biochemical and physical attributes of biological cells, bio-inspired particles have attracted great attention for potential biomedical applications based on cell-like biological functions. Inspired by leukocytes, hierarchical biointerfaces are designed and prepared based on specific molecules-modified leukocyte-inspired particles. These biointerfaces can efficiently recognize cancer cells from whole blood samples through the synergistic effect of molecular recognition and topographical interaction. Compared to flat, mono-micro or nano-biointerfaces, these micro/nano hierarchical biointerfaces are better able to promote specific recognition interactions, resulting in an enhanced cell-capture efficiency. It is anticipated that this study may provide promising guidance to develop new bio-inspired hierarchical biointerfaces for biomedical applications. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Evaluating Sampling Efficiency in Depletion Surveys Using Hierarchical Bayes

    EPA Science Inventory

    Estimating animal abundance is essential to natural resource management and conservation. However, the cost associated with abundance estimation can be high for populations that are difficult to sample. Researchers, particularly in fisheries management, often sample such populati...

  7. A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields

    DOE PAGES

    Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto

    2017-10-26

    In this paper, we propose an alternative method to generate samples of a spatially correlated random field with applications to large-scale problems for forward propagation of uncertainty. A classical approach for generating these samples is the Karhunen--Loève (KL) decomposition. However, the KL expansion requires solving a dense eigenvalue problem and is therefore computationally infeasible for large-scale problems. Sampling methods based on stochastic partial differential equations provide a highly scalable way to sample Gaussian fields, but the resulting parametrization is mesh dependent. We propose a multilevel decomposition of the stochastic field to allow for scalable, hierarchical sampling based on solving amore » mixed finite element formulation of a stochastic reaction-diffusion equation with a random, white noise source function. Lastly, numerical experiments are presented to demonstrate the scalability of the sampling method as well as numerical results of multilevel Monte Carlo simulations for a subsurface porous media flow application using the proposed sampling method.« less

  8. A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields

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

    Osborn, Sarah; Vassilevski, Panayot S.; Villa, Umberto

    In this paper, we propose an alternative method to generate samples of a spatially correlated random field with applications to large-scale problems for forward propagation of uncertainty. A classical approach for generating these samples is the Karhunen--Loève (KL) decomposition. However, the KL expansion requires solving a dense eigenvalue problem and is therefore computationally infeasible for large-scale problems. Sampling methods based on stochastic partial differential equations provide a highly scalable way to sample Gaussian fields, but the resulting parametrization is mesh dependent. We propose a multilevel decomposition of the stochastic field to allow for scalable, hierarchical sampling based on solving amore » mixed finite element formulation of a stochastic reaction-diffusion equation with a random, white noise source function. Lastly, numerical experiments are presented to demonstrate the scalability of the sampling method as well as numerical results of multilevel Monte Carlo simulations for a subsurface porous media flow application using the proposed sampling method.« less

  9. A management-oriented classification of pinyon-juniper woodlands of the Great Basin

    Treesearch

    Neil E. West; Robin J. Tausch; Paul T. Tueller

    1998-01-01

    A hierarchical framework for the classification of Great Basin pinyon-juniper woodlands was based on a systematic sample of 426 stands from a random selection of 66 of the 110 mountain ranges in the region. That is, mountain ranges were randomly selected, but stands were systematically located on mountain ranges. The National Hierarchical Framework of Ecological Units...

  10. Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

    USGS Publications Warehouse

    Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.

    2010-01-01

    Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization-invertebrate response example is used to detail the multilevel hierarchical construction methodology, showing how the result is a set of models that are both statistically more rigorous and ecologically more interpretable than simple linear regression models.

  11. High School Grade Inflation from 2004 to 2011. ACT Research Report Series, 2013 (3)

    ERIC Educational Resources Information Center

    Zhang, Qian; Sanchez, Edgar I.

    2013-01-01

    This study explores inflation in high school grade point average (HSGPA), defined as trend over time in the conditional average of HSGPA, given ACT® Composite score. The time period considered is 2004 to 2011. Using hierarchical linear modeling, the study updates a previous analysis of Woodruff and Ziomek (2004). The study also investigates…

  12. A Hierarchical Linear Modeling Analysis of Working Memory and Implicit Prosody in the Resolution of Adjunct Attachment Ambiguity

    ERIC Educational Resources Information Center

    Traxler, Matthew J.

    2009-01-01

    An eye-movement monitoring experiment investigated readers' response to temporarily ambiguous sentences. The sentences were ambiguous because a relative clause could attach to one of two preceding nouns. Semantic information disambiguated the sentences. Working memory considerations predict an overall preference for the second of the two nouns, as…

  13. Equity in Educational Resources at the School Level in Korea

    ERIC Educational Resources Information Center

    Woo, Myung Suk

    2010-01-01

    This paper analyzed the equity of resources at the elementary school level in Korea using hierarchical linear modeling (HLM). The data included 2,327 Korean public elementary schools in 101 Local Governments within five Local Educational Offices (LEOs). This study found that schools in low property tax per resident areas receive fewer grants,…

  14. Teacher-Child Relationship Quality and Academic Achievement in Elementary School: Does Gender Matter?

    ERIC Educational Resources Information Center

    McCormick, Meghan P.; O'Connor, Erin E.

    2015-01-01

    Using data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (N = 1,364) and 2-level hierarchical linear models with site fixed effects, we examined between- and within-child associations between teacher-child relationship closeness and conflict and standardized measures of children's…

  15. A Multilevel Study of Students' Motivations of Studying Accounting: Implications for Employers

    ERIC Educational Resources Information Center

    Law, Philip; Yuen, Desmond

    2012-01-01

    Purpose: The purpose of this study is to examine the influence of factors affecting students' choice of accounting as a study major in Hong Kong. Design/methodology/approach: Multinomial logistic regression and Hierarchical Generalized Linear Modeling (HGLM) are used to analyze the survey data for the level one and level two data, which is the…

  16. A Multiple Risk Factors Model of the Development of Aggression among Early Adolescents from Urban Disadvantaged Neighborhoods

    ERIC Educational Resources Information Center

    Kim, Sangwon; Orpinas, Pamela; Kamphaus, Randy; Kelder, Steven H.

    2011-01-01

    This study empirically derived a multiple risk factors model of the development of aggression among middle school students in urban, low-income neighborhoods, using Hierarchical Linear Modeling (HLM). Results indicated that aggression increased from sixth to eighth grade. Additionally, the influences of four risk domains (individual, family,…

  17. Universal Beliefs and Specific Practices: Students' Math Self-Efficacy and Related Factors in the United States and China

    ERIC Educational Resources Information Center

    Wu, Yin

    2016-01-01

    This study intends to compare and contrast student and school factors that are associated with students' mathematics self-efficacy in the United States and China. Using hierarchical linear regressions to analyze the Programme for International Student Assessment (PISA) 2012 data, this study compares math self-efficacy, achievement, and variables…

  18. Trajectory of Life Satisfaction and Its Relationship with Subjective Economic Status and Successful Aging

    ERIC Educational Resources Information Center

    Hsu, Hui-Chuan

    2010-01-01

    The aim of the study was to explore the relationship between subjective economic status and indicators of successful aging to life satisfaction trajectories among the elderly in Taiwan. Data were from the four waves of "Survey of Health and Living Status of the Elderly in Taiwan". Hierarchical linear modeling was conducted. Subjective…

  19. Toward Addressing the Issues of Site Selection in District Effectiveness Research: A Two-Level Hierarchical Linear Growth Model

    ERIC Educational Resources Information Center

    Bowers, Alex J.

    2010-01-01

    Purpose: District effectiveness research (DER) is an emerging field concerned with identifying the organizational structures, administration, and leadership practices at the school district level that help districts find success with all of their students across the schools within the system. This work has mirrored much of the early school…

  20. Science Teaching Reform through Professional Development: Teachers' Use of a Scientific Classroom Discourse Community Model

    ERIC Educational Resources Information Center

    Lewis, Elizabeth B.; Baker, Dale R.; Helding, Brandon A.

    2015-01-01

    This report outlines a 2-year investigation into how secondary science teachers used professional development (PD) to build scientific classroom discourse communities (SCDCs). Observation data, teacher, student, and school demographic information were used to build a hierarchical linear model. The length of time that teachers received PD was the…

  1. Classification Based on Hierarchical Linear Models: The Need for Incorporation of Social Contexts in Classification Analysis

    ERIC Educational Resources Information Center

    Vaughn, Brandon K.; Wang, Qui

    2009-01-01

    Many areas in educational and psychological research involve the use of classification statistical analysis. For example, school districts might be interested in attaining variables that provide optimal prediction of school dropouts. In psychology, a researcher might be interested in the classification of a subject into a particular psychological…

  2. Modeling Reader and Text Interactions during Narrative Comprehension: A Test of the Lexical Quality Hypothesis

    ERIC Educational Resources Information Center

    Hamilton, Stephen T.; Freed, Erin M.; Long, Debra L.

    2013-01-01

    The goal of this study was to examine predictions derived from the Lexical Quality Hypothesis regarding relations among word decoding, working-memory capacity, and the ability to integrate new concepts into a developing discourse representation. Hierarchical Linear Modeling was used to quantify the effects of three text properties (length,…

  3. Does Access Matter? Time in General Education and Achievement for Students with Disabilities

    ERIC Educational Resources Information Center

    Cosier, Meghan; Causton-Theoharis, Julie; Theoharis, George

    2013-01-01

    This study examined the relationship between hours in general education and achievement in reading and mathematics for students with disabilities. The study population included more than 1,300 students between the ages of 6 and 9 years old within 180 school districts. Hierarchical linear modeling (HLM) was utilized with the Pre-Elementary…

  4. Psychosocial Development from College through Midlife: A 34-Year Sequential Study

    ERIC Educational Resources Information Center

    Whitbourne, Susan Krauss; Sneed, Joel R.; Sayer, Aline

    2009-01-01

    Two cohorts of alumni, leading-edge and trailing-edge baby boomers, first tested in their college years, were followed to ages 43 (N = 136) and 54 (N = 182) on a measure of Erikson's theory of psychosocial development. Hierarchical linear modeling was used to model the trajectory of growth for each psychosocial issue across middle adulthood. As…

  5. Analysis of Student Performance in Large-Enrollment Life Science Courses

    ERIC Educational Resources Information Center

    Creech, Leah Renee; Sweeder, Ryan D.

    2012-01-01

    This study examined the historical performance of students at Michigan State University in 12 life sciences courses over 13 yr to find variables impacting student success. Hierarchical linear modeling predicted 25.0-62.8% of the variance in students' grades in the courses analyzed. The primary predictor of a student's course grade was his or her…

  6. Connecting the Dots: How Connectedness to Multiple Contexts Influences the Psychological and Academic Adjustment of Urban Youth

    ERIC Educational Resources Information Center

    Witherspoon, Dawn; Schotland, Marieka; Way, Niobe; Hughes, Diane

    2009-01-01

    Cluster analyses and hierarchical linear modeling were used to investigate the impact of perceptions of connectedness to family, school, and neighborhood contexts on academic and psycho-social outcomes for 437 urban ethnically diverse adolescents. Five profiles of connectedness to family, school, and neighborhood were identified. Two profiles were…

  7. Does High School Facility Quality Affect Student Achievement? A Two-Level Hierarchical Linear Model

    ERIC Educational Resources Information Center

    Bowers, Alex J.; Urick, Angela

    2011-01-01

    The purpose of this study is to isolate the independent effects of high school facility quality on student achievement using a large, nationally representative U.S. database of student achievement and school facility quality. Prior research on linking school facility quality to student achievement has been mixed. Studies that relate overall…

  8. Building a Multicontextual Model of Latino College Enrollment: Student, School, and State-Level Effects

    ERIC Educational Resources Information Center

    Nunez, Anne-Marie; Kim, Dongbin

    2012-01-01

    Latinos' college enrollment rates, particularly in four-year institutions, have not kept pace with their population growth in the United States. Using three-level hierarchical generalized linear modeling, this study analyzes data from the Educational Longitudinal Study (ELS) to examine the influence of high school and state contexts, in addition…

  9. The Impact of School Environment and Grade Level on Student Delinquency: A Multilevel Modeling Approach

    ERIC Educational Resources Information Center

    Lo, Celia C.; Kim, Young S.; Allen, Thomas M.; Allen, Andrea N.; Minugh, P. Allison; Lomuto, Nicoletta

    2011-01-01

    Effects on delinquency made by grade level, school type (based on grade levels accommodated), and prosocial school climate were assessed, controlling for individual-level risk and protective factors. Data were obtained from the Substance Abuse Services Division of Alabama's state mental health agency and analyzed via hierarchical linear modeling,…

  10. Adolescents' as Active Agents in the Socialization Process: Legitimacy of Parental Authority and Obligation to Obey as Predictors of Obedience

    ERIC Educational Resources Information Center

    Darling, Nancy; Cumsille, Patricio; Loreto Martinez, M.

    2007-01-01

    Adolescents' agreement with parental standards and beliefs about the legitimacy of parental authority and their own obligation to obey were used to predict adolescents' obedience, controlling for parental monitoring, rules, and rule enforcement. Hierarchical linear models were used to predict both between-adolescent and within-adolescent,…

  11. Concordance of Interests in Dynamic Models of Social Partnership in the System of Continuing Professional Education

    ERIC Educational Resources Information Center

    Tarasenko, Larissa V.; Ougolnitsky, Guennady A.; Usov, Anatoly B.; Vaskov, Maksim A.; Kirik, Vladimir A.; Astoyanz, Margarita S.; Angel, Olga Y.

    2016-01-01

    A dynamic game theoretic model of concordance of interests in the process of social partnership in the system of continuing professional education is proposed. Non-cooperative, cooperative, and hierarchical setups are examined. Analytical solution for a linear state version of the model is provided. Nash equilibrium algorithms (for non-cooperative…

  12. Illustration of a Multilevel Model for Meta-Analysis

    ERIC Educational Resources Information Center

    de la Torre, Jimmy; Camilli, Gregory; Vargas, Sadako; Vernon, R. Fox

    2007-01-01

    In this article, the authors present a multilevel (or hierarchical linear) model that illustrates issues in the application of the model to data from meta-analytic studies. In doing so, several issues are discussed that typically arise in the course of a meta-analysis. These include the presence of non-zero between-study variability, how multiple…

  13. HLM in Cluster-Randomised Trials--Measuring Efficacy across Diverse Populations of Learners

    ERIC Educational Resources Information Center

    Hegedus, Stephen; Tapper, John; Dalton, Sara; Sloane, Finbarr

    2013-01-01

    We describe the application of Hierarchical Linear Modelling (HLM) in a cluster-randomised study to examine learning algebraic concepts and procedures in an innovative, technology-rich environment in the US. HLM is applied to measure the impact of such treatment on learning and on contextual variables. We provide a detailed description of such…

  14. Union Status and Faculty Job Satisfaction: Contemporary Evidence from the 2004 National Study of Postsecondary Faculty

    ERIC Educational Resources Information Center

    Myers, Carrie B.

    2011-01-01

    This study tests the association between union status and job satisfaction using 8,000+ U.S. faculty at four-year public institutions surveyed in the 2004 National Study of Postsecondary Faculty. The results from hierarchical linear models that included individual and institutional variables found that nonunion faculty reported significantly…

  15. Effects of a Reform High School Mathematics Curriculum on Student Achievement: Whom Does It Benefit?

    ERIC Educational Resources Information Center

    Krupa, Erin E.; Confrey, Jere

    2017-01-01

    This study compared the effects of an integrated reform-based curriculum to a subject-specific curriculum on student learning of 19,526 high school algebra students. Using hierarchical linear modelling to account for variation in student achievement, the impact of the reform-based "Core-Plus Mathematics" curricular materials on student…

  16. Parent Involvement and Children's Academic and Social Development in Elementary School

    ERIC Educational Resources Information Center

    El Nokali, Nermeen E.; Bachman, Heather J.; Votruba-Drzal, Elizabeth

    2010-01-01

    Data from the National Institute of Child Health and Human Development (NICHD) Study of Early Childcare and Youth Development (N = 1,364) were used to investigate children's trajectories of academic and social development across 1st, 3rd, and 5th grades. Hierarchical linear modeling was used to examine within- and between-child associations among…

  17. Parental Characteristics and the Achievement Gap in Mathematics: Hierarchical Linear Modeling Analysis of Longitudinal Study of American Youth (LSAY)

    ERIC Educational Resources Information Center

    Shoraka, Mohammad; Arnold, Robert; Kim, Eun Sook; Salinitri, Geri; Kromrey, Jeffrey

    2015-01-01

    One of the most salient problems in education is the achievement gap. The researchers investigated the effects of parental education and parental occupations in science, technology, engineering, mathematics, or medical professions (STEMM) on the achievement gap in mathematics. Because students were nested within schools, two-level Hierarchical…

  18. Division of Labor in German Dual-Earner Families: Testing Equity Theoretical Hypotheses

    ERIC Educational Resources Information Center

    Klumb, Petra; Hoppmann, Christiane; Staats, Melanie

    2006-01-01

    On the basis of 52 German dual-earner couples with at least 1 child younger than 5 years, we tested the effects of an unequal division of labor on relationship satisfaction. We analyzed diary reports of time allocated to productive activities according to the actor-partner-interdependence model. Hierarchical linear models showed that rather than…

  19. Relationships of Out-of-School-Time Mathematics Lessons to Mathematical Literacy in Singapore and Australia

    ERIC Educational Resources Information Center

    Kaur, Berinderjeet; Areepattamannil, Shaljan

    2013-01-01

    This study, drawing on date from the Programme for International Student Assessment (PISA) 2009, examined the relationships of out-of-school-time mathematics lessons to mathematical literacy in Singapore and Australia. Results of two-level hierarchical linear modelling (HLM) analyses revealed that out-of-school-time enrichment lessons in…

  20. Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology

    ERIC Educational Resources Information Center

    Long, Jeffrey D.; Loeber, Rolf; Farrington, David P.

    2009-01-01

    Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…

  1. For Richer, for Poorer: Money as a Topic of Marital Conflict in the Home

    ERIC Educational Resources Information Center

    Papp, Lauren M.; Cummings, E. Mark; Goeke-Morey, Marcie C.

    2009-01-01

    Guided by a family stress perspective, we examined the hypothesis that discussing money would be associated with the handling of marital conflict in the home. Analyses were based on dyadic hierarchical linear modeling of 100 husbands' and 100 wives' diary reports of 748 conflict instances. Contrary to findings from previous laboratory-based…

  2. Increasing Equity and Achievement in Fifth Grade Mathematics: The Contribution of Content Exposure

    ERIC Educational Resources Information Center

    Ottmar, Erin R.; Konold, Timothy R.; Berry, Robert Q.; Grissmer, David W.; Cameron, Claire E.

    2013-01-01

    This study uses a large nationally representative data set (ECLS-K) of 5,181 students to examine the extent to which exposure to content and instructional practice contributes to mathematics achievement in fifth grade. Using hierarchical linear modeling, results suggest that more exposure to content beyond numbers and operations (i.e., geometry,…

  3. Effect Sizes for Growth-Modeling Analysis for Controlled Clinical Trials in the Same Metric as for Classical Analysis

    ERIC Educational Resources Information Center

    Feingold, Alan

    2009-01-01

    The use of growth-modeling analysis (GMA)--including hierarchical linear models, latent growth models, and general estimating equations--to evaluate interventions in psychology, psychiatry, and prevention science has grown rapidly over the last decade. However, an effect size associated with the difference between the trajectories of the…

  4. The Influence of Classroom Disciplinary Climate of Schools on Reading Achievement: A Cross-Country Comparative Study

    ERIC Educational Resources Information Center

    Ning, Bo; Van Damme, Jan; Van Den Noortgate, Wim; Yang, Xiangdong; Gielen, Sarah

    2015-01-01

    Despite considerable interest in research and practice in the effect of classroom disciplinary climate of schools on academic achievement, little is known about the generalizability of this effect over countries. Using hierarchical linear analyses, the present study reveals that a better classroom disciplinary climate in a school is significantly…

  5. Bilingual Education in an Aboriginal Context: Examining the Transfer of Language Skills from Inuktitut to English or French

    ERIC Educational Resources Information Center

    Usborne, Esther; Caouette, Julie; Qumaaluk, Qiallak; Taylor, Donald M.

    2009-01-01

    Bilingual education is thought to be one of the principal means of simultaneously revitalizing threatened language and preparing students for success in mainstream society. However, little research has examined, in a comprehensive and longitudinal fashion, bilingual programs in Aboriginal contexts. Hierarchical linear modeling was used to conduct…

  6. Bullying Victimization and Student Engagement in Elementary, Middle, and High Schools: Moderating Role of School Climate

    ERIC Educational Resources Information Center

    Yang, Chunyan; Sharkey, Jill D.; Reed, Lauren A.; Chen, Chun; Dowdy, Erin

    2018-01-01

    Bullying is the most common form of school violence and is associated with a range of negative outcomes, including traumatic responses. This study used hierarchical linear modeling to examine the multilevel moderating effects of school climate and school level (i.e., elementary, middle, and high schools) on the association between bullying…

  7. Examining the Variability of Mathematics Performance and Its Correlates Using Data from TIMSS '95 and TIMSS '99

    ERIC Educational Resources Information Center

    O'Dwyer, Laura M.

    2005-01-01

    International studies in education provide researchers with opportunities to examine how students with both similar and dissimilar formal education systems perform on a single test and provide rich information about the relationships among student outcomes and the factors that affect them. Using hierarchical linear regression techniques and TIMSS…

  8. When Money Really Matters: Tying Resources of Specific Programmatic and Instructional Elements to Student Academic Growth

    ERIC Educational Resources Information Center

    Goetz, Michael Eric

    2012-01-01

    This study explores the cost-effectiveness ratios associated with individual tutoring, intensive reading/language arts instruction, and a focus on core subject areas. Using the Early Childhood Longitudinal Study (ECLS-K) database, this study analyzes these programs using a three-level hierarchical linear model (HLM) with a nationally…

  9. Obesity, High-Calorie Food Intake, and Academic Achievement Trends among U.S. School Children

    ERIC Educational Resources Information Center

    Li, Jian; O'Connell, Ann A.

    2012-01-01

    The authors investigated children's self-reported high-calorie food intake in Grade 5 and its relationship to trends in obesity status and academic achievement over the first 6 years of school. They used 3-level hierarchical linear models in the large-scale database (the Early Childhood Longitudinal Study--Kindergarten Cohort). Findings indicated…

  10. The Challenge of Separating Effects of Simultaneous Education Projects on Student Achievement

    ERIC Educational Resources Information Center

    Ma, Xin; Ma, Lingling

    2009-01-01

    When multiple education projects operate in an overlapping or rear-ended manner, it is always a challenge to separate unique project effects on schooling outcomes. Our analysis represents a first attempt to address this challenge. A three-level hierarchical linear model (HLM) was presented as a general analytical framework to separate program…

  11. Aspirations, Progress and Perceptions of Boys from a Single Sex School Following the Changeover to Coeducation

    ERIC Educational Resources Information Center

    Yates, Shirley M.

    2004-01-01

    Career and further education aspirations, educational progress and perceptions of the learning environment were measured annually over three years in primary and secondary boys from a single sex non-government school, following the changeover to coeducation. Hierarchical Linear Modelling analyses revealed the significant role played by the career…

  12. Making Sense of Students' Actions in an Open-Ended Virtual Laboratory Environment

    ERIC Educational Resources Information Center

    Gal, Ya'akov; Uzan, Oriel; Belford, Robert; Karabinos, Michael; Yaron, David

    2015-01-01

    A process for analyzing log files collected from open-ended learning environments is developed and tested on a virtual lab problem involving reaction stoichiometry. The process utilizes a set of visualization tools that, by grouping student actions in a hierarchical manner, helps experts make sense of the linear list of student actions recorded in…

  13. FRIT characterized hierarchical kernel memory arrangement for multiband palmprint recognition

    NASA Astrophysics Data System (ADS)

    Kisku, Dakshina R.; Gupta, Phalguni; Sing, Jamuna K.

    2015-10-01

    In this paper, we present a hierarchical kernel associative memory (H-KAM) based computational model with Finite Ridgelet Transform (FRIT) representation for multispectral palmprint recognition. To characterize a multispectral palmprint image, the Finite Ridgelet Transform is used to achieve a very compact and distinctive representation of linear singularities while it also captures the singularities along lines and edges. The proposed system makes use of Finite Ridgelet Transform to represent multispectral palmprint image and it is then modeled by Kernel Associative Memories. Finally, the recognition scheme is thoroughly tested with a benchmarking multispectral palmprint database CASIA. For recognition purpose a Bayesian classifier is used. The experimental results exhibit robustness of the proposed system under different wavelengths of palm image.

  14. Minimax terminal approach problem in two-level hierarchical nonlinear discrete-time dynamical system

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

    Shorikov, A. F., E-mail: afshorikov@mail.ru

    We consider a discrete–time dynamical system consisting of three controllable objects. The motions of all objects are given by the corresponding vector nonlinear or linear discrete–time recurrent vector relations, and control system for its has two levels: basic (first or I level) that is dominating and subordinate level (second or II level) and both have different criterions of functioning and united a priori by determined informational and control connections defined in advance. For the dynamical system in question, we propose a mathematical formalization in the form of solving a multistep problem of two-level hierarchical minimax program control over the terminalmore » approach process with incomplete information and give a general scheme for its solving.« less

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

    Chen, Chao; Pouransari, Hadi; Rajamanickam, Sivasankaran

    We present a parallel hierarchical solver for general sparse linear systems on distributed-memory machines. For large-scale problems, this fully algebraic algorithm is faster and more memory-efficient than sparse direct solvers because it exploits the low-rank structure of fill-in blocks. Depending on the accuracy of low-rank approximations, the hierarchical solver can be used either as a direct solver or as a preconditioner. The parallel algorithm is based on data decomposition and requires only local communication for updating boundary data on every processor. Moreover, the computation-to-communication ratio of the parallel algorithm is approximately the volume-to-surface-area ratio of the subdomain owned by everymore » processor. We also provide various numerical results to demonstrate the versatility and scalability of the parallel algorithm.« less

  16. On the usefulness of 'what' and 'where' pathways in vision.

    PubMed

    de Haan, Edward H F; Cowey, Alan

    2011-10-01

    The primate visual brain is classically portrayed as a large number of separate 'maps', each dedicated to the processing of specific visual cues, such as colour, motion or faces and their many features. In order to understand this fractionated architecture, the concept of cortical 'pathways' or 'streams' was introduced. In the currently prevailing view, the different maps are organised hierarchically into two major pathways, one involved in recognition and memory (the ventral stream or 'what' pathway) and the other in the programming of action (the dorsal stream or 'where' pathway). In this review, we question this heuristically influential but potentially misleading linear hierarchical pathway model and argue instead for a 'patchwork' or network model. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. Hierarchical macroscopic fibrillar adhesives: in situ study of buckling and adhesion mechanisms on wavy substrates.

    PubMed

    Bauer, Christina T; Kroner, Elmar; Fleck, Norman A; Arzt, Eduard

    2015-10-23

    Nature uses hierarchical fibrillar structures to mediate temporary adhesion to arbitrary substrates. Such structures provide high compliance such that the flat fibril tips can be better positioned with respect to asperities of a wavy rough substrate. We investigated the buckling and adhesion of hierarchically structured adhesives in contact with flat smooth, flat rough and wavy rough substrates. A macroscopic model for the structural adhesive was fabricated by molding polydimethylsiloxane into pillars of diameter in the range of 0.3-4.8 mm, with up to three different hierarchy levels. Both flat-ended and mushroom-shaped hierarchical samples buckled at preloads one quarter that of the single level structures. We explain this behavior by a change in the buckling mode; buckling leads to a loss of contact and diminishes adhesion. Our results indicate that hierarchical structures can have a strong influence on the degree of adhesion on both flat and wavy substrates. Strategies are discussed that achieve highly compliant substrates which adhere to rough substrates.

  18. Fabrication of hierarchical porous ZnO/NiO hollow microspheres for adsorptive removal of Congo red

    NASA Astrophysics Data System (ADS)

    Lei, Chunsheng; Pi, Meng; Cheng, Bei; Jiang, Chuanjia; Qin, Jiaqian

    2018-03-01

    Hierarchical porous zinc oxide (ZnO)/nickel(II) oxide (NiO) hollow microspheres were fabricated by a facile hydrothermal approach and subsequent calcination process. The synthesized samples were used as adsorbent for removing Congo red (CR), a commercial azo dye. The synthesized hierarchical porous ZnO/NiO composites exhibit a superior adsorption capacity for CR (518 mg/g), compared with pure NiO (397 mg/g) and ZnO (304 mg/g). The high CR adsorption capacity of ZnO/NiO composites was associated with its hierarchical porous hollow structures and large specific surface area (130 m2/g), which provide a large quantity of active sites for CR molecules. The adsorption kinetics data were perfectly fitted to a pseudo-second-order model. The isotherms were accurately described by the Langmuir model. The results suggest that the as-prepared hierarchical porous ZnO/NiO composites are a highly efficient adsorbent for treating organic dye-impacted wastewater.

  19. The program structure does not reliably recover the correct population structure when sampling is uneven: subsampling and new estimators alleviate the problem.

    PubMed

    Puechmaille, Sebastien J

    2016-05-01

    Inferences of population structure and more precisely the identification of genetically homogeneous groups of individuals are essential to the fields of ecology, evolutionary biology and conservation biology. Such population structure inferences are routinely investigated via the program structure implementing a Bayesian algorithm to identify groups of individuals at Hardy-Weinberg and linkage equilibrium. While the method is performing relatively well under various population models with even sampling between subpopulations, the robustness of the method to uneven sample size between subpopulations and/or hierarchical levels of population structure has not yet been tested despite being commonly encountered in empirical data sets. In this study, I used simulated and empirical microsatellite data sets to investigate the impact of uneven sample size between subpopulations and/or hierarchical levels of population structure on the detected population structure. The results demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure and downward-biased estimates of the true number of subpopulations. Distinct subpopulations with reduced sampling tended to be merged together, while at the same time, individuals from extensively sampled subpopulations were generally split, despite belonging to the same panmictic population. Four new supervised methods to detect the number of clusters were developed and tested as part of this study and were found to outperform the existing methods using both evenly and unevenly sampled data sets. Additionally, a subsampling strategy aiming to reduce sampling unevenness between subpopulations is presented and tested. These results altogether demonstrate that when sampling evenness is accounted for, the detection of the correct population structure is greatly improved. © 2016 John Wiley & Sons Ltd.

  20. Longitudinal data analyses using linear mixed models in SPSS: concepts, procedures and illustrations.

    PubMed

    Shek, Daniel T L; Ma, Cecilia M S

    2011-01-05

    Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

  1. Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

    PubMed Central

    Shek, Daniel T. L.; Ma, Cecilia M. S.

    2011-01-01

    Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented. PMID:21218263

  2. Hierarchical additive modeling of nonlinear association with spatial correlations--an application to relate alcohol outlet density and neighborhood assault rates.

    PubMed

    Yu, Qingzhao; Li, Bin; Scribner, Richard Allen

    2009-06-30

    Previous studies have suggested a link between alcohol outlets and assaults. In this paper, we explore the effects of alcohol availability on assaults at the census tract level over time. In addition, we use a natural experiment to check whether a sudden loss of alcohol outlets is associated with deeper decreasing in assault violence. Several features of the data raise statistical challenges: (1) the association between covariates (for example, the alcohol outlet density of each census tract) and the assault rates may be complex and therefore cannot be described using a linear model without covariates transformation, (2) the covariates may be highly correlated with each other, (3) there are a number of observations that have missing inputs, and (4) there is spatial association in assault rates at the census tract level. We propose a hierarchical additive model, where the nonlinear correlations and the complex interaction effects are modeled using the multiple additive regression trees and the residual spatial association in the assault rates that cannot be explained in the model are smoothed using a conditional autoregressive (CAR) method. We develop a two-stage algorithm that connects the nonparametric trees with CAR to look for important covariates associated with the assault rates, while taking into account the spatial association of assault rates in adjacent census tracts. The proposed method is applied to the Los Angeles assault data (1990-1999). To assess the efficiency of the method, the results are compared with those obtained from a hierarchical linear model. Copyright (c) 2009 John Wiley & Sons, Ltd.

  3. Room temperature synthesis and highly enhanced visible light photocatalytic activity of porous BiOI/BiOCl composites nanoplates microflowers.

    PubMed

    Dong, Fan; Sun, Yanjuan; Fu, Min; Wu, Zhongbiao; Lee, S C

    2012-06-15

    This research represents a highly enhanced visible light photocatalytic removal of 450 ppb level of nitric oxide (NO) in air by utilizing flower-like hierarchical porous BiOI/BiOCl composites synthesized by a room temperature template free method for the first time. The facile synthesis method avoids high temperature treatment, use of organic precursors and production of undesirable organic byproducts during synthesis process. The result indicated that the as-prepared BiOI/BiOCl composites samples were solid solution and were self-assembled hierarchically with single-crystal nanoplates. The aggregation of the self-assembled nanoplates resulted in the formation of 3D hierarchical porous architecture containing tri-model mesopores. The coupling to BiOI with BiOCl led to down-lowered valence band (VB) and up-lifted conduction band (CB) in contrast to BiOI, making the composites suitable for visible light excitation. The BiOI/BiOCl composites samples exhibited highly enhanced visible light photocatalytic activity for removal of NO in air due to the large surface areas and pore volume, hierarchical structure and modified band structure, exceeding that of P25, BiOI, C-doped TiO(2) and Bi(2)WO(6). This research results could provide a cost-effective approach for the synthesis of porous hierarchical materials and enhancement of photocatalyst performance for environmental and energetic applications owing to its low cost and easy scaling up. Copyright © 2012 Elsevier B.V. All rights reserved.

  4. Indirect estimates of natal dispersal distance from genetic data in a stream-dwelling fish (Mogurnda adspersa).

    PubMed

    Shipham, Ashlee; Schmidt, Daniel J; Hughes, Jane M

    2013-01-01

    Recent work has highlighted the need to account for hierarchical patterns of genetic structure when estimating evolutionary and ecological parameters of interest. This caution is particularly relevant to studies of riverine organisms, where hierarchical structure appears to be commonplace. Here, we indirectly estimate dispersal distance in a hierarchically structured freshwater fish, Mogurnda adspersa. Microsatellite and mitochondrial DNA (mtDNA) data were obtained for 443 individuals across 27 sites separated by an average of 1.3 km within creeks of southeastern Queensland, Australia. Significant genetic structure was found among sites (mtDNA Φ(ST) = 0.508; microsatellite F(ST) = 0.225, F'(ST) = 0.340). Various clustering methods produced congruent patterns of hierarchical structure reflecting stream architecture. Partial mantel tests identified contiguous sets of sample sites where isolation by distance (IBD) explained F(ST) variation without significant contribution of hierarchical structure. Analysis of mean natal dispersal distance (σ) within sets of IBD-linked sample sites suggested most dispersal occurs over less than 1 km, and the average effective density (D(e)) was estimated at 11.5 individuals km(-1); indicating sedentary behavior and small effective population size are responsible for the remarkable patterns of genetic structure observed. Our results demonstrate that Rousset's regression-based method is applicable to estimating the scale of dispersal in riverine organisms and that identifying contiguous populations that satisfy the assumptions of this model is achievable with genetic clustering methods and partial correlations.

  5. Detecting temporal trends in species assemblages with bootstrapping procedures and hierarchical models

    USGS Publications Warehouse

    Gotelli, Nicholas J.; Dorazio, Robert M.; Ellison, Aaron M.; Grossman, Gary D.

    2010-01-01

    Quantifying patterns of temporal trends in species assemblages is an important analytical challenge in community ecology. We describe methods of analysis that can be applied to a matrix of counts of individuals that is organized by species (rows) and time-ordered sampling periods (columns). We first developed a bootstrapping procedure to test the null hypothesis of random sampling from a stationary species abundance distribution with temporally varying sampling probabilities. This procedure can be modified to account for undetected species. We next developed a hierarchical model to estimate species-specific trends in abundance while accounting for species-specific probabilities of detection. We analysed two long-term datasets on stream fishes and grassland insects to demonstrate these methods. For both assemblages, the bootstrap test indicated that temporal trends in abundance were more heterogeneous than expected under the null model. We used the hierarchical model to estimate trends in abundance and identified sets of species in each assemblage that were steadily increasing, decreasing or remaining constant in abundance over more than a decade of standardized annual surveys. Our methods of analysis are broadly applicable to other ecological datasets, and they represent an advance over most existing procedures, which do not incorporate effects of incomplete sampling and imperfect detection.

  6. Efficient Parallel Formulations of Hierarchical Methods and Their Applications

    NASA Astrophysics Data System (ADS)

    Grama, Ananth Y.

    1996-01-01

    Hierarchical methods such as the Fast Multipole Method (FMM) and Barnes-Hut (BH) are used for rapid evaluation of potential (gravitational, electrostatic) fields in particle systems. They are also used for solving integral equations using boundary element methods. The linear systems arising from these methods are dense and are solved iteratively. Hierarchical methods reduce the complexity of the core matrix-vector product from O(n^2) to O(n log n) and the memory requirement from O(n^2) to O(n). We have developed highly scalable parallel formulations of a hybrid FMM/BH method that are capable of handling arbitrarily irregular distributions. We apply these formulations to astrophysical simulations of Plummer and Gaussian galaxies. We have used our parallel formulations to solve the integral form of the Laplace equation. We show that our parallel hierarchical mat-vecs yield high efficiency and overall performance even on relatively small problems. A problem containing approximately 200K nodes takes under a second to compute on 256 processors and yet yields over 85% efficiency. The efficiency and raw performance is expected to increase for bigger problems. For the 200K node problem, our code delivers about 5 GFLOPS of performance on a 256 processor T3D. This is impressive considering the fact that the problem has floating point divides and roots, and very little locality resulting in poor cache performance. A dense matrix-vector product of the same dimensions would require about 0.5 TeraBytes of memory and about 770 TeraFLOPS of computing speed. Clearly, if the loss in accuracy resulting from the use of hierarchical methods is acceptable, our code yields significant savings in time and memory. We also study the convergence of a GMRES solver built around this mat-vec. We accelerate the convergence of the solver using three preconditioning techniques: diagonal scaling, block-diagonal preconditioning, and inner-outer preconditioning. We study the performance and parallel efficiency of these preconditioned solvers. Using this solver, we solve dense linear systems with hundreds of thousands of unknowns. Solving a 105K unknown problem takes about 10 minutes on a 64 processor T3D. Until very recently, boundary element problems of this magnitude could not even be generated, let alone solved.

  7. Sensory processing and world modeling for an active ranging device

    NASA Technical Reports Server (NTRS)

    Hong, Tsai-Hong; Wu, Angela Y.

    1991-01-01

    In this project, we studied world modeling and sensory processing for laser range data. World Model data representation and operation were defined. Sensory processing algorithms for point processing and linear feature detection were designed and implemented. The interface between world modeling and sensory processing in the Servo and Primitive levels was investigated and implemented. In the primitive level, linear features detectors for edges were also implemented, analyzed and compared. The existing world model representations is surveyed. Also presented is the design and implementation of the Y-frame model, a hierarchical world model. The interfaces between the world model module and the sensory processing module are discussed as well as the linear feature detectors that were designed and implemented.

  8. Effect of Al substitution on the microstructure and lithium storage performance of nickel hydroxide

    NASA Astrophysics Data System (ADS)

    Li, Yanwei; Pan, Guanlin; Xu, Wenqiang; Yao, Jinhuan; Zhang, Lingzhi

    2016-03-01

    Al-substituted Ni(OH)2 samples with Al3+/Ni2+ mole ratio of 0%, 10% and 20% have been prepared by a very facile chemical co-precipitation method. The microstructure of the prepared samples are analyzed by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), thermo-gravimetric analysis (TGA), and Field emission scanning electron microscopy (FESEM). The results reveal that the pure Ni(OH)2 sample is β-Ni(OH)2 with nanosheets hierarchical structure; the sample with 10% Al is mixed phase α/β-Ni(OH)2 with hybrid nanosheets/nanoparticles hierarchical structure; the sample with 20% Al is α-Ni(OH)2 with irregular nanoparticles hierarchical structure. The lithium storage performances of the prepared samples are characterized by cyclic voltammograms (CV), electrochemical impedance spectroscopy (EIS), and charge-discharge tests. The results demonstrate that Al substitution could improve the lithium storage performances of nickel hydroxide. In particular, the mixed phase α/β-Ni(OH)2 with 10% Al exhibited the highest electrochemical activity, the best rate performance, and superior cycling stability. For example, after 30 charge/discharge cycles under a current density of 200 mA g-1, the mixed phase α/β-Ni(OH)2 with 10% Al can still deliver a specific discharge capacity of 964 mAh g-1, much higher than of for the α-Ni(OH)2 with 20% Al (681 mAh g-1) and the pure Ni(OH)2 (419 mAh g-1).

  9. Hierarchical porous photoanode based on acid boric catalyzed sol for dye sensitized solar cells

    NASA Astrophysics Data System (ADS)

    Maleki, Khatereh; Abdizadeh, Hossein; Golobostanfard, Mohammad Reza; Adelfar, Razieh

    2017-02-01

    The hierarchical porous photoanode of the dye sensitized solar cell (DSSC) is synthesized through non-aqueous sol-gel method based on H3BO3 as an acid catalyst and the efficiencies of the fabricated DSSC based on these photoanodes are compared. The sol parameters of 0.17 M, water mole ratio of 4.5, acid mole ratio of 0.45, and solvent type of ethanol are introduced as optimum parameters for photoanode formation without any detectable cracks. The optimized hierarchical photoanode mainly contains anatase phase with slight shift toward higher angles, confirming the doping of boron into titania structure. Moreover, the porous structure involves two ranges of average pore sizes of 20 and 635 nm. The diffuse reflectance spectroscopy (DRS) shows the proper scattering and blueshift in band gap. The paste parameters of solid:liquid, TiO2:ethyl cellulose, and terpineol:ethanol equal to 11:89, 3.5:7.5, and 25:64, respectively, are assigned as optimized parameters for this novel paste. The photovoltaic properties of short circuit current density, open circuit voltage, fill factor, and efficiency of 5.89 mA/cm2, 703 mV, 0.7, and 2.91% are obtained for the optimized sample, respectively. The relatively higher short circuit current of the main sample compared to other samples is mainly due to higher dye adsorption in this sample corresponding to its higher surface area and presumably higher charge transfer confirmed by low RS and Rct in electrochemical impedance spectroscopy data. Boric acid as a catalyst in titania sol not only forms hierarchical porous structure, but also dopes the titania lattice, which results in appreciated performance in this device.

  10. Fabrication of malachite with a hierarchical sphere-like architecture.

    PubMed

    Xu, Jiasheng; Xue, Dongfeng

    2005-09-15

    Malachite (Cu2(OH)2CO3) with a hierarchical sphere-like architecture has been successfully synthesized via a simple and mild hydrothermal route in the absence of any external inorganic additives or organic structure-directing templates. Powder X-ray diffraction, scanning electron microscopy, and Fourier transmission infrared spectrometry are used to characterize various properties of the obtained malachite samples. The hierarchical malachite particles are uniform spheres with a diameter of 10-20 microm, which are comprised of numerous two-dimensional microplatelets paralleling the sphere surface. The initial concentration of reagents, the hydrothermal reaction time, and temperature are important factors which dominantly affect the evolution of crystal morphologies. The growth of the hierarchical architecture is believed to be a layer-by-layer growth process. Further, copper oxide with the similar morphology can be easily obtained from the as-prepared malachite.

  11. Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

    NASA Astrophysics Data System (ADS)

    Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

    2014-03-01

    This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

  12. Hierarchical multiple regression modelling on predictors of behavior and sexual practices at Takoradi Polytechnic, Ghana.

    PubMed

    Turkson, Anthony Joe; Otchey, James Eric

    2015-01-14

    Various psychosocial studies on health related lifestyles lay emphasis on the fact that the perception one has of himself as being at risk of HIV/AIDS infection was a necessary condition for preventive behaviors to be adopted. Hierarchical Multiple Regression models was used to examine the relationship between eight independent variables and one dependent variable to isolate predictors which have significant influence on behavior and sexual practices. A Cross-sectional design was used for the study. Structured close-ended interviewer-administered questionnaire was used to collect primary data. Multistage stratified technique was used to sample views from 380 students from Takoradi Polytechnic, Ghana. A Hierarchical multiple regression model was used to ascertain the significance of certain predictors of sexual behavior and practices. The variables that were extracted from the multiple regression were; for the constant; Beta=14.202, t=2.279, p=0.023, variable is significant; for the marital status; Beta=0.092, t=1.996, p<0.05, variable is significant; for the knowledge on AIDs; Beta=0.090, t=1.996, p<0.05, variable is significant; for the attitude towards HIV/AIDs; =0.486, t=10.575, p<0.001, variable is highly significant. Thus, the best fitting model for predicting behavior and sexual practices was a linear combination of the constant, one's marital status, knowledge on HIV/AIDs and Attitude towards HIV/AIDs., Y(Behavior and sexual practies)= Beta0+Beta1(Marital status)+Beta2(Knowledge on HIV/AIDs issues)+Beta3(Attitude towards HIV/AIDs issues) Beta0, Beta1, Beta2 and Beta3 are respectively 14.201, 2.038, 0.148 and 0.486; the higher the better. Attitude and behavior change education on HIV/AIDs should be intensified in the institution so that students could adopt better lifestyles.

  13. Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis.

    PubMed

    Fernández-Arjona, María Del Mar; Grondona, Jesús M; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D

    2017-01-01

    It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor.

  14. Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis

    PubMed Central

    Fernández-Arjona, María del Mar; Grondona, Jesús M.; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D.

    2017-01-01

    It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor. PMID:28848398

  15. The organizational social context of mental health services and clinician attitudes toward evidence-based practice: a United States national study

    PubMed Central

    2012-01-01

    Background Evidence-based practices have not been routinely adopted in community mental health organizations despite the support of scientific evidence and in some cases even legislative or regulatory action. We examined the association of clinician attitudes toward evidence-based practice with organizational culture, climate, and other characteristics in a nationally representative sample of mental health organizations in the United States. Methods In-person, group-administered surveys were conducted with a sample of 1,112 mental health service providers in a nationwide sample of 100 mental health service institutions in 26 states in the United States. The study examines these associations with a two-level Hierarchical Linear Modeling (HLM) analysis of responses to the Evidence-Based Practice Attitude Scale (EBPAS) at the individual clinician level as a function of the Organizational Social Context (OSC) measure at the organizational level, controlling for other organization and clinician characteristics. Results We found that more proficient organizational cultures and more engaged and less stressful organizational climates were associated with positive clinician attitudes toward adopting evidence-based practice. Conclusions The findings suggest that organizational intervention strategies for improving the organizational social context of mental health services may contribute to the success of evidence-based practice dissemination and implementation efforts by influencing clinician attitudes. PMID:22726759

  16. Determination of Ignitable Liquids in Fire Debris: Direct Analysis by Electronic Nose

    PubMed Central

    Ferreiro-González, Marta; Barbero, Gerardo F.; Palma, Miguel; Ayuso, Jesús; Álvarez, José A.; Barroso, Carmelo G.

    2016-01-01

    Arsonists usually use an accelerant in order to start or accelerate a fire. The most widely used analytical method to determine the presence of such accelerants consists of a pre-concentration step of the ignitable liquid residues followed by chromatographic analysis. A rapid analytical method based on headspace-mass spectrometry electronic nose (E-Nose) has been developed for the analysis of Ignitable Liquid Residues (ILRs). The working conditions for the E-Nose analytical procedure were optimized by studying different fire debris samples. The optimized experimental variables were related to headspace generation, specifically, incubation temperature and incubation time. The optimal conditions were 115 °C and 10 min for these two parameters. Chemometric tools such as hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA) were applied to the MS data (45–200 m/z) to establish the most suitable spectroscopic signals for the discrimination of several ignitable liquids. The optimized method was applied to a set of fire debris samples. In order to simulate post-burn samples several ignitable liquids (gasoline, diesel, citronella, kerosene, paraffin) were used to ignite different substrates (wood, cotton, cork, paper and paperboard). A full discrimination was obtained on using discriminant analysis. This method reported here can be considered as a green technique for fire debris analyses. PMID:27187407

  17. Aerobic Capacity and Cognitive Control in Elementary School-Age Children

    PubMed Central

    Scudder, Mark R.; Lambourne, Kate; Drollette, Eric S.; Herrmann, Stephen; Washburn, Richard; Donnelly, Joseph E.; Hillman, Charles H.

    2014-01-01

    Purpose The current study examined the relationship between children’s performance on the Progressive Aerobic Cardiovascular Endurance Run (PACER) subtest of the FitnessGram® and aspects of cognitive control that are believed to support academic success. Methods Hierarchical linear regression analyses were conducted on a sample of 2nd and 3rd grade children (n = 397) who completed modified versions of a flanker task and spatial n-back task to assess inhibitory control and working memory, respectively. Results Greater aerobic fitness was significantly related to shorter reaction time and superior accuracy during the flanker task, suggesting better inhibitory control and the facilitation of attention in higher fit children. A similar result was observed for the n-back task such that higher fit children exhibited more accurate target detection and discrimination performance when working memory demands were increased. Conclusion These findings support the positive association between aerobic fitness and multiple aspects of cognitive control in a large sample of children, using a widely implemented and reliable field estimate of aerobic capacity. Importantly, the current results suggest that this relationship is consistent across methods used to assess fitness, which may have important implications for extending this research to more representative samples of children in a variety of experimental contexts. PMID:24743109

  18. Decentralization, stabilization, and estimation of large-scale linear systems

    NASA Technical Reports Server (NTRS)

    Siljak, D. D.; Vukcevic, M. B.

    1976-01-01

    In this short paper we consider three closely related aspects of large-scale systems: decentralization, stabilization, and estimation. A method is proposed to decompose a large linear system into a number of interconnected subsystems with decentralized (scalar) inputs or outputs. The procedure is preliminary to the hierarchic stabilization and estimation of linear systems and is performed on the subsystem level. A multilevel control scheme based upon the decomposition-aggregation method is developed for stabilization of input-decentralized linear systems Local linear feedback controllers are used to stabilize each decoupled subsystem, while global linear feedback controllers are utilized to minimize the coupling effect among the subsystems. Systems stabilized by the method have a tolerance to a wide class of nonlinearities in subsystem coupling and high reliability with respect to structural perturbations. The proposed output-decentralization and stabilization schemes can be used directly to construct asymptotic state estimators for large linear systems on the subsystem level. The problem of dimensionality is resolved by constructing a number of low-order estimators, thus avoiding a design of a single estimator for the overall system.

  19. Void statistics of the CfA redshift survey

    NASA Technical Reports Server (NTRS)

    Vogeley, Michael S.; Geller, Margaret J.; Huchra, John P.

    1991-01-01

    Clustering properties of two samples from the CfA redshift survey, each containing about 2500 galaxies, are studied. A comparison of the velocity distributions via a K-S test reveals structure on scales comparable with the extent of the survey. The void probability function (VPF) is employed for these samples to examine the structure and to test for scaling relations in the galaxy distribution. The galaxy correlation function is calculated via moments of galaxy counts. The shape and amplitude of the correlation function roughly agree with previous determinations. The VPFs for distance-limited samples of the CfA survey do not match the scaling relation predicted by the hierarchical clustering models. On scales not greater than 10/h Mpc, the VPFs for these samples roughly follow the hierarchical pattern. A variant of the VPF which uses nearly all the data in magnitude-limited samples is introduced; it accounts for the variation of the sampling density with velocity in a magnitude-limited survey.

  20. Void statistics of the CfA redshift survey

    NASA Astrophysics Data System (ADS)

    Vogeley, Michael S.; Geller, Margaret J.; Huchra, John P.

    1991-11-01

    Clustering properties of two samples from the CfA redshift survey, each containing about 2500 galaxies, are studied. A comparison of the velocity distributions via a K-S test reveals structure on scales comparable with the extent of the survey. The void probability function (VPF) is employed for these samples to examine the structure and to test for scaling relations in the galaxy distribution. The galaxy correlation function is calculated via moments of galaxy counts. The shape and amplitude of the correlation function roughly agree with previous determinations. The VPFs for distance-limited samples of the CfA survey do not match the scaling relation predicted by the hierarchical clustering models. On scales not greater than 10/h Mpc, the VPFs for these samples roughly follow the hierarchical pattern. A variant of the VPF which uses nearly all the data in magnitude-limited samples is introduced; it accounts for the variation of the sampling density with velocity in a magnitude-limited survey.

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